From be55fec97982d2767cf80232f3447e3c56a1bf86 Mon Sep 17 00:00:00 2001
From: Alistair Sellar <alistair.sellar@metoffice.gov.uk>
Date: Tue, 20 Jun 2023 12:48:56 +0100
Subject: [PATCH 01/93] Generate climatology on the fly for AutoAssess soil
 moisture (#3197)

Co-authored-by: Bouwe Andela <b.andela@esciencecenter.nl>
---
 .../source/recipes/broken_recipe_list.rst     |   4 -
 ...pe_autoassess_landsurface_soilmoisture.rst |  66 +----
 esmvaltool/config-references.yml              |   6 +-
 .../autoassess/_plot_mo_metrics.py            |  34 ++-
 .../land_surface_soilmoisture/soilmoisture.py | 261 +++++++++++++-----
 .../autoassess/plot_autoassess_metrics.py     |   7 +-
 ...pe_autoassess_landsurface_soilmoisture.yml |  27 +-
 7 files changed, 252 insertions(+), 153 deletions(-)

diff --git a/doc/sphinx/source/recipes/broken_recipe_list.rst b/doc/sphinx/source/recipes/broken_recipe_list.rst
index 7da6f41437..5720261827 100644
--- a/doc/sphinx/source/recipes/broken_recipe_list.rst
+++ b/doc/sphinx/source/recipes/broken_recipe_list.rst
@@ -16,10 +16,6 @@ More details can be found in the :ref:`broken recipe policy
      - Affected diagnostics
      - Problem
      - GitHub issue 
-   * - :ref:`recipe_autoassess_landsurface_soilmoisture.yml <recipe_autoassess_landsurface_soilmoisture.rst>`
-     - All
-     - Dependency on some external climatology files
-     - `#2309 <https://github.com/ESMValGroup/ESMValTool/issues/2309>`_
    * - `recipe_check_obs.yml`
      - `ERA5_native6`
      - Derivation of custom variables `rlus` and `rsus`
diff --git a/doc/sphinx/source/recipes/recipe_autoassess_landsurface_soilmoisture.rst b/doc/sphinx/source/recipes/recipe_autoassess_landsurface_soilmoisture.rst
index 9734498df8..5ba790b093 100644
--- a/doc/sphinx/source/recipes/recipe_autoassess_landsurface_soilmoisture.rst
+++ b/doc/sphinx/source/recipes/recipe_autoassess_landsurface_soilmoisture.rst
@@ -17,6 +17,7 @@ Performance metrics:
 
 Metrics are calculated using model and observation multi-year climatologies (seasonal means) 
 for meteorological seasons:
+
 * December-January-February (djf)
 * March-April-May (mam)
 * June-July-August (jja)
@@ -38,7 +39,6 @@ Recipes are stored in esmvaltool/recipes/
 
 Diagnostics are stored in esmvaltool/diag_scripts/autoassess/
 
-    * autoassess_area_base.py: wrapper for autoassess scripts
     * land_surface_soilmoisture/soilmoisture.py: script to calculate soil moisture
       metrics
     * plot_autoassess_metrics.py: plot normalised assessment metrics
@@ -47,21 +47,17 @@ Diagnostics are stored in esmvaltool/diag_scripts/autoassess/
 User settings in recipe
 -----------------------
 
-#. Script autoassess_area_base.py
+#. Script soilmoisture.py
 
    *Required settings for script*
 
    * area: must equal land_surface_soilmoisture to select this diagnostic
    * control_model: name of model to be used as control
    * exp_model: name of model to be used as experiment
-   * start: date (YYYY/MM/DD) at which period begins (see note on time gating)
-   * end: date (YYYY/MM/DD) at which period ends (see note on time gating)
-   * climfiles_root: path to observation climatologies
 
    *Optional settings for script*
 
-   * title: arbitrary string with name of diagnostic
-   * obs_models: unused for this recipe
+   none
 
    *Required settings for variables*
 
@@ -97,7 +93,8 @@ User settings in recipe
 Variables
 ---------
 
-* mrsos (land, monthly mean, longitude latitude time)
+* mrsos (from models: land, monthly mean, longitude latitude time)
+* sm (from observations: land, monthly mean, longitude latitude time)
 
 
 Observations and reformat scripts
@@ -122,56 +119,3 @@ Example plots
    :alt: Soilmoisture_Metrics.png
 
    Normalised metrics plot comparing a control and experiment simulation
-
-
-Additional notes on usage
--------------------------
-The ``landsurface_soilmoisture`` area metric is part of the ``esmvaltool/diag_scripts/autoassess`` diagnostics,
-and, as any other ``autoassess`` metric, it uses the ``autoassess_area_base.py`` as general purpose
-wrapper. This wrapper accepts a number of input arguments that are read through from the recipe.
-
-This recipe is part of the larger group of Autoassess metrics ported to ESMValTool
-from the native Autoassess package from the UK's Met Office. The ``diagnostics`` settings
-are almost the same as for the other Autoassess metrics.
-
-**Currently this recipe is marked as broken, because it only runs on Jasmin due to a dependency on some 
-external climatology files.**
-
-.. note::
-
-   **Time gating for autoassess metrics.**
-
-   To preserve the native Autoassess functionalities,
-   data loading and selection on time is done somewhat
-   differently for ESMValTool's autoassess metrics: the
-   time selection is done in the preprocessor as per usual but
-   a further time selection is performed as part of the diagnostic.
-   For this purpose the user will specify a ``start:`` and ``end:``
-   pair of arguments of ``scripts: autoassess_script`` (see below
-   for example). These are formatted as ``YYYY/MM/DD``; this is
-   necessary since the Autoassess metrics are computed from 1-Dec
-   through 1-Dec rather than 1-Jan through 1-Jan. This is a temporary
-   implementation to fully replicate the native Autoassess functionality
-   and a minor user inconvenience since they need to set an extra set of
-   ``start`` and ``end`` arguments in the diagnostic; this will be phased
-   when all the native Autoassess metrics have been ported to ESMValTool
-   review has completed.
-
-
-An example of standard inputs as read by ``autoassess_area_base.py`` and passed
-over to the diagnostic/metric is listed below.
-
-
-.. code-block:: yaml
-
-    scripts:
-      autoassess_landsurf_soilmoisture: &autoassess_landsurf_soilmoisture_settings
-        script: autoassess/autoassess_area_base.py
-        title: "Autoassess Land-Surface Soilmoisture Diagnostic"
-        area: land_surface_soilmoisture
-        control_model: IPSL-CM5A-LR
-        exp_model: inmcm4
-        obs_models: []
-        start: 1997/12/01
-        end: 2002/12/01
-        climfiles_root: '/gws/nopw/j04/esmeval/autoassess_specific_files/files'  # on JASMIN
diff --git a/esmvaltool/config-references.yml b/esmvaltool/config-references.yml
index f48ac9a6ab..baaaa44c96 100644
--- a/esmvaltool/config-references.yml
+++ b/esmvaltool/config-references.yml
@@ -597,7 +597,7 @@ authors:
   sellar_alistair:
     name: Sellar, Alistair
     institute: MetOffice, UK
-    orcid:
+    orcid: 0000-0002-2955-7254
   wyser_klaus:
     name: Wyser, Klaus
     institute: SMHI, Sweden
@@ -668,6 +668,10 @@ authors:
     institute:
     orcid:
     github: mcreader97
+  rumbold_heather:
+    name: Heather, Rumbold
+    institute: Met Office, UK
+    orcid:
   senftleben_daniel:
     name: Senftleben, Daniel
     institute: DLR, Germany
diff --git a/esmvaltool/diag_scripts/autoassess/_plot_mo_metrics.py b/esmvaltool/diag_scripts/autoassess/_plot_mo_metrics.py
index 425cdbd0b6..52eca796ab 100644
--- a/esmvaltool/diag_scripts/autoassess/_plot_mo_metrics.py
+++ b/esmvaltool/diag_scripts/autoassess/_plot_mo_metrics.py
@@ -13,6 +13,8 @@
 import matplotlib.pyplot as plt
 import numpy as np
 
+from esmvaltool.diag_scripts.shared import save_figure
+
 # Define some colours
 BLACK = '#000000'
 RED = '#FF0000'
@@ -596,7 +598,8 @@ def plot_nac(cref,
              acc=None,
              extend_y=False,
              title=None,
-             ofile=None):
+             ofile=None,
+             config=None):
     """
     Routine to produce NAC plot.
 
@@ -611,6 +614,7 @@ def plot_nac(cref,
     :param bool extend_y: Extend y-axis to include obs/acc ranges
     :param str title: Plot title
     :param str ofile: Plot file name
+    :param dict config: ESMValTool configuration object
     """
     # initialize
     if metrics is None:
@@ -682,15 +686,31 @@ def plot_nac(cref,
     legend.set_title('Vs %s' % cref, prop={'size': 'small'})
 
     # Display or produce file
-    if ofile:
-        # Create directory to write file to
-        odir = os.path.dirname(ofile)
-        if not os.path.isdir(odir):
-            os.makedirs(odir)
+    if ofile and config:
+        os.makedirs(config['plot_dir'], exist_ok=True)
+        provenance = get_provenance_record(config)
         # Note that bbox_inches only works for png plots
-        plt.savefig(ofile, bbox_extra_artists=(legend, ), bbox_inches='tight')
+        save_figure(ofile, provenance, config, fig,
+                    bbox_extra_artists=(legend, ), bbox_inches='tight')
     else:
         # Need the following to attempt to display legend in frame
         fig.subplots_adjust(right=0.85)
         plt.show()
     plt.close()
+
+
+def get_provenance_record(config):
+    """Create a provenance record describing the diagnostic data and plot."""
+    filenames = [item["filename"] for item in config["input_data"].values()]
+    record = {
+        'caption': 'Normalised assessment criteria plot',
+        'plot_type': 'metrics',
+        'authors': [
+            'williams_keith',
+            'predoi_valeriu',
+            'sellar_alistair'
+        ],
+        "ancestors": filenames,
+    }
+
+    return record
diff --git a/esmvaltool/diag_scripts/autoassess/land_surface_soilmoisture/soilmoisture.py b/esmvaltool/diag_scripts/autoassess/land_surface_soilmoisture/soilmoisture.py
index 85d6a7dc02..0533b94eed 100644
--- a/esmvaltool/diag_scripts/autoassess/land_surface_soilmoisture/soilmoisture.py
+++ b/esmvaltool/diag_scripts/autoassess/land_surface_soilmoisture/soilmoisture.py
@@ -2,16 +2,25 @@
 
 import os
 import logging
+import csv
+from collections.abc import Iterable
 import numpy as np
 import iris
 from esmvalcore.preprocessor import regrid
 from esmvaltool.diag_scripts.shared._base import ProvenanceLogger
-from esmvaltool.diag_scripts.shared._supermeans import get_supermean
+from esmvaltool.diag_scripts.shared import (
+    group_metadata,
+    run_diagnostic,
+    save_data,
+)
+
+# Order of seasons must agree with preprocessor definition in recipe
+SEASONS = ("djf", "mam", "jja", "son")
 
 logger = logging.getLogger(__name__)
 
 
-def get_provenance_record(caption, run):
+def get_provenance_record(caption, ancestor_filenames):
     """Create a provenance record describing the diagnostic data and plot."""
     record = {
         'caption': caption,
@@ -27,69 +36,142 @@ def get_provenance_record(caption, run):
             'dorigo17rse',
             'gruber19essd',
         ],
-        'ancestors': run,
+        "ancestors": ancestor_filenames,
     }
 
     return record
 
 
-def land_sm_top(run):
+def write_metrics(output_dir, metrics, config, ancestors):
+    """Write metrics to CSV file.
+
+    The CSV file will have the name ``metrics.csv`` and can be
+    used for the normalised metric assessment plot.
+
+    Parameters
+    ----------
+    output_dir : string
+        The full path to the directory in which the CSV file will be written.
+    metrics : dictionary of metric,value pairs
+        The seasonal data to write.
+    config : dictionary
+        ESMValTool configuration object
+    ancestors : list
+        Filenames of input files for provenance
+    """
+    os.makedirs(output_dir, exist_ok=True)
+
+    file_name = "metrics.csv"
+    file_path = os.path.join(output_dir, file_name)
+
+    with open(file_path, "w", newline="", encoding="utf-8") as csvfile:
+        csv_writer = csv.writer(csvfile)
+        for line in metrics.items():
+            csv_writer.writerow(line)
+
+    record_provenance(file_path, config, ancestors)
+
+
+def volumetric_soil_moisture(model_file, constr_season):
+    """
+    Read moisture mass content and convert to volumetric soil moisture.
+
+    Parameters
+    ----------
+    model_file : string
+        Path to model file
+    constr_season : iris constraint
+        Constraint on season to load
+
+    Returns
+    -------
+    vol_sm1_run : cube
+        Volumetric soil moisture
+    """
+    # Constant: density of water
+    rhow = 1000.
+
+    # m01s08i223
+    # CMOR name: mrsos (soil moisture in top model layer kg/m2)
+    mrsos = iris.load_cube(
+        model_file,
+        "mass_content_of_water_in_soil_layer" & constr_season
+    )
+
+    # Set soil moisture to missing data where no soil (moisture=0)
+    np.ma.masked_where(mrsos.data == 0, mrsos.data, copy=False)
+
+    # first soil layer depth
+    dz1 = mrsos.coord('depth').bounds[0, 1] - \
+        mrsos.coord('depth').bounds[0, 0]
+
+    # Calculate the volumetric soil moisture in m3/m3
+    # volumetric soil moisture = volume of water / volume of soil layer
+    # = depth equivalent of water / thickness of soil layer
+    # = (soil moisture content (kg m-2) / water density (kg m-3) )  /
+    #      soil layer thickness (m)
+    # = mosrs / (rhow * dz1)
+    vol_sm1_run = mrsos / (rhow * dz1)
+    vol_sm1_run.units = "m3 m-3"
+    vol_sm1_run.long_name = "Top layer Soil Moisture"
+
+    return vol_sm1_run
+
+
+def flatten(list_of_lists):
+    """
+    Convert list of lists into a flat list, allowing some items to be non-list.
+
+    Parameters
+    ----------
+    list_of_lists : list
+        List containing iterables to flatten, plus optionally non-list items
+
+    Returns
+    -------
+    flattened : list
+        Flattened list with one level of nesting removed
+    """
+    flattened = []
+    for item in list_of_lists:
+        if isinstance(item, Iterable) and not isinstance(item, (str, bytes)):
+            flattened.extend(item)
+        else:
+            flattened.append(item)
+
+    return flattened
+
+
+def land_sm_top(clim_file, model_file, model_dataset, config, ancestors):
     """
     Calculate median absolute errors for soil mosture against CCI data.
 
     Parameters
     ----------
-    run: dict
-        dictionary containing model run metadata
-        (see auto_assess/model_run.py for description)
+    clim_file : string
+        Path to observation climatology file
+    model_file : list
+        Paths to model files
+    model_dataset : string
+        Name of model dataset
+    config : dict
+        ESMValTool configuration object
+    ancestors : list
+        Filenames of input files for provenance
 
     Returns
     -------
     metrics: dict
         a dictionary of metrics names and values
     """
-    supermean_data_dir = os.path.join(run['data_root'], run['runid'],
-                                      run['_area'] + '_supermeans')
-
-    seasons = ['djf', 'mam', 'jja', 'son']
+    # Work through each season
+    metrics = {}
+    for index, season in enumerate(SEASONS):
 
-    # Constant: density of water
-    rhow = 1000.
+        constr_season = iris.Constraint(season_number=index)
+        ecv_clim = iris.load_cube(clim_file, constr_season)
 
-    # Work through each season
-    metrics = dict()
-    for season in seasons:
-        fname = 'ecv_soil_moisture_{}.nc'.format(season)
-        clim_file = os.path.join(run['climfiles_root'], fname)
-        ecv_clim = iris.load_cube(clim_file)
-        # correct invalid units
-        if (ecv_clim.units == 'unknown' and
-                'invalid_units' in ecv_clim.attributes):
-            if ecv_clim.attributes['invalid_units'] == 'm^3m^-3':
-                ecv_clim.units = 'm3 m-3'
-
-        # m01s08i223
-        # CMOR name: mrsos (soil moisture in top model layer kg/m2)
-        mrsos = get_supermean('mass_content_of_water_in_soil_layer',
-                              season,
-                              supermean_data_dir)
-
-        # Set soil moisture to missing data on ice points (i.e. no soil)
-        np.ma.masked_where(mrsos.data == 0, mrsos.data, copy=False)
-
-        # first soil layer depth
-        dz1 = mrsos.coord('depth').bounds[0, 1] - \
-            mrsos.coord('depth').bounds[0, 0]
-
-        # Calculate the volumetric soil moisture in m3/m3
-        # volumetric soil moisture = volume of water / volume of soil layer
-        # = depth equivalent of water / thickness of soil layer
-        # = (soil moisture content (kg m-2) / water density (kg m-3) )  /
-        #      soil layer thickness (m)
-        # = mosrs / (rhow * dz1)
-        vol_sm1_run = mrsos / (rhow * dz1)
-        vol_sm1_run.units = "m3 m-3"
-        vol_sm1_run.long_name = "Top layer Soil Moisture"
+        vol_sm1_run = volumetric_soil_moisture(model_file, constr_season)
 
         # update the coordinate system ECV data with a WGS84 coord system
         # unify coord systems for regridder
@@ -117,23 +199,72 @@ def land_sm_top(run):
         dff = vol_sm1_run - ecv_clim
 
         # save output and populate metric
-        iris.save(dff, os.path.join(run['dump_output'],
-                                    'soilmoist_diff_{}.nc'.format(season)))
-        name = 'soilmoisture MedAbsErr {}'.format(season)
-        dffs = dff.data
-        dffs = np.ma.abs(dffs)
-        metrics[name] = float(np.ma.median(dffs))
-
-    # record provenance
-    plot_file = "Autoassess soilmoisture metrics"
-    caption = 'Autoassess soilmoisture MedAbsErr for {}'.format(str(seasons))
-    provenance_record = get_provenance_record(caption, run)
-    cfg = {}
-    cfg['run_dir'] = run['out_dir']
-    # avoid rewriting provenance when running the plot diag
-    if not os.path.isfile(os.path.join(cfg['run_dir'],
-                                       'diagnostic_provenance.yml')):
-        with ProvenanceLogger(cfg) as provenance_logger:
-            provenance_logger.log(plot_file, provenance_record)
+        caption = f"{model_dataset} minus CCI soil moisture clim for {season}"
+        provenance_record = get_provenance_record(caption, ancestors)
+        save_data(f"soilmoist_diff_{model_dataset}_{season}",
+                  provenance_record, config, dff)
+
+        name = f"soilmoisture MedAbsErr {season}"
+        metrics[name] = float(np.ma.median(np.ma.abs(dff.data)))
 
     return metrics
+
+
+def record_provenance(diagnostic_file, config, ancestors):
+    """Record provenance."""
+    caption = f"Autoassess soilmoisture MedAbsErr for {SEASONS}"
+    provenance_record = get_provenance_record(caption, ancestors)
+    with ProvenanceLogger(config) as provenance_logger:
+        provenance_logger.log(diagnostic_file, provenance_record)
+
+
+def main(config):
+    """
+    Top-level function for soil moisture metrics.
+
+    Parameters
+    ----------
+    config : dict
+        The ESMValTool configuration.
+    """
+    input_data = config["input_data"]
+
+    # Separate OBS from model datasets
+    # (and check there is only one obs dataset)
+    obs = [v for v in input_data.values() if v["project"] == "OBS"]
+    if len(obs) != 1:
+        msg = f"Expected exactly 1 OBS dataset: found {len(obs)}"
+        raise RuntimeError(msg)
+    clim_file = obs[0]["filename"]
+
+    models = group_metadata(
+        [v for v in input_data.values() if v["project"] != "OBS"],
+        "dataset")
+
+    for model_dataset, group in models.items():
+        # 'model_dataset' is the name of the model dataset.
+        # 'group' is a list of dictionaries containing metadata.
+        logger.info("Processing data for %s", model_dataset)
+        model_file = [item["filename"] for item in group]
+
+        # Input filenames for provenance
+        ancestors = flatten([model_file, clim_file])
+
+        # Calculate metrics
+        metrics = land_sm_top(clim_file, model_file, model_dataset, config,
+                              ancestors)
+
+        # Write metrics
+        metrics_dir = os.path.join(
+            config["plot_dir"],
+            f"{config['exp_model']}_vs_{config['control_model']}",
+            config["area"],
+            model_dataset,
+        )
+
+        write_metrics(metrics_dir, metrics, config, ancestors)
+
+
+if __name__ == "__main__":
+    with run_diagnostic() as CONFIG:
+        main(CONFIG)
diff --git a/esmvaltool/diag_scripts/autoassess/plot_autoassess_metrics.py b/esmvaltool/diag_scripts/autoassess/plot_autoassess_metrics.py
index ccf3051d64..201ae0c248 100644
--- a/esmvaltool/diag_scripts/autoassess/plot_autoassess_metrics.py
+++ b/esmvaltool/diag_scripts/autoassess/plot_autoassess_metrics.py
@@ -43,10 +43,12 @@ def main():
         cfg['diag_name'], vsloc, cfg['area'], control_model, 'metrics.csv')
 
     plot_title = ' '.join([cfg['area'], control_model, 'vs', exp_model])
-    # Read metrics files
+    # Read (and record) metrics files
     # metrics = read_order_metrics(args.file_ord)
     ref = read_model_metrics(file_ref)
     tests = [read_model_metrics(file_exp)]
+    cfg['input_data'] = {'ref': {'filename': file_ref},
+                         'exp': {'filename': file_exp}}
     # var = read_model_metrics(args.file_var)
     obs, acc = None, None
     if 'additional_metrics' in cfg:
@@ -68,7 +70,8 @@ def main():
         acc=acc,
         extend_y=False,
         title=plot_title,
-        ofile=os.path.join(cfg['plot_dir'], cfg['plot_name'] + '.png'))
+        ofile=cfg['plot_name'],
+        config=cfg)
 
 
 if __name__ == '__main__':
diff --git a/esmvaltool/recipes/recipe_autoassess_landsurface_soilmoisture.yml b/esmvaltool/recipes/recipe_autoassess_landsurface_soilmoisture.yml
index a5491cc0b9..061a6a6dfa 100644
--- a/esmvaltool/recipes/recipe_autoassess_landsurface_soilmoisture.yml
+++ b/esmvaltool/recipes/recipe_autoassess_landsurface_soilmoisture.yml
@@ -4,9 +4,6 @@
 documentation:
   description: |
     Recipe that runs the Autoassess Land-surface assessment area diagnostic.
-    Climatological files are stored externally to avoid overloading the
-    ESMValTool source. See /gws/nopw/j04/esmeval/autoassess_specific_files
-    (on JASMIN).
 
   authors:
     - predoi_valeriu
@@ -27,10 +24,11 @@ datasets:
     - {dataset: E3SM-1-0,  project: CMIP6, exp: historical,  grid: gr,  ensemble: r1i1p1f1,  start_year: 1992,  end_year: 2002}
 
 preprocessors:
-  pp_aa_area:
-    regrid:  # NOT USED
-      target_grid: 0.15x0.15
-      scheme: linear
+  seasonal:
+    climate_statistics:
+      operator: mean
+      period: seasonal
+      seasons: ['DJF', 'MAM', 'JJA', 'SON']
 
 diagnostics:
   aa_landsurf_soilmoisture:
@@ -38,17 +36,20 @@ diagnostics:
     variables:
       mrsos: # moisture_content_of_soil_layer
         mip: Lmon
+        preprocessor: seasonal
+      sm: # Volumetric Moisture in Upper Portion of Soil Column
+        mip: Lmon
+        project: CMIP5
+        derive: true
+        preprocessor: seasonal
+        additional_datasets:
+            - {dataset: ESACCI-SOILMOISTURE, project: OBS, type: sat, version: L3S-SSMV-COMBINED-v4.2, tier: 2, start_year: 1999, end_year: 2008}
     scripts:
       autoassess_landsurf_soilmoisture: &autoassess_landsurf_soilmoisture_settings
-        script: autoassess/autoassess_area_base.py
-        title: "Autoassess Land-Surface Soilmoisture Diagnostic"
+        script: autoassess/land_surface_soilmoisture/soilmoisture.py
         area: land_surface_soilmoisture
         control_model: ACCESS-CM2
         exp_model: E3SM-1-0
-        obs_models: []
-        start: 1993/12/01
-        end: 2002/12/01
-        climfiles_root: '/gws/nopw/j04/esmeval/autoassess_specific_files/files'  # on JASMIN
 
   plot_standard:
     description: Wrapper to collect and plot previously calculated metrics

From 909ea47e1db2d5aaa73cbf198e659dbbdc62bc66 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?R=C3=A9mi=20Kazeroni?= <remi.kazeroni@dlr.de>
Date: Tue, 20 Jun 2023 16:19:56 +0200
Subject: [PATCH 02/93] Add ESMValCore release `v2.8.1` into the documentation
 (#3235)

---
 .../community/release_strategy/release_strategy.rst       | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/doc/sphinx/source/community/release_strategy/release_strategy.rst b/doc/sphinx/source/community/release_strategy/release_strategy.rst
index d4662f38b3..9843e52363 100644
--- a/doc/sphinx/source/community/release_strategy/release_strategy.rst
+++ b/doc/sphinx/source/community/release_strategy/release_strategy.rst
@@ -81,6 +81,14 @@ Upcoming releases
 Past releases
 ^^^^^^^^^^^^^
 
+- 2.8.1 (Bugfix, Release Manager: `Valeriu Predoi`_)
+
++------------+---------------------------------------------------------------------------------------------+------------------------------------+
+|    Done    |                                            Event                                            |             Changelog              |
++============+=============================================================================================+====================================+
+| 2023-06-02 | `ESMValCore Release 2.8.1 <https://github.com/ESMValGroup/ESMValCore/releases/tag/v2.8.1>`_ | :ref:`esmvalcore:changelog-v2-8-1` |
++------------+---------------------------------------------------------------------------------------------+------------------------------------+
+
 - 2.8.0 (Release Manager: `Rémi Kazeroni`_)
 
 +------------+------------+---------------------------------------------------------------------------------------------+------------------------------------+

From 2dbc2cfccb56e5d84e807ef630cf4843668a7120 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?R=C3=A9mi=20Kazeroni?= <remi.kazeroni@dlr.de>
Date: Tue, 20 Jun 2023 17:32:31 +0200
Subject: [PATCH 03/93] Modified links to the tutorial (#3236)

---
 README.md                                      | 4 ++--
 doc/sphinx/source/develop/recipe.rst           | 4 ++--
 doc/sphinx/source/quickstart/configuration.rst | 4 ++--
 doc/sphinx/source/quickstart/installation.rst  | 8 ++++----
 doc/sphinx/source/quickstart/running.rst       | 4 ++--
 5 files changed, 12 insertions(+), 12 deletions(-)

diff --git a/README.md b/README.md
index d8b11698dd..13b0219965 100644
--- a/README.md
+++ b/README.md
@@ -15,7 +15,7 @@
 
 - [**Documentation**](https://docs.esmvaltool.org/en/latest/)
 - [**ESMValTool Website**](https://www.esmvaltool.org/)
-- [**ESMValTool Tutorial**](https://esmvalgroup.github.io/ESMValTool_Tutorial/index.html)
+- [**ESMValTool Tutorial**](https://tutorial.esmvaltool.org/index.html)
 - [**ESMValGroup Project on GitHub**](https://github.com/ESMValGroup)
 - [**Gallery**](https://docs.esmvaltool.org/en/latest/gallery.html)
 - [**`conda-forge` package feedstock**](https://github.com/conda-forge/esmvaltool-suite-feedstock)
@@ -53,7 +53,7 @@ ESMValTool can run with the following types of [data as input](https://docs.esmv
 
 # Getting started
 
-Please see [getting started](https://docs.esmvaltool.org/en/latest/quickstart/index.html) on readthedocs as well as [ESMValTool tutorial](https://esmvalgroup.github.io/ESMValTool_Tutorial/index.html). The tutorial is a set of lessons that together teach skills needed to work with ESMValTool in climate-related domains.
+Please see [getting started](https://docs.esmvaltool.org/en/latest/quickstart/index.html) on readthedocs as well as [ESMValTool tutorial](https://tutorial.esmvaltool.org/index.html). The tutorial is a set of lessons that together teach skills needed to work with ESMValTool in climate-related domains.
 
 ## Getting help
 
diff --git a/doc/sphinx/source/develop/recipe.rst b/doc/sphinx/source/develop/recipe.rst
index 4404428a6c..98f802505d 100644
--- a/doc/sphinx/source/develop/recipe.rst
+++ b/doc/sphinx/source/develop/recipe.rst
@@ -17,6 +17,6 @@ the specific parameters needed by a recipe that runs a personal diagnostic are:
 i.e. the full path to the personal diagnostic that the user needs to run.
 
 There is also a lesson available in the 
-`ESMValTool tutorial <https://esmvalgroup.github.io/ESMValTool_Tutorial/>`_
+`ESMValTool tutorial <https://tutorial.esmvaltool.org/>`_
 that describes in a step-by-step procedure how to write your own recipe. It can be found
-`here <https://esmvalgroup.github.io/ESMValTool_Tutorial/06-preprocessor/index.html>`_.
+`here <https://tutorial.esmvaltool.org/06-preprocessor/index.html>`_.
diff --git a/doc/sphinx/source/quickstart/configuration.rst b/doc/sphinx/source/quickstart/configuration.rst
index faee8dd2d8..34c29aac5c 100644
--- a/doc/sphinx/source/quickstart/configuration.rst
+++ b/doc/sphinx/source/quickstart/configuration.rst
@@ -23,6 +23,6 @@ the ``esmvaltool`` command can find the data on your system, before it can run
 a recipe.
 
 There is a lesson available in the
-`ESMValTool tutorial <https://esmvalgroup.github.io/ESMValTool_Tutorial/>`_
+`ESMValTool tutorial <https://tutorial.esmvaltool.org/>`_
 that describes how to personalize the configuration file. It can be found
-`at this site <https://esmvalgroup.github.io/ESMValTool_Tutorial/03-configuration/index.html>`_.
+`at this site <https://tutorial.esmvaltool.org/03-configuration/index.html>`_.
diff --git a/doc/sphinx/source/quickstart/installation.rst b/doc/sphinx/source/quickstart/installation.rst
index 5f91594ed3..a4f9f2a64c 100644
--- a/doc/sphinx/source/quickstart/installation.rst
+++ b/doc/sphinx/source/quickstart/installation.rst
@@ -37,10 +37,10 @@ The next sections will detail the procedure to install ESMValTool through each
 of these methods.
 
 There is also a lesson available in the
-`ESMValTool tutorial <https://esmvalgroup.github.io/ESMValTool_Tutorial/>`_
+`ESMValTool tutorial <https://tutorial.esmvaltool.org/>`_
 that describes the installation of the ESMValTool in more detail.
 It can be found
-`here <https://esmvalgroup.github.io/ESMValTool_Tutorial/02-installation/index.html>`_.
+`here <https://tutorial.esmvaltool.org/02-installation/index.html>`_.
 
 See `common installation issues`_ if you run into trouble.
 
@@ -510,11 +510,11 @@ estate, so there is no need to install ESMValTool if you are just running recipe
  - Met Office: `esmvaltool` is available on the Linux estate after login and module loading via `module load`;
    see the ESMValTool Community of Practice SharePoint site for more details.
 
-The ESMValTool Tutorial provides a `quickstart guide <https://esmvalgroup.github.io/ESMValTool_Tutorial/01-quickstart/index.html>`__
+The ESMValTool Tutorial provides a `quickstart guide <https://tutorial.esmvaltool.org/01-quickstart/index.html>`__
 that is particularly suited for new users that have an access to pre-installed version of ESMValTool.
 
 Information on how to request an account at CEDA-JASMIN and DKRZ-Levante and to get started with these HPC clusters
-can be found on the setup page of the tutorial `here <https://esmvalgroup.github.io/ESMValTool_Tutorial/setup.html>`__.
+can be found on the setup page of the tutorial `here <https://tutorial.esmvaltool.org/setup.html>`__.
 
 .. _install_with_docker:
 
diff --git a/doc/sphinx/source/quickstart/running.rst b/doc/sphinx/source/quickstart/running.rst
index 8df3f99635..7f9cadbaa1 100644
--- a/doc/sphinx/source/quickstart/running.rst
+++ b/doc/sphinx/source/quickstart/running.rst
@@ -14,9 +14,9 @@ Running your first recipe
 =========================
 
 There is a step-by-step tutorial available in the
-`ESMValTool tutorial <https://esmvalgroup.github.io/ESMValTool_Tutorial/>`_
+`ESMValTool tutorial <https://tutorial.esmvaltool.org/>`_
 on how to run your first recipe. It can be found
-`here <https://esmvalgroup.github.io/ESMValTool_Tutorial/04-recipe/index.html>`_.
+`here <https://tutorial.esmvaltool.org/04-recipe/index.html>`_.
 
 An
 `example recipe <https://github.com/ESMValGroup/ESMValTool/blob/main/esmvaltool/recipes/examples/recipe_python.yml>`_

From d7b3c1f94e5f34b9cb5a5d22ede530cf66babb02 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Wed, 21 Jun 2023 12:45:45 +0100
Subject: [PATCH 04/93] [Condalock] Update Linux condalock file (#3237)

Co-authored-by: valeriupredoi <valeriupredoi@users.noreply.github.com>
---
 conda-linux-64.lock | 160 ++++++++++++++++++++++----------------------
 1 file changed, 80 insertions(+), 80 deletions(-)

diff --git a/conda-linux-64.lock b/conda-linux-64.lock
index e8915dafdc..c41403d662 100644
--- a/conda-linux-64.lock
+++ b/conda-linux-64.lock
@@ -1,6 +1,6 @@
 # Generated by conda-lock.
 # platform: linux-64
-# input_hash: cdee46d10f8bc1b75620e0bfb5babf885dd0f4e4fc49bd6d7ac9f226a3f0c8af
+# input_hash: 7d637eea13b048450933417ec5ec069834faf2d132e6ccfa960adbe351ac0b19
 @EXPLICIT
 https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2#d7c89558ba9fa0495403155b64376d81
 https://conda.anaconda.org/conda-forge/linux-64/_py-xgboost-mutex-2.0-gpu_0.tar.bz2#7702188077361f43a4d61e64c694f850
@@ -30,13 +30,13 @@ https://conda.anaconda.org/conda-forge/linux-64/binutils_impl_linux-64-2.40-hf60
 https://conda.anaconda.org/conda-forge/noarch/fonts-conda-ecosystem-1-0.tar.bz2#fee5683a3f04bd15cbd8318b096a27ab
 https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-13.1.0-he5830b7_0.conda#cd93f779ff018dd85c7544c015c9db3c
 https://conda.anaconda.org/conda-forge/linux-64/aom-3.5.0-h27087fc_0.tar.bz2#a08150fd2298460cd1fcccf626305642
-https://conda.anaconda.org/conda-forge/linux-64/aws-c-common-0.8.19-hd590300_0.conda#81bd50906818d08c2f98d6d9f94cbd02
+https://conda.anaconda.org/conda-forge/linux-64/aws-c-common-0.8.20-hd590300_0.conda#8717fccceb6a9394d86f37f3b663b4e9
 https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-h7f98852_4.tar.bz2#a1fd65c7ccbf10880423d82bca54eb54
 https://conda.anaconda.org/conda-forge/linux-64/c-ares-1.19.1-hd590300_0.conda#e8c18d865be43e2fb3f7a145b6adf1f5
 https://conda.anaconda.org/conda-forge/linux-64/charls-2.4.2-h59595ed_0.conda#4336bd67920dd504cd8c6761d6a99645
 https://conda.anaconda.org/conda-forge/linux-64/cudatoolkit-11.1.1-ha002fc5_11.conda#2b11133c35a4899a29fc5109d8f95d2e
 https://conda.anaconda.org/conda-forge/linux-64/dav1d-1.2.1-hd590300_0.conda#418c6ca5929a611cbd69204907a83995
-https://conda.anaconda.org/conda-forge/linux-64/fftw-3.3.10-nompi_hc118613_107.conda#28b2b46b350ddb6a01d061392f75af54
+https://conda.anaconda.org/conda-forge/linux-64/fftw-3.3.10-nompi_hc118613_108.conda#6fa90698000b05dfe8ce6515794fe71a
 https://conda.anaconda.org/conda-forge/linux-64/freexl-1.0.6-h166bdaf_1.tar.bz2#897e772a157faf3330d72dd291486f62
 https://conda.anaconda.org/conda-forge/linux-64/fribidi-1.0.10-h36c2ea0_0.tar.bz2#ac7bc6a654f8f41b352b38f4051135f8
 https://conda.anaconda.org/conda-forge/linux-64/geos-3.11.2-hcb278e6_0.conda#3b8e364995e3575e57960d29c1e5ab14
@@ -73,14 +73,14 @@ https://conda.anaconda.org/conda-forge/linux-64/libunwind-1.6.2-h9c3ff4c_0.tar.b
 https://conda.anaconda.org/conda-forge/linux-64/libutf8proc-2.8.0-h166bdaf_0.tar.bz2#ede4266dc02e875fe1ea77b25dd43747
 https://conda.anaconda.org/conda-forge/linux-64/libuuid-2.38.1-h0b41bf4_0.conda#40b61aab5c7ba9ff276c41cfffe6b80b
 https://conda.anaconda.org/conda-forge/linux-64/libwebp-base-1.3.0-h0b41bf4_0.conda#0d4a7508d8c6c65314f2b9c1f56ad408
-https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.2.13-h166bdaf_4.tar.bz2#f3f9de449d32ca9b9c66a22863c96f41
+https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.2.13-hd590300_5.conda#f36c115f1ee199da648e0597ec2047ad
 https://conda.anaconda.org/conda-forge/linux-64/libzopfli-1.0.3-h9c3ff4c_0.tar.bz2#c66fe2d123249af7651ebde8984c51c2
 https://conda.anaconda.org/conda-forge/linux-64/lz4-c-1.9.4-hcb278e6_0.conda#318b08df404f9c9be5712aaa5a6f0bb0
 https://conda.anaconda.org/conda-forge/linux-64/lzo-2.10-h516909a_1000.tar.bz2#bb14fcb13341b81d5eb386423b9d2bac
 https://conda.anaconda.org/conda-forge/linux-64/make-4.3-hd18ef5c_1.tar.bz2#4049ebfd3190b580dffe76daed26155a
 https://conda.anaconda.org/conda-forge/linux-64/mbedtls-3.3.0-hcb278e6_0.conda#cc1213f464c357b647cc5dde5cfca881
 https://conda.anaconda.org/conda-forge/linux-64/metis-5.1.0-h58526e2_1006.tar.bz2#d099b812378b1e133c12e3b75167d83a
-https://conda.anaconda.org/conda-forge/linux-64/nccl-2.18.1.1-h12f7317_0.conda#27a927b408c246762a9d891a3e6e1c2c
+https://conda.anaconda.org/conda-forge/linux-64/nccl-2.18.3.1-h12f7317_0.conda#c0041b39fc72c1d12139b45363c8a510
 https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.4-hcb278e6_0.conda#681105bccc2a3f7f1a837d47d39c9179
 https://conda.anaconda.org/conda-forge/linux-64/nspr-4.35-h27087fc_0.conda#da0ec11a6454ae19bff5b02ed881a2b1
 https://conda.anaconda.org/conda-forge/linux-64/openlibm-0.8.1-h7f98852_0.tar.bz2#ba0c56761f2380babaa783b2a37b4d08
@@ -108,10 +108,10 @@ https://conda.anaconda.org/conda-forge/linux-64/xz-5.2.6-h166bdaf_0.tar.bz2#2161
 https://conda.anaconda.org/conda-forge/linux-64/yaml-0.2.5-h7f98852_2.tar.bz2#4cb3ad778ec2d5a7acbdf254eb1c42ae
 https://conda.anaconda.org/conda-forge/linux-64/zfp-1.0.0-h27087fc_3.tar.bz2#0428af0510c3fafedf1c66b43102a34b
 https://conda.anaconda.org/conda-forge/linux-64/zlib-ng-2.0.7-h0b41bf4_0.conda#49e8329110001f04923fe7e864990b0c
-https://conda.anaconda.org/conda-forge/linux-64/aws-c-cal-0.5.26-hf677bf3_1.conda#7d00f2b22493e28400fdbea8dc110790
-https://conda.anaconda.org/conda-forge/linux-64/aws-c-compression-0.2.16-hbad4bc6_7.conda#d58359b64c6d1256c07eeaee753159e3
-https://conda.anaconda.org/conda-forge/linux-64/aws-c-sdkutils-0.1.9-hbad4bc6_2.conda#eee3831810e132b6caf45f03c3428363
-https://conda.anaconda.org/conda-forge/linux-64/aws-checksums-0.1.14-hbad4bc6_7.conda#916c2a86bf786aab811a60990f7538ed
+https://conda.anaconda.org/conda-forge/linux-64/aws-c-cal-0.5.27-hf85dbcb_0.conda#d067fbf673901a6e0fd323da1eeafe10
+https://conda.anaconda.org/conda-forge/linux-64/aws-c-compression-0.2.17-h4b87b72_0.conda#183be3df566bc1c143d5d7e0fc60ed8b
+https://conda.anaconda.org/conda-forge/linux-64/aws-c-sdkutils-0.1.10-h4b87b72_0.conda#613b0910286d4feba563ad657ac93372
+https://conda.anaconda.org/conda-forge/linux-64/aws-checksums-0.1.16-h4b87b72_0.conda#c2a56432ce6009419442dd78e4d63829
 https://conda.anaconda.org/conda-forge/linux-64/expat-2.5.0-hcb278e6_1.conda#8b9b5aca60558d02ddaa09d599e55920
 https://conda.anaconda.org/conda-forge/linux-64/gcc_impl_linux-64-13.1.0-hc4be1a9_0.conda#99d1a8a8ee1665ee9435f8d160df69fe
 https://conda.anaconda.org/conda-forge/linux-64/glog-0.6.0-h6f12383_0.tar.bz2#b31f3565cb84435407594e548a2fb7b2
@@ -131,23 +131,22 @@ https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.42.0-h2797004_0.cond
 https://conda.anaconda.org/conda-forge/linux-64/libssh2-1.11.0-h0841786_0.conda#1f5a58e686b13bcfde88b93f547d23fe
 https://conda.anaconda.org/conda-forge/linux-64/libxcb-1.15-h0b41bf4_0.conda#33277193f5b92bad9fdd230eb700929c
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-https://conda.anaconda.org/conda-forge/linux-64/libxml2-2.10.4-hfdac1af_0.conda#241845899caff54ac1d2b3102ad988cf
+https://conda.anaconda.org/conda-forge/linux-64/libxml2-2.11.4-h0d562d8_0.conda#e46fad17d5fb57316b956f88dca765e4
 https://conda.anaconda.org/conda-forge/linux-64/libzip-1.9.2-hc929e4a_1.tar.bz2#5b122b50e738c4be5c3f2899f010d7cf
 https://conda.anaconda.org/conda-forge/linux-64/mpfr-4.2.0-hb012696_0.conda#14d87bdff2cbd3b1179a29fb316ed743
 https://conda.anaconda.org/conda-forge/linux-64/openblas-ilp64-0.3.23-pthreads_h3d04fff_0.conda#9787e8492f0a51a6b0498dc86f3864f9
-https://conda.anaconda.org/conda-forge/linux-64/pandoc-2.19.2-h32600fe_2.conda#326f46f36d15c44cff5f81d505cb717f
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-https://conda.anaconda.org/conda-forge/linux-64/s2n-1.3.44-h06160fa_0.conda#968cb0fca1249fe9778876201dd2b828
+https://conda.anaconda.org/conda-forge/linux-64/s2n-1.3.45-h06160fa_0.conda#5b78d77397d75049c433eb7b17a9bca8
 https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.12-h27826a3_0.tar.bz2#5b8c42eb62e9fc961af70bdd6a26e168
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+https://conda.anaconda.org/conda-forge/linux-64/zlib-1.2.13-hd590300_5.conda#68c34ec6149623be41a1933ab996a209
 https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.2-h3eb15da_6.conda#6b63daed8feeca47be78f323e793d555
-https://conda.anaconda.org/conda-forge/linux-64/aws-c-io-0.13.21-h9fef7b8_5.conda#0e64949e8f740ceeb9f1d6255f314ab2
+https://conda.anaconda.org/conda-forge/linux-64/aws-c-io-0.13.26-h0d05201_0.conda#2b8feff4f71c70e9ca0f7ac66b464e8a
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@@ -598,12 +598,12 @@ https://conda.anaconda.org/conda-forge/noarch/r-rprojroot-2.0.3-r41hc72bb7e_1.ta
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@@ -621,13 +621,13 @@ https://conda.anaconda.org/conda-forge/linux-64/r-openssl-2.0.6-r41habfbb5e_0.co
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+https://conda.anaconda.org/conda-forge/linux-64/r-specsverification-0.5_3-r41ha503ecb_3.conda#2bc51f0d44b98092ba57cf2f8671b490
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-https://conda.anaconda.org/conda-forge/noarch/nbconvert-7.4.0-pyhd8ed1ab_0.conda#a86727968b41c20dd3d73b91632e77dc
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@@ -637,7 +637,7 @@ https://conda.anaconda.org/conda-forge/noarch/r-pillar-1.9.0-r41hc72bb7e_0.conda
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+https://conda.anaconda.org/conda-forge/label/esmvalcore_rc/noarch/esmvalcore-2.9.0rc1-pyh39db41b_0.conda#dcbff06e21971c0cdce69b77219b45f6
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From da7f3dbe64ced5425dba05d4fe5ed20180cbaebe Mon Sep 17 00:00:00 2001
From: Valeriu Predoi <valeriu.predoi@gmail.com>
Date: Tue, 27 Jun 2023 12:53:05 +0100
Subject: [PATCH 05/93] Remove jquery sphinx extension from docs config since
 new theme doesn't use it (#3251)

---
 doc/sphinx/source/conf.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/doc/sphinx/source/conf.py b/doc/sphinx/source/conf.py
index 4606f1e359..6257289715 100644
--- a/doc/sphinx/source/conf.py
+++ b/doc/sphinx/source/conf.py
@@ -71,8 +71,6 @@
     'sphinx.ext.viewcode',
     'sphinx.ext.napoleon',
     'autodocsumm',
-    # github.com/readthedocs/sphinx_rtd_theme/issues/1451
-    'sphinxcontrib.jquery',
 ]
 
 autodoc_default_options = {

From abaedeb9c6271477a91a7bd9d9270084dcaf0c03 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?R=C3=A9mi=20Kazeroni?= <remi.kazeroni@dlr.de>
Date: Wed, 28 Jun 2023 15:37:19 +0200
Subject: [PATCH 06/93] Fix gitter badge in README (#3258)

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 13b0219965..069ce0a0c6 100644
--- a/README.md
+++ b/README.md
@@ -2,7 +2,7 @@
 [![made-with-python](https://img.shields.io/badge/Made%20with-Python-1f425f.svg)](https://www.python.org/)
 [![Documentation Status](https://readthedocs.org/projects/esmvaltool/badge/?version=latest)](https://esmvaltool.readthedocs.io/en/latest/?badge=latest)
 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3401363.svg)](https://doi.org/10.5281/zenodo.3401363)
-[![Gitter](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/ESMValGroup?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
+[![Chat on Matrix](https://matrix.to/img/matrix-badge.svg)](https://matrix.to/#/#ESMValGroup_Lobby:gitter.im)
 [![CircleCI](https://circleci.com/gh/ESMValGroup/ESMValTool/tree/main.svg?style=svg)](https://circleci.com/gh/ESMValGroup/ESMValTool/tree/main)
 [![Test in Full Development Mode](https://github.com/ESMValGroup/ESMValTool/actions/workflows/test-development.yml/badge.svg)](https://github.com/ESMValGroup/ESMValTool/actions/workflows/test-development.yml)
 [![Codacy Badge](https://app.codacy.com/project/badge/Coverage/79bf6932c2e844eea15d0fb1ed7e415c)](https://www.codacy.com/gh/ESMValGroup/ESMValTool?utm_source=github.com&utm_medium=referral&utm_content=ESMValGroup/ESMValTool&utm_campaign=Badge_Coverage)

From 776135a83ba8d52c495f26deaa057b40e06fc5fd Mon Sep 17 00:00:00 2001
From: Valeriu Predoi <valeriu.predoi@gmail.com>
Date: Mon, 3 Jul 2023 09:34:02 +0200
Subject: [PATCH 07/93] Realize data for scalar cube in
 `recipe_carvalhais14nat` to avert issue from dask latest (2023.6.0) (#3265)

---
 .../diag_scripts/land_carbon_cycle/diag_global_turnover.py | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

diff --git a/esmvaltool/diag_scripts/land_carbon_cycle/diag_global_turnover.py b/esmvaltool/diag_scripts/land_carbon_cycle/diag_global_turnover.py
index 0d8b95ff84..d703c87a24 100644
--- a/esmvaltool/diag_scripts/land_carbon_cycle/diag_global_turnover.py
+++ b/esmvaltool/diag_scripts/land_carbon_cycle/diag_global_turnover.py
@@ -737,7 +737,12 @@ def main(diag_config):
         tau_global = ctotal_global / gpp_global
         tau_global.convert_units('yr')
 
-        global_tau_mod['global'][model_name] = float(tau_global.core_data())
+        # since dask=2023.3 there is an issue with converting the core_data()
+        # to float; I have not managed to pinpoint the issue neither in dask
+        # nor in iris, since minimal test cases are not reproducing it
+        # this is a scalar cube so no big mem issue by realizing the data
+        # global_tau_mod['global'][model_name] = float(tau_global.core_data())
+        global_tau_mod['global'][model_name] = float(tau_global.data)
 
         base_name_mod = (
             'global_{title}_{source_label}_'

From e1a06dd3e1d0c92789eb95ec517984708f8b6a58 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?R=C3=A9mi=20Kazeroni?= <remi.kazeroni@dlr.de>
Date: Tue, 4 Jul 2023 10:34:05 +0200
Subject: [PATCH 08/93] Fix failing `mlr` diagnostic test by adding new
 scikit-learn default tag (#3273)

Co-authored-by: Bouwe Andela <b.andela@esciencecenter.nl>
Co-authored-by: Valeriu Predoi <valeriu.predoi@gmail.com>
---
 esmvaltool/diag_scripts/mlr/custom_sklearn.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/esmvaltool/diag_scripts/mlr/custom_sklearn.py b/esmvaltool/diag_scripts/mlr/custom_sklearn.py
index 2e403163cb..198cbdc376 100644
--- a/esmvaltool/diag_scripts/mlr/custom_sklearn.py
+++ b/esmvaltool/diag_scripts/mlr/custom_sklearn.py
@@ -86,6 +86,7 @@
 
 
 _DEFAULT_TAGS = {
+    'array_api_support': False,
     'non_deterministic': False,
     'requires_positive_X': False,
     'requires_positive_y': False,

From 28ad6b4a0d200187ec861b2f07a1f6c7a6fd6cb3 Mon Sep 17 00:00:00 2001
From: Bouwe Andela <b.andela@esciencecenter.nl>
Date: Tue, 4 Jul 2023 12:30:21 +0200
Subject: [PATCH 09/93] Relax the pin on iris to allow the use of older
 versions for performance reasons (#3270)

---
 setup.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/setup.py b/setup.py
index 497815cf7e..940cc5224f 100755
--- a/setup.py
+++ b/setup.py
@@ -60,7 +60,9 @@
         'scikit-image',
         'scikit-learn',
         'scipy',
-        'scitools-iris>=3.6.0',
+        # See the following issue for info on the iris pin below:
+        # https://github.com/ESMValGroup/ESMValTool/issues/3239#issuecomment-1613298587
+        'scitools-iris>=3.4.0',
         'seaborn',
         'seawater',
         'shapely',

From 6454112f447e0ea27cfbbdf94f3e655029f7d37a Mon Sep 17 00:00:00 2001
From: Valeriu Predoi <valeriu.predoi@gmail.com>
Date: Tue, 27 Jun 2023 12:53:05 +0100
Subject: [PATCH 10/93] Remove jquery sphinx extension from docs config since
 new theme doesn't use it (#3251)

---
 doc/sphinx/source/conf.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/doc/sphinx/source/conf.py b/doc/sphinx/source/conf.py
index 4606f1e359..6257289715 100644
--- a/doc/sphinx/source/conf.py
+++ b/doc/sphinx/source/conf.py
@@ -71,8 +71,6 @@
     'sphinx.ext.viewcode',
     'sphinx.ext.napoleon',
     'autodocsumm',
-    # github.com/readthedocs/sphinx_rtd_theme/issues/1451
-    'sphinxcontrib.jquery',
 ]
 
 autodoc_default_options = {

From 72c089d21377b0fb291640b3c4df8d4c906e97c2 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?R=C3=A9mi=20Kazeroni?= <remi.kazeroni@dlr.de>
Date: Wed, 28 Jun 2023 15:37:19 +0200
Subject: [PATCH 11/93] Fix gitter badge in README (#3258)

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 13b0219965..069ce0a0c6 100644
--- a/README.md
+++ b/README.md
@@ -2,7 +2,7 @@
 [![made-with-python](https://img.shields.io/badge/Made%20with-Python-1f425f.svg)](https://www.python.org/)
 [![Documentation Status](https://readthedocs.org/projects/esmvaltool/badge/?version=latest)](https://esmvaltool.readthedocs.io/en/latest/?badge=latest)
 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3401363.svg)](https://doi.org/10.5281/zenodo.3401363)
-[![Gitter](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/ESMValGroup?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
+[![Chat on Matrix](https://matrix.to/img/matrix-badge.svg)](https://matrix.to/#/#ESMValGroup_Lobby:gitter.im)
 [![CircleCI](https://circleci.com/gh/ESMValGroup/ESMValTool/tree/main.svg?style=svg)](https://circleci.com/gh/ESMValGroup/ESMValTool/tree/main)
 [![Test in Full Development Mode](https://github.com/ESMValGroup/ESMValTool/actions/workflows/test-development.yml/badge.svg)](https://github.com/ESMValGroup/ESMValTool/actions/workflows/test-development.yml)
 [![Codacy Badge](https://app.codacy.com/project/badge/Coverage/79bf6932c2e844eea15d0fb1ed7e415c)](https://www.codacy.com/gh/ESMValGroup/ESMValTool?utm_source=github.com&utm_medium=referral&utm_content=ESMValGroup/ESMValTool&utm_campaign=Badge_Coverage)

From 8778cb4d28790c61276215d49b8fb8d235a81643 Mon Sep 17 00:00:00 2001
From: Valeriu Predoi <valeriu.predoi@gmail.com>
Date: Mon, 3 Jul 2023 09:34:02 +0200
Subject: [PATCH 12/93] Realize data for scalar cube in
 `recipe_carvalhais14nat` to avert issue from dask latest (2023.6.0) (#3265)

---
 .../diag_scripts/land_carbon_cycle/diag_global_turnover.py | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

diff --git a/esmvaltool/diag_scripts/land_carbon_cycle/diag_global_turnover.py b/esmvaltool/diag_scripts/land_carbon_cycle/diag_global_turnover.py
index 0d8b95ff84..d703c87a24 100644
--- a/esmvaltool/diag_scripts/land_carbon_cycle/diag_global_turnover.py
+++ b/esmvaltool/diag_scripts/land_carbon_cycle/diag_global_turnover.py
@@ -737,7 +737,12 @@ def main(diag_config):
         tau_global = ctotal_global / gpp_global
         tau_global.convert_units('yr')
 
-        global_tau_mod['global'][model_name] = float(tau_global.core_data())
+        # since dask=2023.3 there is an issue with converting the core_data()
+        # to float; I have not managed to pinpoint the issue neither in dask
+        # nor in iris, since minimal test cases are not reproducing it
+        # this is a scalar cube so no big mem issue by realizing the data
+        # global_tau_mod['global'][model_name] = float(tau_global.core_data())
+        global_tau_mod['global'][model_name] = float(tau_global.data)
 
         base_name_mod = (
             'global_{title}_{source_label}_'

From fb599303229ccabc18d66a552429e91c497700a4 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?R=C3=A9mi=20Kazeroni?= <remi.kazeroni@dlr.de>
Date: Tue, 4 Jul 2023 10:34:05 +0200
Subject: [PATCH 13/93] Fix failing `mlr` diagnostic test by adding new
 scikit-learn default tag (#3273)

Co-authored-by: Bouwe Andela <b.andela@esciencecenter.nl>
Co-authored-by: Valeriu Predoi <valeriu.predoi@gmail.com>
---
 esmvaltool/diag_scripts/mlr/custom_sklearn.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/esmvaltool/diag_scripts/mlr/custom_sklearn.py b/esmvaltool/diag_scripts/mlr/custom_sklearn.py
index 2e403163cb..198cbdc376 100644
--- a/esmvaltool/diag_scripts/mlr/custom_sklearn.py
+++ b/esmvaltool/diag_scripts/mlr/custom_sklearn.py
@@ -86,6 +86,7 @@
 
 
 _DEFAULT_TAGS = {
+    'array_api_support': False,
     'non_deterministic': False,
     'requires_positive_X': False,
     'requires_positive_y': False,

From 4fc4a3500460d15d4c0dbbd23a6fc501d0d3171f Mon Sep 17 00:00:00 2001
From: Bouwe Andela <b.andela@esciencecenter.nl>
Date: Tue, 4 Jul 2023 12:30:21 +0200
Subject: [PATCH 14/93] Relax the pin on iris to allow the use of older
 versions for performance reasons (#3270)

---
 setup.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/setup.py b/setup.py
index 497815cf7e..940cc5224f 100755
--- a/setup.py
+++ b/setup.py
@@ -60,7 +60,9 @@
         'scikit-image',
         'scikit-learn',
         'scipy',
-        'scitools-iris>=3.6.0',
+        # See the following issue for info on the iris pin below:
+        # https://github.com/ESMValGroup/ESMValTool/issues/3239#issuecomment-1613298587
+        'scitools-iris>=3.4.0',
         'seaborn',
         'seawater',
         'shapely',

From c694d4c8e33c4f4af812df0b18186b44003d243a Mon Sep 17 00:00:00 2001
From: Bouwe Andela <b.andela@esciencecenter.nl>
Date: Tue, 4 Jul 2023 14:32:49 +0200
Subject: [PATCH 15/93] Use ESMValCore v2.9.0 (#3274)

---
 environment.yml     | 2 +-
 environment_osx.yml | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/environment.yml b/environment.yml
index 7f060c5437..33a556b7d9 100644
--- a/environment.yml
+++ b/environment.yml
@@ -4,7 +4,7 @@ channels:
   # The release candidate channel should only be activated
   # during the rc phase right before the next release of the
   # ESMValCore.
-  - conda-forge/label/esmvalcore_rc
+  # - conda-forge/label/esmvalcore_rc
   - conda-forge
   - nodefaults
 
diff --git a/environment_osx.yml b/environment_osx.yml
index 64d3a142b9..fac9409617 100644
--- a/environment_osx.yml
+++ b/environment_osx.yml
@@ -4,7 +4,7 @@ channels:
   # The release candidate channel should only be activated
   # during the rc phase right before the next release of the
   # ESMValCore.
-  - conda-forge/label/esmvalcore_rc
+  # - conda-forge/label/esmvalcore_rc
   - conda-forge
   - nodefaults
 

From bd374852a623616aa97fe0f1b55c31c7da0d4343 Mon Sep 17 00:00:00 2001
From: Bouwe Andela <b.andela@esciencecenter.nl>
Date: Tue, 4 Jul 2023 14:32:49 +0200
Subject: [PATCH 16/93] Use ESMValCore v2.9.0 (#3274)

---
 environment.yml     | 2 +-
 environment_osx.yml | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/environment.yml b/environment.yml
index 7f060c5437..33a556b7d9 100644
--- a/environment.yml
+++ b/environment.yml
@@ -4,7 +4,7 @@ channels:
   # The release candidate channel should only be activated
   # during the rc phase right before the next release of the
   # ESMValCore.
-  - conda-forge/label/esmvalcore_rc
+  # - conda-forge/label/esmvalcore_rc
   - conda-forge
   - nodefaults
 
diff --git a/environment_osx.yml b/environment_osx.yml
index 64d3a142b9..fac9409617 100644
--- a/environment_osx.yml
+++ b/environment_osx.yml
@@ -4,7 +4,7 @@ channels:
   # The release candidate channel should only be activated
   # during the rc phase right before the next release of the
   # ESMValCore.
-  - conda-forge/label/esmvalcore_rc
+  # - conda-forge/label/esmvalcore_rc
   - conda-forge
   - nodefaults
 

From dfc78841b0a0a87bde4b782645f6d1759fe54d1d Mon Sep 17 00:00:00 2001
From: Lisa Bock <lisa.bock@dlr.de>
Date: Thu, 6 Jul 2023 10:39:24 +0200
Subject: [PATCH 17/93] Fix ordering of models in perfmetrics (#3275)

---
 esmvaltool/diag_scripts/perfmetrics/collect.ncl | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/esmvaltool/diag_scripts/perfmetrics/collect.ncl b/esmvaltool/diag_scripts/perfmetrics/collect.ncl
index 0fd2efe311..503a9c50d8 100644
--- a/esmvaltool/diag_scripts/perfmetrics/collect.ncl
+++ b/esmvaltool/diag_scripts/perfmetrics/collect.ncl
@@ -351,9 +351,9 @@ begin
       end if
       if (n_proj .gt. 1) then
         id2 = ind(projectnames.eq.diag_script_info@project_order(1))
-        id2_mm = (/ind(data_all&models(id2) .eq. \
+        id2_mm = (/ind(data_temp&models(id2) .eq. \
                   diag_script_info@project_order(1) + "_mean"), \
-                  ind(data_all&models(id2) .eq. \
+                  ind(data_temp&models(id2) .eq. \
                   diag_script_info@project_order(1) + "_median") /)
         if (any(ismissing(id2_mm))) then
           id2_mm = -1
@@ -368,9 +368,9 @@ begin
         end if
         if (n_proj .gt. 2) then
           id3 = ind(projectnames.eq.diag_script_info@project_order(2))
-          id3_mm = (/ind(data_all&models(id3) .eq. \
+          id3_mm = (/ind(data_temp&models(id3) .eq. \
                     diag_script_info@project_order(2) + "_mean"), \
-                    ind(data_all&models(id3) .eq. \
+                    ind(data_temp&models(id3) .eq. \
                     diag_script_info@project_order(2) + "_median") /)
           if (any(ismissing(id3_mm))) then
             id3_mm = -1

From 578421beb4663fe11f4e7bbc02e1e01d5ede39fb Mon Sep 17 00:00:00 2001
From: Lisa Bock <lisa.bock@dlr.de>
Date: Thu, 6 Jul 2023 10:39:24 +0200
Subject: [PATCH 18/93] Fix ordering of models in perfmetrics (#3275)

---
 esmvaltool/diag_scripts/perfmetrics/collect.ncl | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/esmvaltool/diag_scripts/perfmetrics/collect.ncl b/esmvaltool/diag_scripts/perfmetrics/collect.ncl
index 0fd2efe311..503a9c50d8 100644
--- a/esmvaltool/diag_scripts/perfmetrics/collect.ncl
+++ b/esmvaltool/diag_scripts/perfmetrics/collect.ncl
@@ -351,9 +351,9 @@ begin
       end if
       if (n_proj .gt. 1) then
         id2 = ind(projectnames.eq.diag_script_info@project_order(1))
-        id2_mm = (/ind(data_all&models(id2) .eq. \
+        id2_mm = (/ind(data_temp&models(id2) .eq. \
                   diag_script_info@project_order(1) + "_mean"), \
-                  ind(data_all&models(id2) .eq. \
+                  ind(data_temp&models(id2) .eq. \
                   diag_script_info@project_order(1) + "_median") /)
         if (any(ismissing(id2_mm))) then
           id2_mm = -1
@@ -368,9 +368,9 @@ begin
         end if
         if (n_proj .gt. 2) then
           id3 = ind(projectnames.eq.diag_script_info@project_order(2))
-          id3_mm = (/ind(data_all&models(id3) .eq. \
+          id3_mm = (/ind(data_temp&models(id3) .eq. \
                     diag_script_info@project_order(2) + "_mean"), \
-                    ind(data_all&models(id3) .eq. \
+                    ind(data_temp&models(id3) .eq. \
                     diag_script_info@project_order(2) + "_median") /)
           if (any(ismissing(id3_mm))) then
             id3_mm = -1

From 7e0c5a5b630bc9f37e056ca064b4b627dde96cb1 Mon Sep 17 00:00:00 2001
From: Bouwe Andela <b.andela@esciencecenter.nl>
Date: Thu, 6 Jul 2023 16:20:23 +0200
Subject: [PATCH 19/93] Add release notes for v2.9 (#3266)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Co-authored-by: Valeriu Predoi <valeriu.predoi@gmail.com>
Co-authored-by: Rémi Kazeroni <remi.kazeroni@dlr.de>
---
 CITATION.cff                    |   4 +-
 doc/sphinx/source/changelog.rst | 117 ++++++++++++++++++++++++++++++--
 2 files changed, 114 insertions(+), 7 deletions(-)

diff --git a/CITATION.cff b/CITATION.cff
index f069250a3d..31404e4c7e 100644
--- a/CITATION.cff
+++ b/CITATION.cff
@@ -351,11 +351,11 @@ authors:
     orcid: "https://orcid.org/0000-0002-2406-4936"
 
 cff-version: 1.2.0
-date-released: 2023-03-28
+date-released: 2023-07-06
 doi: "10.5281/zenodo.3401363"
 license: "Apache-2.0"
 message: "If you use this software, please cite it using these metadata."
 repository-code: "https://github.com/ESMValGroup/ESMValTool/"
 title: ESMValTool
-version: "v2.8.0"
+version: "v2.9.0"
 ...
diff --git a/doc/sphinx/source/changelog.rst b/doc/sphinx/source/changelog.rst
index e26ec7d26b..52c3aa3086 100644
--- a/doc/sphinx/source/changelog.rst
+++ b/doc/sphinx/source/changelog.rst
@@ -3,6 +3,113 @@
 Changelog
 =========
 
+.. _changelog-v2-9-0:
+
+v2.9.0
+------
+
+Highlights
+~~~~~~~~~~
+
+-  A new :ref:`diagnostic <api.esmvaltool.diag_scripts.seaborn_diag>` has been
+   added to provide a high-level interface to
+   `seaborn <https://seaborn.pydata.org/>`__,
+   a Python data visualization library based on
+   `matplotlib <https://matplotlib.org/>`__.
+   See the :ref:`recipe documentation <recipes_seaborn_diag>` for more
+   information.
+
+-  We have included a new recipe and diagnostic that represent the major
+   physical processes that describe Arctic-midlatitude teleconnections and
+   provide the basis for the CMIP6 model evaluation for the further application
+   of causal discovery.
+   The results are discussed in the article
+   `"Causal model evaluation of Arctic-midlatitude teleconnections in CMIP6" <https://essopenarchive.org/doi/full/10.1002/essoar.10512569.1>`__
+   by Galytska et al. (in review in Journal of Geophysical Research: Atmospheres).
+
+-  It is now possible to use the
+   `Dask distributed scheduler <https://docs.dask.org/en/latest/deploying.html>`__,
+   which can
+   `significantly reduce the run-time of recipes <https://github.com/ESMValGroup/ESMValCore/pull/2049#pullrequestreview-1446279391>`__.
+   Configuration examples and advice are available in the
+   :ref:`ESMValCore documentation <esmvalcore:config-dask>`.
+   If configured, the Dask distributed scheduler will also be used by diagnostic
+   scripts written in Python, so make sure to use
+   `lazy data <https://scitools-iris.readthedocs.io/en/latest/userguide/real_and_lazy_data.html#real-and-lazy-data>`__
+   wherever it is possible in your (new) diagnostics.
+   More work on improving the computational performance is planned, so please
+   share your experiences, good and bad, with this new feature in
+   `ESMValGroup/ESMValCore#1763 <https://github.com/ESMValGroup/ESMValCore/discussions/1763>`__.
+
+This release includes
+
+Bug fixes
+~~~~~~~~~
+
+-  Fixed usage of ``work_dir`` in some CMORizer scripts (`#3192 <https://github.com/ESMValGroup/ESMValTool/pull/3192>`__) `Rémi Kazeroni <https://github.com/remi-kazeroni>`__
+-  Realize data for scalar cube in `recipe_carvalhais14nat` to avert issue from dask latest (2023.6.0) (`#3265 <https://github.com/ESMValGroup/ESMValTool/pull/3265>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+-  Fix failing ``mlr`` diagnostic test by adding new scikit-learn default tag (`#3273 <https://github.com/ESMValGroup/ESMValTool/pull/3273>`__) `Rémi Kazeroni <https://github.com/remi-kazeroni>`__
+-  Fix ordering of models in perfmetrics diagnostic script (`#3275 <https://github.com/ESMValGroup/ESMValTool/pull/3275>`__) `Lisa Bock <https://github.com/LisaBock>`__
+
+Documentation
+~~~~~~~~~~~~~
+
+-  Update release schedule after v2.8.0 (`#3138 <https://github.com/ESMValGroup/ESMValTool/pull/3138>`__) `Rémi Kazeroni <https://github.com/remi-kazeroni>`__
+-  Added reference entry for Winterstein (`#3154 <https://github.com/ESMValGroup/ESMValTool/pull/3154>`__) `FranziskaWinterstein <https://github.com/FranziskaWinterstein>`__
+-  Show logo on PyPI (`#3185 <https://github.com/ESMValGroup/ESMValTool/pull/3185>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+-  Add Release Managers for v2.9.0 and v2.10.0 (`#3184 <https://github.com/ESMValGroup/ESMValTool/pull/3184>`__) `Rémi Kazeroni <https://github.com/remi-kazeroni>`__
+-  Fix readthedocs build with esmpy>=8.4.0 and missing ESMFMKFILE variable (`#3205 <https://github.com/ESMValGroup/ESMValTool/pull/3205>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+-  Add ESMValCore release v2.8.1 into the documentation (`#3235 <https://github.com/ESMValGroup/ESMValTool/pull/3235>`__) `Rémi Kazeroni <https://github.com/remi-kazeroni>`__
+-  Modified links to the tutorial (`#3236 <https://github.com/ESMValGroup/ESMValTool/pull/3236>`__) `Rémi Kazeroni <https://github.com/remi-kazeroni>`__
+-  Fix gitter badge in README (`#3258 <https://github.com/ESMValGroup/ESMValTool/pull/3258>`__) `Rémi Kazeroni <https://github.com/remi-kazeroni>`__
+-  Add release notes for v2.9.0 (`#3266 <https://github.com/ESMValGroup/ESMValTool/pull/3266>`__) `Bouwe Andela <https://github.com/bouweandela>`__
+
+Diagnostics
+~~~~~~~~~~~
+
+-  New plot_type 1d_profile in monitor  (`#3178 <https://github.com/ESMValGroup/ESMValTool/pull/3178>`__) `FranziskaWinterstein <https://github.com/FranziskaWinterstein>`__
+-  Add Seaborn diagnostic (`#3155 <https://github.com/ESMValGroup/ESMValTool/pull/3155>`__) `Manuel Schlund <https://github.com/schlunma>`__
+-  New recipe and diagnostic for Arctic-midlatitude research (`#3021 <https://github.com/ESMValGroup/ESMValTool/pull/3021>`__) `Evgenia Galytska <https://github.com/egalytska>`__
+-  Generate climatology on the fly for AutoAssess soil moisture (`#3197 <https://github.com/ESMValGroup/ESMValTool/pull/3197>`__) `Alistair Sellar <https://github.com/alistairsellar>`__
+-  Remove "fx_variables" from recipe_tebaldi21esd.yml (`#3211 <https://github.com/ESMValGroup/ESMValTool/pull/3211>`__) `Birgit Hassler <https://github.com/hb326>`__
+-  Remove "fx_variables" from ipccwg1ar5ch9 recipes (`#3215 <https://github.com/ESMValGroup/ESMValTool/pull/3215>`__) `katjaweigel <https://github.com/katjaweigel>`__
+-  Remove "fx_variables" from recipe_wenzel14jgr.yml (`#3212 <https://github.com/ESMValGroup/ESMValTool/pull/3212>`__) `Birgit Hassler <https://github.com/hb326>`__
+-  Update obs4MIPs dataset to the current naming scheme in recipe_smpi.yml (`#2991 <https://github.com/ESMValGroup/ESMValTool/pull/2991>`__) `Bouwe Andela <https://github.com/bouweandela>`__
+-  Fixed pandas diagnostics for pandas>=2.0.0 (`#3209 <https://github.com/ESMValGroup/ESMValTool/pull/3209>`__) `Manuel Schlund <https://github.com/schlunma>`__
+-  Update recipe_impact.yml to work with newer versions of `pandas` (`#3220 <https://github.com/ESMValGroup/ESMValTool/pull/3220>`__) `Bouwe Andela <https://github.com/bouweandela>`__
+-  Add variable long names to provenance record in monitoring diagnostics (`#3222 <https://github.com/ESMValGroup/ESMValTool/pull/3222>`__) `Brei Soliño <https://github.com/bsolino>`__
+
+Observational and re-analysis dataset support
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+-  Add CMORizer for GPCP-SG (pr) (`#3150 <https://github.com/ESMValGroup/ESMValTool/pull/3150>`__) `FranziskaWinterstein <https://github.com/FranziskaWinterstein>`__
+-  Extension of NASA MERRA2 CMORizer (cl, cli, clivi, clw, clwvi) (`#3167 <https://github.com/ESMValGroup/ESMValTool/pull/3167>`__) `Axel Lauer <https://github.com/axel-lauer>`__
+
+Automatic testing
+~~~~~~~~~~~~~~~~~
+
+-  Add a CircleCI-testing-specific ``recipe_python_for_CI.yml`` to avoid calling geolocator/Nominatim over CI (`#3159 <https://github.com/ESMValGroup/ESMValTool/pull/3159>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+-  Check if Python minor version changed after Julia install in development installation test (`#3213 <https://github.com/ESMValGroup/ESMValTool/pull/3213>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+-  Fix tests using deprecated ``esmvalcore._config`` module that has been removed in ESMValCore v2.9 (`#3204 <https://github.com/ESMValGroup/ESMValTool/pull/3204>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+
+Installation
+~~~~~~~~~~~~
+
+-  Add support for Python=3.11 (`#3173 <https://github.com/ESMValGroup/ESMValTool/pull/3173>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+-  Drop python=3.8 support (`#3193 <https://github.com/ESMValGroup/ESMValTool/pull/3193>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+-  Repair generation of conda lock files (`#3148 <https://github.com/ESMValGroup/ESMValTool/pull/3148>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+-  Modernize lock creation script and repair lock generation (`#3174 <https://github.com/ESMValGroup/ESMValTool/pull/3174>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+-  Pin numpy !=1.24.3 due to severe masking bug (`#3182 <https://github.com/ESMValGroup/ESMValTool/pull/3182>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+-  Update xesmf to versions >= 0.4.0 (`#2728 <https://github.com/ESMValGroup/ESMValTool/pull/2728>`__) `Klaus Zimmermann <https://github.com/zklaus>`__
+-  Update esmpy import for ESMF version 8.4.0 or larger (`#3188 <https://github.com/ESMValGroup/ESMValTool/pull/3188>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+-  Relax the pin on iris to allow the use of older versions for performance reasons (`#3270 <https://github.com/ESMValGroup/ESMValTool/pull/3270>`__) `Bouwe Andela <https://github.com/bouweandela>`__
+-  Use ESMValCore v2.9.0 (`#3274 <https://github.com/ESMValGroup/ESMValTool/pull/3274>`__) `Bouwe Andela <https://github.com/bouweandela>`__
+
+Improvements
+~~~~~~~~~~~~
+
+-  Update pre-commit hooks (`#3189 <https://github.com/ESMValGroup/ESMValTool/pull/3189>`__) `Bouwe Andela <https://github.com/bouweandela>`__
+-  Add support for using a dask distributed scheduler (`#3151 <https://github.com/ESMValGroup/ESMValTool/pull/3151>`__) `Bouwe Andela <https://github.com/bouweandela>`__
 
 .. _changelog-v2-8-0:
 
@@ -19,7 +126,7 @@ Highlights
    climatologies from CMIP models as used in `Lauer et al. (2023), J. Climate
    <https://doi.org/10.1175/JCLI-D-22-0181.1>`__.
    See :ref:`recipe documentation <recipes_clouds>` about added recipes.
--  Addition of a set of recipes for extreme events, regional and impact 
+-  Addition of a set of recipes for extreme events, regional and impact
    evaluation as used in `Weigel et al. (2021), J. Climate
    <https://doi.org/10.5194/gmd-14-3159-2021>`__ and in IPCC AR5.
    See :ref:`recipe documentation <recipes_ipccwg1ar5ch9>` about added recipes.
@@ -265,7 +372,7 @@ Documentation
 -  Update documentation for the Landschuetzer 2016 recipe. (`#2801 <https://github.com/ESMValGroup/ESMValTool/pull/2801>`__) `Tomas Torsvik <https://github.com/TomasTorsvik>`__
 -  Fixed anaconda badge in README (`#2866 <https://github.com/ESMValGroup/ESMValTool/pull/2866>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
 -  Update release strategy notes (`#2734 <https://github.com/ESMValGroup/ESMValTool/pull/2734>`__) `sloosvel <https://github.com/sloosvel>`__
--  Add documention on how to handle CMORizers for multiple dataset versions (`#2730 <https://github.com/ESMValGroup/ESMValTool/pull/2730>`__) `Rémi Kazeroni <https://github.com/remi-kazeroni>`__
+-  Add documentation on how to handle CMORizers for multiple dataset versions (`#2730 <https://github.com/ESMValGroup/ESMValTool/pull/2730>`__) `Rémi Kazeroni <https://github.com/remi-kazeroni>`__
 -  Extending documentation: recipe maintainer + broken recipe policy (`#2719 <https://github.com/ESMValGroup/ESMValTool/pull/2719>`__) `Axel Lauer <https://github.com/axel-lauer>`__
 
 Diagnostics
@@ -310,8 +417,8 @@ Highlights
 ~~~~~~~~~~
 
 - A new monitoring diagnostic has been added to allow the comparison of model runs against reference datasets. For details, see :ref:`Monitoring diagnostic to show multiple datasets in one plot (incl. biases) <api.esmvaltool.diag_scripts.monitor.multi_datasets>`.
-- A tool has been developed to compare the output of recipe runs against previous runs, in order to detect in an automatized way breaking changes between releases. Find more information in :ref:`Comparing recipe runs <compare_recipe_runs>`.
-- The recipe :ref:`Climate Change Hotspot <recipe_climate_change_hotspot.rst>` allows to compute hotspots in any rectangular region. 
+- A tool has been developed to compare the output of recipe runs against previous runs, in order to detect in an automated way breaking changes between releases. Find more information in :ref:`Comparing recipe runs <compare_recipe_runs>`.
+- The recipe :ref:`Climate Change Hotspot <recipe_climate_change_hotspot.rst>` allows to compute hotspots in any rectangular region.
 
 Please also note the highlights from the corresponding ESMValCore release :ref:`here<esmvalcore:changelog-v2-6-0>`.
 Thanks to that ESMValTool has gained the following features:
@@ -418,7 +525,7 @@ Thanks to that ESMValTool has gained the following features:
 
 - The new preprocessor ``extract_location`` can extract arbitrary locations on the Earth.
 - Time ranges can now be extracted using the `ISO 8601 format <https://en.wikipedia.org/wiki/ISO_8601>`_.
-- The new preprocessor ``ensemble_statistics`` can calculate arbitrary statitics over all ensemble members of a simulation.
+- The new preprocessor ``ensemble_statistics`` can calculate arbitrary statistics over all ensemble members of a simulation.
 
 
 This release includes

From 35c4fcfdceddf3c1dfbd1cf6004ab7bdeee7abc6 Mon Sep 17 00:00:00 2001
From: Bouwe Andela <b.andela@esciencecenter.nl>
Date: Thu, 6 Jul 2023 16:20:23 +0200
Subject: [PATCH 20/93] Add release notes for v2.9 (#3266)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Co-authored-by: Valeriu Predoi <valeriu.predoi@gmail.com>
Co-authored-by: Rémi Kazeroni <remi.kazeroni@dlr.de>
---
 CITATION.cff                    |   4 +-
 doc/sphinx/source/changelog.rst | 117 ++++++++++++++++++++++++++++++--
 2 files changed, 114 insertions(+), 7 deletions(-)

diff --git a/CITATION.cff b/CITATION.cff
index f069250a3d..31404e4c7e 100644
--- a/CITATION.cff
+++ b/CITATION.cff
@@ -351,11 +351,11 @@ authors:
     orcid: "https://orcid.org/0000-0002-2406-4936"
 
 cff-version: 1.2.0
-date-released: 2023-03-28
+date-released: 2023-07-06
 doi: "10.5281/zenodo.3401363"
 license: "Apache-2.0"
 message: "If you use this software, please cite it using these metadata."
 repository-code: "https://github.com/ESMValGroup/ESMValTool/"
 title: ESMValTool
-version: "v2.8.0"
+version: "v2.9.0"
 ...
diff --git a/doc/sphinx/source/changelog.rst b/doc/sphinx/source/changelog.rst
index e26ec7d26b..52c3aa3086 100644
--- a/doc/sphinx/source/changelog.rst
+++ b/doc/sphinx/source/changelog.rst
@@ -3,6 +3,113 @@
 Changelog
 =========
 
+.. _changelog-v2-9-0:
+
+v2.9.0
+------
+
+Highlights
+~~~~~~~~~~
+
+-  A new :ref:`diagnostic <api.esmvaltool.diag_scripts.seaborn_diag>` has been
+   added to provide a high-level interface to
+   `seaborn <https://seaborn.pydata.org/>`__,
+   a Python data visualization library based on
+   `matplotlib <https://matplotlib.org/>`__.
+   See the :ref:`recipe documentation <recipes_seaborn_diag>` for more
+   information.
+
+-  We have included a new recipe and diagnostic that represent the major
+   physical processes that describe Arctic-midlatitude teleconnections and
+   provide the basis for the CMIP6 model evaluation for the further application
+   of causal discovery.
+   The results are discussed in the article
+   `"Causal model evaluation of Arctic-midlatitude teleconnections in CMIP6" <https://essopenarchive.org/doi/full/10.1002/essoar.10512569.1>`__
+   by Galytska et al. (in review in Journal of Geophysical Research: Atmospheres).
+
+-  It is now possible to use the
+   `Dask distributed scheduler <https://docs.dask.org/en/latest/deploying.html>`__,
+   which can
+   `significantly reduce the run-time of recipes <https://github.com/ESMValGroup/ESMValCore/pull/2049#pullrequestreview-1446279391>`__.
+   Configuration examples and advice are available in the
+   :ref:`ESMValCore documentation <esmvalcore:config-dask>`.
+   If configured, the Dask distributed scheduler will also be used by diagnostic
+   scripts written in Python, so make sure to use
+   `lazy data <https://scitools-iris.readthedocs.io/en/latest/userguide/real_and_lazy_data.html#real-and-lazy-data>`__
+   wherever it is possible in your (new) diagnostics.
+   More work on improving the computational performance is planned, so please
+   share your experiences, good and bad, with this new feature in
+   `ESMValGroup/ESMValCore#1763 <https://github.com/ESMValGroup/ESMValCore/discussions/1763>`__.
+
+This release includes
+
+Bug fixes
+~~~~~~~~~
+
+-  Fixed usage of ``work_dir`` in some CMORizer scripts (`#3192 <https://github.com/ESMValGroup/ESMValTool/pull/3192>`__) `Rémi Kazeroni <https://github.com/remi-kazeroni>`__
+-  Realize data for scalar cube in `recipe_carvalhais14nat` to avert issue from dask latest (2023.6.0) (`#3265 <https://github.com/ESMValGroup/ESMValTool/pull/3265>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+-  Fix failing ``mlr`` diagnostic test by adding new scikit-learn default tag (`#3273 <https://github.com/ESMValGroup/ESMValTool/pull/3273>`__) `Rémi Kazeroni <https://github.com/remi-kazeroni>`__
+-  Fix ordering of models in perfmetrics diagnostic script (`#3275 <https://github.com/ESMValGroup/ESMValTool/pull/3275>`__) `Lisa Bock <https://github.com/LisaBock>`__
+
+Documentation
+~~~~~~~~~~~~~
+
+-  Update release schedule after v2.8.0 (`#3138 <https://github.com/ESMValGroup/ESMValTool/pull/3138>`__) `Rémi Kazeroni <https://github.com/remi-kazeroni>`__
+-  Added reference entry for Winterstein (`#3154 <https://github.com/ESMValGroup/ESMValTool/pull/3154>`__) `FranziskaWinterstein <https://github.com/FranziskaWinterstein>`__
+-  Show logo on PyPI (`#3185 <https://github.com/ESMValGroup/ESMValTool/pull/3185>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+-  Add Release Managers for v2.9.0 and v2.10.0 (`#3184 <https://github.com/ESMValGroup/ESMValTool/pull/3184>`__) `Rémi Kazeroni <https://github.com/remi-kazeroni>`__
+-  Fix readthedocs build with esmpy>=8.4.0 and missing ESMFMKFILE variable (`#3205 <https://github.com/ESMValGroup/ESMValTool/pull/3205>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+-  Add ESMValCore release v2.8.1 into the documentation (`#3235 <https://github.com/ESMValGroup/ESMValTool/pull/3235>`__) `Rémi Kazeroni <https://github.com/remi-kazeroni>`__
+-  Modified links to the tutorial (`#3236 <https://github.com/ESMValGroup/ESMValTool/pull/3236>`__) `Rémi Kazeroni <https://github.com/remi-kazeroni>`__
+-  Fix gitter badge in README (`#3258 <https://github.com/ESMValGroup/ESMValTool/pull/3258>`__) `Rémi Kazeroni <https://github.com/remi-kazeroni>`__
+-  Add release notes for v2.9.0 (`#3266 <https://github.com/ESMValGroup/ESMValTool/pull/3266>`__) `Bouwe Andela <https://github.com/bouweandela>`__
+
+Diagnostics
+~~~~~~~~~~~
+
+-  New plot_type 1d_profile in monitor  (`#3178 <https://github.com/ESMValGroup/ESMValTool/pull/3178>`__) `FranziskaWinterstein <https://github.com/FranziskaWinterstein>`__
+-  Add Seaborn diagnostic (`#3155 <https://github.com/ESMValGroup/ESMValTool/pull/3155>`__) `Manuel Schlund <https://github.com/schlunma>`__
+-  New recipe and diagnostic for Arctic-midlatitude research (`#3021 <https://github.com/ESMValGroup/ESMValTool/pull/3021>`__) `Evgenia Galytska <https://github.com/egalytska>`__
+-  Generate climatology on the fly for AutoAssess soil moisture (`#3197 <https://github.com/ESMValGroup/ESMValTool/pull/3197>`__) `Alistair Sellar <https://github.com/alistairsellar>`__
+-  Remove "fx_variables" from recipe_tebaldi21esd.yml (`#3211 <https://github.com/ESMValGroup/ESMValTool/pull/3211>`__) `Birgit Hassler <https://github.com/hb326>`__
+-  Remove "fx_variables" from ipccwg1ar5ch9 recipes (`#3215 <https://github.com/ESMValGroup/ESMValTool/pull/3215>`__) `katjaweigel <https://github.com/katjaweigel>`__
+-  Remove "fx_variables" from recipe_wenzel14jgr.yml (`#3212 <https://github.com/ESMValGroup/ESMValTool/pull/3212>`__) `Birgit Hassler <https://github.com/hb326>`__
+-  Update obs4MIPs dataset to the current naming scheme in recipe_smpi.yml (`#2991 <https://github.com/ESMValGroup/ESMValTool/pull/2991>`__) `Bouwe Andela <https://github.com/bouweandela>`__
+-  Fixed pandas diagnostics for pandas>=2.0.0 (`#3209 <https://github.com/ESMValGroup/ESMValTool/pull/3209>`__) `Manuel Schlund <https://github.com/schlunma>`__
+-  Update recipe_impact.yml to work with newer versions of `pandas` (`#3220 <https://github.com/ESMValGroup/ESMValTool/pull/3220>`__) `Bouwe Andela <https://github.com/bouweandela>`__
+-  Add variable long names to provenance record in monitoring diagnostics (`#3222 <https://github.com/ESMValGroup/ESMValTool/pull/3222>`__) `Brei Soliño <https://github.com/bsolino>`__
+
+Observational and re-analysis dataset support
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+-  Add CMORizer for GPCP-SG (pr) (`#3150 <https://github.com/ESMValGroup/ESMValTool/pull/3150>`__) `FranziskaWinterstein <https://github.com/FranziskaWinterstein>`__
+-  Extension of NASA MERRA2 CMORizer (cl, cli, clivi, clw, clwvi) (`#3167 <https://github.com/ESMValGroup/ESMValTool/pull/3167>`__) `Axel Lauer <https://github.com/axel-lauer>`__
+
+Automatic testing
+~~~~~~~~~~~~~~~~~
+
+-  Add a CircleCI-testing-specific ``recipe_python_for_CI.yml`` to avoid calling geolocator/Nominatim over CI (`#3159 <https://github.com/ESMValGroup/ESMValTool/pull/3159>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+-  Check if Python minor version changed after Julia install in development installation test (`#3213 <https://github.com/ESMValGroup/ESMValTool/pull/3213>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+-  Fix tests using deprecated ``esmvalcore._config`` module that has been removed in ESMValCore v2.9 (`#3204 <https://github.com/ESMValGroup/ESMValTool/pull/3204>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+
+Installation
+~~~~~~~~~~~~
+
+-  Add support for Python=3.11 (`#3173 <https://github.com/ESMValGroup/ESMValTool/pull/3173>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+-  Drop python=3.8 support (`#3193 <https://github.com/ESMValGroup/ESMValTool/pull/3193>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+-  Repair generation of conda lock files (`#3148 <https://github.com/ESMValGroup/ESMValTool/pull/3148>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+-  Modernize lock creation script and repair lock generation (`#3174 <https://github.com/ESMValGroup/ESMValTool/pull/3174>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+-  Pin numpy !=1.24.3 due to severe masking bug (`#3182 <https://github.com/ESMValGroup/ESMValTool/pull/3182>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+-  Update xesmf to versions >= 0.4.0 (`#2728 <https://github.com/ESMValGroup/ESMValTool/pull/2728>`__) `Klaus Zimmermann <https://github.com/zklaus>`__
+-  Update esmpy import for ESMF version 8.4.0 or larger (`#3188 <https://github.com/ESMValGroup/ESMValTool/pull/3188>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
+-  Relax the pin on iris to allow the use of older versions for performance reasons (`#3270 <https://github.com/ESMValGroup/ESMValTool/pull/3270>`__) `Bouwe Andela <https://github.com/bouweandela>`__
+-  Use ESMValCore v2.9.0 (`#3274 <https://github.com/ESMValGroup/ESMValTool/pull/3274>`__) `Bouwe Andela <https://github.com/bouweandela>`__
+
+Improvements
+~~~~~~~~~~~~
+
+-  Update pre-commit hooks (`#3189 <https://github.com/ESMValGroup/ESMValTool/pull/3189>`__) `Bouwe Andela <https://github.com/bouweandela>`__
+-  Add support for using a dask distributed scheduler (`#3151 <https://github.com/ESMValGroup/ESMValTool/pull/3151>`__) `Bouwe Andela <https://github.com/bouweandela>`__
 
 .. _changelog-v2-8-0:
 
@@ -19,7 +126,7 @@ Highlights
    climatologies from CMIP models as used in `Lauer et al. (2023), J. Climate
    <https://doi.org/10.1175/JCLI-D-22-0181.1>`__.
    See :ref:`recipe documentation <recipes_clouds>` about added recipes.
--  Addition of a set of recipes for extreme events, regional and impact 
+-  Addition of a set of recipes for extreme events, regional and impact
    evaluation as used in `Weigel et al. (2021), J. Climate
    <https://doi.org/10.5194/gmd-14-3159-2021>`__ and in IPCC AR5.
    See :ref:`recipe documentation <recipes_ipccwg1ar5ch9>` about added recipes.
@@ -265,7 +372,7 @@ Documentation
 -  Update documentation for the Landschuetzer 2016 recipe. (`#2801 <https://github.com/ESMValGroup/ESMValTool/pull/2801>`__) `Tomas Torsvik <https://github.com/TomasTorsvik>`__
 -  Fixed anaconda badge in README (`#2866 <https://github.com/ESMValGroup/ESMValTool/pull/2866>`__) `Valeriu Predoi <https://github.com/valeriupredoi>`__
 -  Update release strategy notes (`#2734 <https://github.com/ESMValGroup/ESMValTool/pull/2734>`__) `sloosvel <https://github.com/sloosvel>`__
--  Add documention on how to handle CMORizers for multiple dataset versions (`#2730 <https://github.com/ESMValGroup/ESMValTool/pull/2730>`__) `Rémi Kazeroni <https://github.com/remi-kazeroni>`__
+-  Add documentation on how to handle CMORizers for multiple dataset versions (`#2730 <https://github.com/ESMValGroup/ESMValTool/pull/2730>`__) `Rémi Kazeroni <https://github.com/remi-kazeroni>`__
 -  Extending documentation: recipe maintainer + broken recipe policy (`#2719 <https://github.com/ESMValGroup/ESMValTool/pull/2719>`__) `Axel Lauer <https://github.com/axel-lauer>`__
 
 Diagnostics
@@ -310,8 +417,8 @@ Highlights
 ~~~~~~~~~~
 
 - A new monitoring diagnostic has been added to allow the comparison of model runs against reference datasets. For details, see :ref:`Monitoring diagnostic to show multiple datasets in one plot (incl. biases) <api.esmvaltool.diag_scripts.monitor.multi_datasets>`.
-- A tool has been developed to compare the output of recipe runs against previous runs, in order to detect in an automatized way breaking changes between releases. Find more information in :ref:`Comparing recipe runs <compare_recipe_runs>`.
-- The recipe :ref:`Climate Change Hotspot <recipe_climate_change_hotspot.rst>` allows to compute hotspots in any rectangular region. 
+- A tool has been developed to compare the output of recipe runs against previous runs, in order to detect in an automated way breaking changes between releases. Find more information in :ref:`Comparing recipe runs <compare_recipe_runs>`.
+- The recipe :ref:`Climate Change Hotspot <recipe_climate_change_hotspot.rst>` allows to compute hotspots in any rectangular region.
 
 Please also note the highlights from the corresponding ESMValCore release :ref:`here<esmvalcore:changelog-v2-6-0>`.
 Thanks to that ESMValTool has gained the following features:
@@ -418,7 +525,7 @@ Thanks to that ESMValTool has gained the following features:
 
 - The new preprocessor ``extract_location`` can extract arbitrary locations on the Earth.
 - Time ranges can now be extracted using the `ISO 8601 format <https://en.wikipedia.org/wiki/ISO_8601>`_.
-- The new preprocessor ``ensemble_statistics`` can calculate arbitrary statitics over all ensemble members of a simulation.
+- The new preprocessor ``ensemble_statistics`` can calculate arbitrary statistics over all ensemble members of a simulation.
 
 
 This release includes

From 197024d940179601363b5a619bd0e5d048901a7c Mon Sep 17 00:00:00 2001
From: Manuel Schlund <32543114+schlunma@users.noreply.github.com>
Date: Wed, 12 Jul 2023 16:01:26 +0200
Subject: [PATCH 21/93] Made sklearn test backwards-compatible with sklearn <
 1.3 (#3285)

---
 .../mlr/test_custom_sklearn_functions.py          | 15 +++++++++++----
 1 file changed, 11 insertions(+), 4 deletions(-)

diff --git a/tests/integration/diag_scripts/mlr/test_custom_sklearn_functions.py b/tests/integration/diag_scripts/mlr/test_custom_sklearn_functions.py
index f14ccb3e2e..b058465188 100644
--- a/tests/integration/diag_scripts/mlr/test_custom_sklearn_functions.py
+++ b/tests/integration/diag_scripts/mlr/test_custom_sklearn_functions.py
@@ -459,10 +459,18 @@ def _more_tags(self):
         return {"allow_nan": True}
 
 
+class MockBaseEstimator:
+    """Estimator with ``_get_tags``."""
+
+    def _get_tags(self):
+        """Return tags."""
+        return _DEFAULT_TAGS
+
+
 @pytest.mark.parametrize(
     'estimator,err_msg',
     [
-        (BaseEstimator(), 'The key xxx is not defined in _get_tags'),
+        (MockBaseEstimator(), 'The key xxx is not defined in _get_tags'),
         (NoTagsEstimator(), 'The key xxx is not defined in _DEFAULT_TAGS'),
     ],
 )
@@ -480,9 +488,8 @@ def test_safe_tags_error(estimator, err_msg):
         (NoTagsEstimator(), 'allow_nan', _DEFAULT_TAGS['allow_nan']),
         (MoreTagsEstimator(), None, {**_DEFAULT_TAGS, **{'allow_nan': True}}),
         (MoreTagsEstimator(), 'allow_nan', True),
-        (BaseEstimator(), None, _DEFAULT_TAGS),
-        (BaseEstimator(), 'allow_nan', _DEFAULT_TAGS['allow_nan']),
-        (BaseEstimator(), 'allow_nan', _DEFAULT_TAGS['allow_nan']),
+        (MockBaseEstimator(), None, _DEFAULT_TAGS),
+        (MockBaseEstimator(), 'allow_nan', _DEFAULT_TAGS['allow_nan']),
     ],
 )
 def test_safe_tags_no_get_tags(estimator, key, expected_results):

From 4da5cd376035bfe61220791293cd520305dd6113 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?R=C3=A9mi=20Kazeroni?= <remi.kazeroni@dlr.de>
Date: Thu, 13 Jul 2023 13:13:15 +0200
Subject: [PATCH 22/93] Add merge instructions to release instructions (#3292)

---
 .../release_strategy/release_strategy.rst     | 36 +++++++++++++++++--
 1 file changed, 33 insertions(+), 3 deletions(-)

diff --git a/doc/sphinx/source/community/release_strategy/release_strategy.rst b/doc/sphinx/source/community/release_strategy/release_strategy.rst
index 9843e52363..696dbfd997 100644
--- a/doc/sphinx/source/community/release_strategy/release_strategy.rst
+++ b/doc/sphinx/source/community/release_strategy/release_strategy.rst
@@ -462,7 +462,37 @@ and create the new release from the release branch (i.e. not from ``main``).
 The release tag always starts with the letter ``v`` followed by the version
 number, e.g. ``v2.1.0``.
 
-6. Create and upload the PyPI package
+6. Mark the release in the main branch
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+When the (pre-)release is tagged, it is time to merge the release branch back into `main`.
+We do this for two reasons, namely, one, to mark the point up to which commits in `main`
+have been considered for inclusion into the present release, and, two, to inform
+setuptools-scm about the version number so that it creates the correct version number in
+`main`.
+However, unlike in a normal merge, we do not want to integrate any of the changes from the
+release branch into main.
+This is because all changes that should be in both branches, i.e. bug fixes, originate from
+`main` anyway and the only other changes in the release branch relate to the release itself.
+To take this into account, we perform the merge in this case on the command line using `the
+ours merge strategy <https://git-scm.com/docs/merge-strategies#Documentation/merge-strategies.txt-ours-1>`__
+(``git merge -s ours``), not to be confused with the ``ours`` option to the ort merge strategy
+(``git merge -X ours``).
+For details about merge strategies, see the above-linked page.
+To execute the merge use following sequence of steps
+
+.. code-block:: bash
+
+   git fetch
+   git checkout main
+   git pull
+   git merge -s ours v2.1.x
+   git push
+
+Note that the release branch remains intact and you should continue any work on the release
+on that branch.
+
+7. Create and upload the PyPI package
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 The package is automatically uploaded to the
@@ -493,7 +523,7 @@ Follow these steps to create a new Python package:
 You can read more about this in
 `Packaging Python Projects <https://packaging.python.org/tutorials/packaging-projects/>`__.
 
-7. Create the Conda package
+8. Create the Conda package
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 The ``esmvaltool`` package is published on the `conda-forge conda channel
@@ -514,7 +544,7 @@ they will merge the pull request, which will in turn publish the package on
 conda-forge some time later.
 Contact the feedstock maintainers if you want to become a maintainer yourself.
 
-8. Check the Docker images
+9. Check the Docker images
 ~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 There are three main Docker container images available for ESMValTool on

From 3fcece52b4cd2c8d4cd7739faab4f50bcdafb7ae Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?R=C3=A9mi=20Kazeroni?= <remi.kazeroni@dlr.de>
Date: Fri, 14 Jul 2023 08:57:31 +0200
Subject: [PATCH 23/93] Update release schedule after release of v2.9.0 (#3289)

---
 .../release_strategy/release_strategy.rst     | 26 ++++++++++---------
 1 file changed, 14 insertions(+), 12 deletions(-)

diff --git a/doc/sphinx/source/community/release_strategy/release_strategy.rst b/doc/sphinx/source/community/release_strategy/release_strategy.rst
index 696dbfd997..9bd8d71e2d 100644
--- a/doc/sphinx/source/community/release_strategy/release_strategy.rst
+++ b/doc/sphinx/source/community/release_strategy/release_strategy.rst
@@ -54,18 +54,6 @@ With the following release schedule, we strive to have three releases per year a
 Upcoming releases
 ^^^^^^^^^^^^^^^^^
 
-- 2.9.0 (Release Manager: `Bouwe Andela`_)
-
-+------------+--------------------------+
-| 2023-06-05 |ESMValCore feature freeze |
-+------------+--------------------------+
-| 2023-06-12 |ESMValCore release        |
-+------------+--------------------------+
-| 2023-06-19 |ESMValTool feature freeze |
-+------------+--------------------------+
-| 2023-06-26 |ESMValTool release        |
-+------------+--------------------------+
-
 - 2.10.0 (Release Manager: `Klaus Zimmermann`_)
 
 +------------+--------------------------+
@@ -81,6 +69,20 @@ Upcoming releases
 Past releases
 ^^^^^^^^^^^^^
 
+- 2.9.0 (Release Manager: `Bouwe Andela`_)
+
++------------+------------+---------------------------------------------------------------------------------------------+------------------------------------+
+|  Planned   |    Done    |                                            Event                                            |             Changelog              |
++============+============+=============================================================================================+====================================+
+| 2023-06-05 |            |                                  ESMValCore Feature Freeze                                  |                                    |
++------------+------------+---------------------------------------------------------------------------------------------+------------------------------------+
+| 2023-06-12 | 2023-07-04 | `ESMValCore Release 2.9.0 <https://github.com/ESMValGroup/ESMValCore/releases/tag/v2.9.0>`_ | :ref:`esmvalcore:changelog-v2-9-0` |
++------------+------------+---------------------------------------------------------------------------------------------+------------------------------------+
+| 2023-06-19 |            |                                  ESMValTool Feature Freeze                                  |                                    |
++------------+------------+---------------------------------------------------------------------------------------------+------------------------------------+
+| 2023-06-26 | 2023-07-06 | `ESMValTool Release 2.9.0 <https://github.com/ESMValGroup/ESMValTool/releases/tag/v2.9.0>`_ |      :ref:`changelog-v2-9-0`       |
++------------+------------+---------------------------------------------------------------------------------------------+------------------------------------+
+
 - 2.8.1 (Bugfix, Release Manager: `Valeriu Predoi`_)
 
 +------------+---------------------------------------------------------------------------------------------+------------------------------------+

From d87863682c0ef9725185d7b126dd56c64ea75ab0 Mon Sep 17 00:00:00 2001
From: Lukas <lukas@uni-bremen.de>
Date: Mon, 17 Jul 2023 13:52:16 +0200
Subject: [PATCH 24/93] Update diag_shapeselect.py to work with shapely v2
 (#3283)

---
 .../shapeselect/diag_shapeselect.py           | 61 ++++++++++++-------
 esmvaltool/recipes/recipe_shapeselect.yml     |  2 +-
 2 files changed, 39 insertions(+), 24 deletions(-)

diff --git a/esmvaltool/diag_scripts/shapeselect/diag_shapeselect.py b/esmvaltool/diag_scripts/shapeselect/diag_shapeselect.py
index 403bc3e630..94ab3b14ec 100644
--- a/esmvaltool/diag_scripts/shapeselect/diag_shapeselect.py
+++ b/esmvaltool/diag_scripts/shapeselect/diag_shapeselect.py
@@ -11,8 +11,11 @@
 from shapely.geometry import MultiPoint, shape
 from shapely.ops import nearest_points
 
-from esmvaltool.diag_scripts.shared import (run_diagnostic, ProvenanceLogger,
-                                            get_diagnostic_filename)
+from esmvaltool.diag_scripts.shared import (
+    ProvenanceLogger,
+    get_diagnostic_filename,
+    run_diagnostic,
+)
 
 logger = logging.getLogger(os.path.basename(__file__))
 
@@ -48,16 +51,22 @@ def main(cfg):
             xname = name + '_table'
             writexls(cfg, filename, ncts, nclon, nclat)
             caption = 'Selected gridpoints within shapefile.'
-            get_provenance_record(
-                cfg, xname, caption, 'xlsx', ancestor_files=[filename])
+            get_provenance_record(cfg,
+                                  xname,
+                                  caption,
+                                  'xlsx',
+                                  ancestor_files=[filename])
         path = os.path.join(
             cfg['work_dir'],
             name + '.nc',
         )
         write_netcdf(path, ncts, nclon, nclat, cube, cfg)
         caption = 'Selected gridpoints within shapefile.'
-        get_provenance_record(
-            cfg, name, caption, 'nc', ancestor_files=[filename])
+        get_provenance_record(cfg,
+                              name,
+                              caption,
+                              'nc',
+                              ancestor_files=[filename])
 
 
 def write_keyvalue_toxlsx(worksheet, row, key, value):
@@ -93,17 +102,16 @@ def writexls(cfg, filename, ncts, nclon1, nclat1):
     workbook = xlsxwriter.Workbook(
         os.path.join(
             cfg['work_dir'],
-            os.path.splitext(os.path.basename(filename))[0] + '_polygon_table'
-            + '.xlsx'))
+            os.path.splitext(os.path.basename(filename))[0] +
+            '_polygon_table' + '.xlsx'))
     worksheet = workbook.add_worksheet('Data')
     worksheet.write(0, 0, 'Date')
     worksheet.write(0, 1, 'Lon/Lat')
     worksheet.write_column(2, 0, wtime)
     for row in range(ncts.shape[1]):
         worksheet.write(
-            1, row + 1,
-            str("%#.3f" % round(float(nclon1[row]), 3)) + '_' + str(
-                "%#.3f" % round(float(nclat1[row]), 3)))
+            1, row + 1, f"{round(float(nclon1[row]), 3):.3f}_\
+            {round(float(nclat1[row]), 3)}")
         worksheet.write_column(2, row + 1,
                                np.around(np.squeeze(ncts[:, row]), decimals=8))
         worksheet.set_column(0, row + 1, 20)
@@ -135,7 +143,8 @@ def shapeselect(cfg, cube):
                 coordpoints[i] = (coordpoints[i][0] - 360., coordpoints[i][1])
     else:
         raise ValueError("Support for 2-d coords not implemented!")
-    points = MultiPoint(coordpoints)
+    multipoint = MultiPoint(coordpoints)
+    points = list(multipoint.geoms)
     with fiona.open(shppath) as shp:
         gpx = []
         gpy = []
@@ -149,15 +158,16 @@ def shapeselect(cfg, cube):
             if wgtmet == 'mean_inside':
                 gpx, gpy = mean_inside(gpx, gpy, points, multi, cube)
                 if not gpx:
-                    gpx, gpy = representative(gpx, gpy, points, multi, cube)
+                    gpx, gpy = representative(gpx, gpy, multipoint, multi,
+                                              cube)
             elif wgtmet == 'representative':
-                gpx, gpy = representative(gpx, gpy, points, multi, cube)
+                gpx, gpy = representative(gpx, gpy, multipoint, multi, cube)
             if len(gpx) == 1:
                 ncts[:, ishp] = np.reshape(cube.data[:, gpy, gpx],
                                            (cube.data.shape[0], ))
             else:
                 ncts[:, ishp] = np.mean(cube.data[:, gpy, gpx], axis=1)
-            gxx, gyy = representative([], [], points, multi, cube)
+            gxx, gyy = representative([], [], multipoint, multi, cube)
             nclon[ishp] = cube.coord('longitude').points[gxx]
             nclat[ishp] = cube.coord('latitude').points[gyy]
     return ncts, nclon, nclat
@@ -179,10 +189,10 @@ def mean_inside(gpx, gpy, points, multi, cube):
     return gpx, gpy
 
 
-def representative(gpx, gpy, points, multi, cube):
+def representative(gpx, gpy, multipoint, multi, cube):
     """Find representative point in shape."""
     reprpoint = multi.representative_point()
-    nearest = nearest_points(reprpoint, points)
+    nearest = nearest_points(reprpoint, multipoint)
     npx = nearest[1].coords[0][0]
     npy = nearest[1].coords[0][1]
     if npx < 0:
@@ -235,19 +245,24 @@ def write_netcdf(path, var, plon, plat, cube, cfg):
     polys.setncattr_string('standard_name', 'polygon')
     polys.setncattr_string('long_name', 'polygon')
     polys.setncattr_string('shapefile', cfg['shapefile'])
-    lon = ncout.createVariable(
-        cube.coord('longitude').var_name, 'f8', 'polygon', zlib=True)
+    lon = ncout.createVariable(cube.coord('longitude').var_name,
+                               'f8',
+                               'polygon',
+                               zlib=True)
     lon.setncattr_string('standard_name',
                          cube.coord('longitude').standard_name)
     lon.setncattr_string('long_name', cube.coord('longitude').long_name)
     lon.setncattr_string('units', cube.coord('longitude').units.origin)
-    lat = ncout.createVariable(
-        cube.coord('latitude').var_name, 'f8', 'polygon', zlib=True)
+    lat = ncout.createVariable(cube.coord('latitude').var_name,
+                               'f8',
+                               'polygon',
+                               zlib=True)
     lat.setncattr_string('standard_name', cube.coord('latitude').standard_name)
     lat.setncattr_string('long_name', cube.coord('latitude').long_name)
     lat.setncattr_string('units', cube.coord('latitude').units.origin)
-    data = ncout.createVariable(
-        cube.var_name, 'f4', ('time', 'polygon'), zlib=True)
+    data = ncout.createVariable(cube.var_name,
+                                'f4', ('time', 'polygon'),
+                                zlib=True)
     data.setncattr_string('standard_name', cube.standard_name)
     data.setncattr_string('long_name', cube.long_name)
     data.setncattr_string('units', cube.units.origin)
diff --git a/esmvaltool/recipes/recipe_shapeselect.yml b/esmvaltool/recipes/recipe_shapeselect.yml
index f37a302dff..0fb22c0d5d 100644
--- a/esmvaltool/recipes/recipe_shapeselect.yml
+++ b/esmvaltool/recipes/recipe_shapeselect.yml
@@ -11,7 +11,7 @@ documentation:
     - berg_peter
 
   maintainer:
-    - unmaintained
+    - ruhe_lukas
 
   projects:
     - c3s-magic

From dcb2f043cff895a2bd4a385e5fb86e145119efd7 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?R=C3=A9mi=20Kazeroni?= <remi.kazeroni@dlr.de>
Date: Mon, 17 Jul 2023 15:13:31 +0200
Subject: [PATCH 25/93] Add list of failing recipes for v2.9.0 release (#3294)

---
 doc/sphinx/source/recipes/broken_recipe_list.rst | 10 +++++++++-
 1 file changed, 9 insertions(+), 1 deletion(-)

diff --git a/doc/sphinx/source/recipes/broken_recipe_list.rst b/doc/sphinx/source/recipes/broken_recipe_list.rst
index 5720261827..64f4437a96 100644
--- a/doc/sphinx/source/recipes/broken_recipe_list.rst
+++ b/doc/sphinx/source/recipes/broken_recipe_list.rst
@@ -15,8 +15,16 @@ More details can be found in the :ref:`broken recipe policy
    * - Broken recipe
      - Affected diagnostics
      - Problem
-     - GitHub issue 
+     - GitHub issue
+   * - :ref:`recipe_carvalhais14nat.yml <recipe_carvalhais14nat>`
+     - `global_turnover_time`
+     - ``cartopy`` issue
+     - `#3281 <https://github.com/ESMValGroup/ESMValTool/issues/3281>`_
    * - `recipe_check_obs.yml`
      - `ERA5_native6`
      - Derivation of custom variables `rlus` and `rsus`
      - `#1388 <https://github.com/ESMValGroup/ESMValCore/issues/1388>`_
+   * - :ref:`recipe_seaice_drift.yml <recipes_seaice_drift>`
+     - `sea_ice_drift_SCICEX`
+     - ``shapely`` issue
+     - `#3243 <https://github.com/ESMValGroup/ESMValTool/issues/3243>`_

From f3ad0a0b7628032cb86719bcccfe1029d6857168 Mon Sep 17 00:00:00 2001
From: Manuel Schlund <32543114+schlunma@users.noreply.github.com>
Date: Mon, 31 Jul 2023 08:50:09 +0200
Subject: [PATCH 26/93] Allow NCL unit conversion `kg s-1` -> `GtC y-1` (#3300)

---
 esmvaltool/diag_scripts/shared/scaling.ncl |  9 +++++++++
 esmvaltool/recipes/recipe_wenzel14jgr.yml  | 16 ++++++++--------
 2 files changed, 17 insertions(+), 8 deletions(-)

diff --git a/esmvaltool/diag_scripts/shared/scaling.ncl b/esmvaltool/diag_scripts/shared/scaling.ncl
index 986398746d..a2ef8f185d 100644
--- a/esmvaltool/diag_scripts/shared/scaling.ncl
+++ b/esmvaltool/diag_scripts/shared/scaling.ncl
@@ -169,6 +169,15 @@ begin
     end if
   end if
 
+  if (units_from.eq."kg.s-1") then
+    if (any(units_to.eq.(/"PgC y-1", "GtC y-1"/))) then
+      out = out * 3600. * 24. * 365 / 1.e12
+      out@units = units_to
+      leave_msg(scriptname, funcname)
+      return(out)
+    end if
+  end if
+
   if (units_from.eq."kg m-2 s-1") then
     if (any(units_to.eq.(/"PgC y-1", "GtC y-1"/))) then
       out = out * 3600. * 24. * 365 / 1.e12
diff --git a/esmvaltool/recipes/recipe_wenzel14jgr.yml b/esmvaltool/recipes/recipe_wenzel14jgr.yml
index cd66bfc64c..814da02a18 100644
--- a/esmvaltool/recipes/recipe_wenzel14jgr.yml
+++ b/esmvaltool/recipes/recipe_wenzel14jgr.yml
@@ -26,14 +26,14 @@ preprocessors:
       area_type: land
       exclude: [
         'GCP2018',
-        ]
+      ]
 
   sea_fraction_weighting:
     weighting_landsea_fraction:
       area_type: sea
       exclude: [
         'GCP2018', 'HadGEM2-ES', 'CanESM2', 'IPSL-CM5A-LR', 'GFDL-ESM2M', 'MPI-ESM-LR', 'CESM1-BGC', 'NorESM1-ME',
-        ]
+      ]
     regrid:
       target_grid: CanESM2
       scheme: area_weighted
@@ -43,30 +43,30 @@ preprocessors:
       area_type: land
       exclude: [
         'GCP2018', 'HadGEM2-ES', 'CanESM2', 'IPSL-CM5A-LR', 'GFDL-ESM2M', 'MPI-ESM-LR', 'CESM1-BGC', 'NorESM1-ME',
-        ]
+      ]
     area_statistics:
-          operator: sum
+      operator: sum
 
   tropical_land:
     weighting_landsea_fraction:
       area_type: land
       exclude: [
         'GCP2018', 'HadGEM2-ES', 'CanESM2', 'IPSL-CM5A-LR', 'GFDL-ESM2M', 'MPI-ESM-LR', 'CESM1-BGC', 'NorESM1-ME',
-        ]
+      ]
     extract_region:
       start_longitude: 0.
       end_longitude: 360.
       start_latitude: -30.
       end_latitude: 30.
     area_statistics:
-          operator: sum
+      operator: sum
 
   global_ocean:
     weighting_landsea_fraction:
       area_type: sea
       exclude: [
         'GCP2018', 'HadGEM2-ES', 'CanESM2', 'IPSL-CM5A-LR', 'GFDL-ESM2M', 'MPI-ESM-LR', 'CESM1-BGC', 'NorESM1-ME',
-        ]
+      ]
     area_statistics:
       operator: sum
 
@@ -77,7 +77,7 @@ preprocessors:
       start_latitude: -30.
       end_latitude: 30.
     area_statistics:
-          operator: mean
+      operator: mean
 
 
 diagnostics:

From 9485a64e590809368184b05047d14b098b61b9af Mon Sep 17 00:00:00 2001
From: Valeriu Predoi <valeriu.predoi@gmail.com>
Date: Wed, 2 Aug 2023 12:49:12 +0100
Subject: [PATCH 27/93] [condalock] update conda lock creation Github Action
 workflow and ship updated (bot-generated) conda-lock file (#3307)

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: valeriupredoi <valeriupredoi@users.noreply.github.com>
---
 .github/workflows/create-condalock-file.yml |  54 +++--
 conda-linux-64.lock                         | 243 ++++++++++----------
 2 files changed, 152 insertions(+), 145 deletions(-)

diff --git a/.github/workflows/create-condalock-file.yml b/.github/workflows/create-condalock-file.yml
index 34ec0aada7..9ab4443cd7 100644
--- a/.github/workflows/create-condalock-file.yml
+++ b/.github/workflows/create-condalock-file.yml
@@ -6,10 +6,15 @@ on:
   # and hence lots of automated PRs
   # push:
   #   branches:
-  #     - condalock-update
+  #     - main
   schedule:
     - cron: '0 4 */10 * *'
 
+# Required shell entrypoint to have properly configured bash shell
+defaults:
+  run:
+    shell: bash -l {0}
+
 jobs:
   create-lock-file:
     name: Create conda lock file for latest Python
@@ -27,50 +32,49 @@ jobs:
           miniforge-variant: Mambaforge
           use-mamba: true
       - name: Show conda config
-        shell: bash -l {0}
         run: |
           conda update -n base -c conda-forge conda
-          conda info
-          conda list
+          conda --version
+          # setup-miniconda@v2 installs an old conda and mamba
+          # forcing a modern mamba updates both mamba and conda
+          conda install -c conda-forge "mamba>=1.4.8"
           conda config --show-sources
           conda config --show
+          conda --version
+          mamba --version
       - name: Python info
-        shell: bash -l {0}
         run: |
           which python
           python --version
       - name: Install conda-lock
-        shell: bash -l {0}
-        run: mamba install -y conda-lock
+        run: mamba install -y -c conda-forge conda-lock
       - name: Check version of conda-lock
-        shell: bash -l {0}
         run: conda-lock --version
       - name: Create conda lock file for linux-64
-        shell: bash -l {0}
         run: conda-lock lock --platform linux-64 -f environment.yml --mamba --kind explicit
-      - shell: bash -l {0}
+      - name: Show conda version again
         run: conda --version
-      - shell: bash -l {0}
-        run: which python
-      - shell: bash -l {0}
-        run: python -V
-      - shell: bash -l {0}
+      - name: Show Python exec and version again
+        run: |
+          which python
+          python -V
+      - name: Create conda-lock environment
         run: conda create --name esmvaltool-fromlock --file conda-linux-64.lock
-      - shell: bash -l {0}
+      - name: Install pip
         run: mamba install -y pip
-      - shell: bash -l {0}
-        run: which python
-      - shell: bash -l {0}
-        run: pip --version
-      - shell: bash -l {0}
+      - name: Check Python and pip versions post pip-install
+        run: |
+          which python
+          pip --version
+      - name: Install ESMValTool
         run: pip install -e .[develop]
-      - shell: bash -l {0}
+      - name: Check ESMValTool version
         run: esmvaltool --help
-      - shell: bash -l {0}
+      - name: Check ESMValTool help
         run: esmvaltool version
-      - shell: bash -l {0}
+      - name: Run flake8
         run: flake8
-      - shell: bash -l {0}
+      - name: Run tests
         run: pytest -n 2 -m "not installation"
       # Automated PR
       # see https://github.com/marketplace/actions/create-pull-request
diff --git a/conda-linux-64.lock b/conda-linux-64.lock
index c41403d662..39331facf0 100644
--- a/conda-linux-64.lock
+++ b/conda-linux-64.lock
@@ -1,17 +1,17 @@
 # Generated by conda-lock.
 # platform: linux-64
-# input_hash: 7d637eea13b048450933417ec5ec069834faf2d132e6ccfa960adbe351ac0b19
+# input_hash: f47d35f9d83344217c0911cc8cede368892e578ba25206f3c774436c197445b3
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 https://conda.anaconda.org/conda-forge/noarch/pylint-django-2.5.3-pyhd8ed1ab_0.tar.bz2#00d8853fb1f87195722ea6a582cc9b56
 https://conda.anaconda.org/conda-forge/noarch/pylint-flask-0.6-py_0.tar.bz2#5a9afd3d0a61b08d59eed70fab859c1b
@@ -559,20 +562,20 @@ https://conda.anaconda.org/conda-forge/noarch/r-withr-2.5.0-r41hc72bb7e_1.tar.bz
 https://conda.anaconda.org/conda-forge/linux-64/r-xfun-0.39-r41ha503ecb_0.conda#555ee06849209b9471946da6f09bb98b
 https://conda.anaconda.org/conda-forge/noarch/r-xmlparsedata-1.0.5-r41hc72bb7e_1.tar.bz2#921c0ef7104d8df0ab506f1bb81a062c
 https://conda.anaconda.org/conda-forge/linux-64/r-yaml-2.3.7-r41h133d619_0.conda#4af88071a607237aa73a3cbd51788a39
-https://conda.anaconda.org/conda-forge/linux-64/scikit-image-0.20.0-py311h2872171_1.conda#24fca64735554fdf2794c69f5b3d9a06
-https://conda.anaconda.org/conda-forge/linux-64/scikit-learn-1.2.2-py311hc009520_2.conda#538b903a5572cf48fb87c8d30fc06e0d
+https://conda.anaconda.org/conda-forge/linux-64/scikit-image-0.21.0-py311hb755f60_0.conda#0a8cbf18f7e57e43b8e106630a0ca7df
+https://conda.anaconda.org/conda-forge/linux-64/scikit-learn-1.3.0-py311hc009520_0.conda#847797c4a9c0c3363ffcfe7571dedfee
 https://conda.anaconda.org/conda-forge/noarch/seaborn-base-0.12.2-pyhd8ed1ab_0.conda#cf88f3a1c11536bc3c10c14ad00ccc42
 https://conda.anaconda.org/conda-forge/noarch/sparse-0.14.0-pyhd8ed1ab_0.conda#ee01b310177a0612554b9d20e537fdbe
 https://conda.anaconda.org/conda-forge/linux-64/cdo-2.2.0-he026af2_4.conda#6c00b0a21b3de8a149eee137e83465d3
-https://conda.anaconda.org/conda-forge/linux-64/imagemagick-7.1.1_11-pl5321hf48ede7_0.conda#25fddd05bbbe24b2ca9024c30b05bd6d
-https://conda.anaconda.org/conda-forge/noarch/iris-3.6.0-pyha770c72_0.conda#a213bee1c2fab6f99c4f66ef5f0b34f9
+https://conda.anaconda.org/conda-forge/linux-64/imagemagick-7.1.1_14-pl5321hf48ede7_0.conda#5ad1a13e7d4bc4e32c7f9c66680a7bfc
+https://conda.anaconda.org/conda-forge/noarch/iris-3.6.1-pyha770c72_0.conda#36d615b339058273520990fc78239116
 https://conda.anaconda.org/conda-forge/noarch/lime-0.2.0.1-pyhd8ed1ab_1.tar.bz2#789ce01416721a5533fb74aa4361fd13
 https://conda.anaconda.org/conda-forge/noarch/mapgenerator-1.0.7-pyhd8ed1ab_0.conda#d18db96ef2a920b0ecefe30282b0aecf
-https://conda.anaconda.org/conda-forge/noarch/nbconvert-core-7.6.0-pyhd8ed1ab_0.conda#879782bde4bbdb4c7b5d4054504a20d5
+https://conda.anaconda.org/conda-forge/noarch/nbconvert-core-7.7.2-pyhd8ed1ab_0.conda#0cda9f218d791ed71c639c1e6cc52c92
 https://conda.anaconda.org/conda-forge/noarch/prospector-1.10.2-pyhd8ed1ab_0.conda#2c536985982f7e531df8d640f554008a
 https://conda.anaconda.org/conda-forge/noarch/psy-maps-1.4.2-pyhd8ed1ab_0.tar.bz2#3ed13103dfd46f71dc870d188bd0b276
-https://conda.anaconda.org/conda-forge/linux-64/py-xgboost-1.7.4-cuda111py311h82c1ec6_2.conda#15e4e8d751e4740367631c17f460ad58
-https://conda.anaconda.org/conda-forge/linux-64/pyarrow-12.0.0-py311h39c9aba_8_cpu.conda#ecd8e4f35130ebd816f0ff806f645757
+https://conda.anaconda.org/conda-forge/linux-64/py-xgboost-1.7.4-cuda112py311h63ba870_2.conda#ee148e9b5a8bb1842fd936b65d79ef6a
+https://conda.anaconda.org/conda-forge/linux-64/pyarrow-12.0.1-py311h39c9aba_5_cpu.conda#a0d6807551f44743f84ab6c87be191c4
 https://conda.anaconda.org/conda-forge/linux-64/pydot-1.4.2-py311h38be061_3.tar.bz2#64a77de29fde80aef5013ddf5e62a564
 https://conda.anaconda.org/conda-forge/linux-64/r-askpass-1.1-r41h06615bd_3.tar.bz2#c8ec8683302ad9a2345cb31ab28e6c6b
 https://conda.anaconda.org/conda-forge/linux-64/r-bigmemory-4.6.1-r41h7525677_1.tar.bz2#6a956b57b027b49b7a9ca48031a8bbd6
@@ -602,8 +605,8 @@ https://conda.anaconda.org/conda-forge/linux-64/r-xml2-1.3.4-r41h1ad5fc0_1.conda
 https://conda.anaconda.org/conda-forge/linux-64/r-zoo-1.8_12-r41h133d619_0.conda#1d432d2eba171727afd03507faa5e2f6
 https://conda.anaconda.org/conda-forge/linux-64/statsmodels-0.14.0-py311h1f0f07a_1.conda#a1daa39fa0bfed4d91a3640c2274034a
 https://conda.anaconda.org/conda-forge/noarch/xesmf-0.7.1-pyhd8ed1ab_0.conda#3a9cc63d7bcbc8d738a0e92faf8b6c07
-https://conda.anaconda.org/conda-forge/noarch/dask-2023.6.0-pyhd8ed1ab_0.conda#187668ed10c12ad03aded53bc8e7aee6
-https://conda.anaconda.org/conda-forge/noarch/nbconvert-pandoc-7.6.0-pyhd8ed1ab_0.conda#e8172ca42f2869bb90185c9356899e81
+https://conda.anaconda.org/conda-forge/noarch/dask-2023.7.1-pyhd8ed1ab_0.conda#6cf42e7860cf46630fd5faf83386ff5d
+https://conda.anaconda.org/conda-forge/noarch/nbconvert-pandoc-7.7.2-pyhd8ed1ab_0.conda#00a7300181018085bab62b6ffa630ac4
 https://conda.anaconda.org/conda-forge/noarch/prov-2.0.0-pyhd3deb0d_0.tar.bz2#aa9b3ad140f6c0668c646f32e20ccf82
 https://conda.anaconda.org/conda-forge/linux-64/psy-reg-1.4.0-py311h38be061_3.conda#6f7871722c07922028043144e8873b37
 https://conda.anaconda.org/conda-forge/noarch/python-cdo-1.6.0-pyhd8ed1ab_0.conda#3fd1a0b063c1fbbe4b7bd5a5a7601e84
@@ -625,9 +628,9 @@ https://conda.anaconda.org/conda-forge/linux-64/r-specsverification-0.5_3-r41ha5
 https://conda.anaconda.org/conda-forge/linux-64/r-splancs-2.01_43-r41h8da6f51_1.tar.bz2#3a6aad0706541141d10e3b514467a080
 https://conda.anaconda.org/conda-forge/linux-64/r-vctrs-0.6.2-r41ha503ecb_0.conda#1f7610a1863648cab254a9f85bd29dcd
 https://conda.anaconda.org/conda-forge/noarch/seaborn-0.12.2-hd8ed1ab_0.conda#50847a47c07812f88581081c620f5160
-https://conda.anaconda.org/conda-forge/linux-64/xgboost-1.7.4-cuda111py311h569739f_2.conda#6c06902f15128dad7e0b26a3c83e6f43
+https://conda.anaconda.org/conda-forge/linux-64/xgboost-1.7.4-cuda112py311haec1985_2.conda#67811285755f2380562b3318e049a7b0
 https://conda.anaconda.org/conda-forge/noarch/iris-esmf-regrid-0.7.0-pyhd8ed1ab_0.conda#de82eb8d09362babacafe6b7e27752ac
-https://conda.anaconda.org/conda-forge/noarch/nbconvert-7.6.0-pyhd8ed1ab_0.conda#59976ee8df1c6f82c4aa94b5fd6b745e
+https://conda.anaconda.org/conda-forge/noarch/nbconvert-7.7.2-pyhd8ed1ab_0.conda#6f119203c5648ed2b0c36e4fa8b6b504
 https://conda.anaconda.org/conda-forge/noarch/r-cyclocomp-1.1.0-r41hc72bb7e_1005.tar.bz2#800e1da5bf774be48934b8865dd78d33
 https://conda.anaconda.org/conda-forge/noarch/r-gridextra-2.3-r41hc72bb7e_1004.tar.bz2#71ebed7e976df735ff3443bb88bd154f
 https://conda.anaconda.org/conda-forge/noarch/r-httr-1.4.6-r41hc72bb7e_0.conda#53dbb769c96782db54bf2d414fc9b239
@@ -637,7 +640,7 @@ https://conda.anaconda.org/conda-forge/noarch/r-pillar-1.9.0-r41hc72bb7e_0.conda
 https://conda.anaconda.org/conda-forge/noarch/r-pkgload-1.3.2-r41hc72bb7e_0.tar.bz2#e23a1a8420ab52056d86a6f9691d23fa
 https://conda.anaconda.org/conda-forge/linux-64/r-purrr-1.0.1-r41h133d619_0.conda#d7404238cac0da3c97dc08503d116a2f
 https://conda.anaconda.org/conda-forge/noarch/r-r.cache-0.16.0-r41hc72bb7e_1.tar.bz2#aef451160d655cc630d8038d934dced3
-https://conda.anaconda.org/conda-forge/label/esmvalcore_rc/noarch/esmvalcore-2.9.0rc1-pyh39db41b_0.conda#dcbff06e21971c0cdce69b77219b45f6
+https://conda.anaconda.org/conda-forge/noarch/esmvalcore-2.9.0-pyhd8ed1ab_0.conda#1f80c9bce2737630da4e71332c9d39c1
 https://conda.anaconda.org/conda-forge/noarch/nbsphinx-0.9.2-pyhd8ed1ab_0.conda#d1212b423fdd10d2da59601385561ff7
 https://conda.anaconda.org/conda-forge/noarch/r-climprojdiags-0.3.2-r41hc72bb7e_0.conda#9922b863cd10035cbb75e3c2edae64a7
 https://conda.anaconda.org/conda-forge/linux-64/r-tibble-3.2.1-r41h133d619_1.conda#3ae9b78fb1d8a44deed24a27cce33ebf

From 430ee452f56d60ebcefaaf51e3a2230d5d730be2 Mon Sep 17 00:00:00 2001
From: Valeriu Predoi <valeriu.predoi@gmail.com>
Date: Tue, 8 Aug 2023 12:32:58 +0100
Subject: [PATCH 28/93] [Github Actions] Compress all bash shell setters into
 one default option per workflow (#3315)

---
 .github/workflows/install-from-conda.yml      | 46 +++++------
 .../workflows/install-from-condalock-file.yml | 76 +++++--------------
 .github/workflows/install-from-source.yml     | 29 +++----
 .github/workflows/run-tests-monitor.yml       | 22 ++----
 .github/workflows/test-development.yml        | 14 ++--
 .github/workflows/test.yml                    | 22 ++----
 6 files changed, 67 insertions(+), 142 deletions(-)

diff --git a/.github/workflows/install-from-conda.yml b/.github/workflows/install-from-conda.yml
index 3696d34e86..55897e7fe4 100644
--- a/.github/workflows/install-from-conda.yml
+++ b/.github/workflows/install-from-conda.yml
@@ -9,6 +9,11 @@ on:
   schedule:
     - cron: '0 4 * * *'
 
+# Required shell entrypoint to have properly configured bash shell
+defaults:
+  run:
+    shell: bash -l {0}
+
 jobs:
   linux:
     runs-on: "ubuntu-latest"
@@ -24,20 +29,16 @@ jobs:
           miniforge-version: "latest"
           miniforge-variant: Mambaforge
           use-mamba: true
-      - shell: bash -l {0}
-        run: mkdir -p conda_install_linux_artifacts_python_${{ matrix.python-version }}
+      - run: mkdir -p conda_install_linux_artifacts_python_${{ matrix.python-version }}
       - name: Record versions
-        shell: bash -l {0}
         run: |
           mamba --version 2>&1 | tee conda_install_linux_artifacts_python_${{ matrix.python-version }}/conda_version.txt
           which conda 2>&1 | tee conda_install_linux_artifacts_python_${{ matrix.python-version }}/conda_path.txt
           which mamba 2>&1 | tee -a conda_install_linux_artifacts_python_${{ matrix.python-version }}/conda_path.txt
           python -V 2>&1 | tee conda_install_linux_artifacts_python_${{ matrix.python-version }}/python_version.txt
       - name: Install ESMValTool
-        shell: bash -l {0}
         run: mamba install esmvaltool 2>&1 | tee conda_install_linux_artifacts_python_${{ matrix.python-version }}/install.txt
       - name: Verify installation
-        shell: bash -l {0}
         run: |
           esmvaltool --help
           esmvaltool version 2>&1 | tee conda_install_linux_artifacts_python_${{ matrix.python-version }}/version.txt
@@ -65,31 +66,20 @@ jobs:
 #          python-version: ${{ matrix.python-version }}
 #          miniconda-version: "latest"
 #          channels: conda-forge
-#      - shell: bash -l {0}
-#        run: mkdir -p conda_install_osx_artifacts_python_${{ matrix.python-version }}
-#      - shell: bash -l {0}
-#        run: conda --version 2>&1 | tee conda_install_osx_artifacts_python_${{ matrix.python-version }}/conda_version.txt
-#      - shell: bash -l {0}
-#        run: which conda 2>&1 | tee conda_install_osx_artifacts_python_${{ matrix.python-version }}/conda_path.txt
-#      - shell: bash -l {0}
-#        run: python -V 2>&1 | tee conda_install_osx_artifacts_python_${{ matrix.python-version }}/python_version.txt
+#      - run: mkdir -p conda_install_osx_artifacts_python_${{ matrix.python-version }}
+#      - run: conda --version 2>&1 | tee conda_install_osx_artifacts_python_${{ matrix.python-version }}/conda_version.txt
+#      - run: which conda 2>&1 | tee conda_install_osx_artifacts_python_${{ matrix.python-version }}/conda_path.txt
+#      - run: python -V 2>&1 | tee conda_install_osx_artifacts_python_${{ matrix.python-version }}/python_version.txt
 #      # ncurses needs to be from conda-forge and not main channel
 #      # for now it's turned off since we're not testing R/Julia installs
-#      # - shell: bash -l {0}
-#      #   run: conda uninstall -y ncurses
-#      # - shell: bash -l {0}
-#      #   run: conda list ncurses
-#      # - shell: bash -l {0}
-#      #   run: conda install -y conda-forge::ncurses
-#      # - shell: bash -l {0}
-#      #   run: conda list ncurses
-#      - shell: bash -l {0}
-#        #run: conda install esmvaltool --no-update-deps 2>&1 | tee conda_install_osx_artifacts_python_${{ matrix.python-version }}/install.txt
-#        run: conda install esmvaltool-python esmvaltool-ncl 2>&1 | tee conda_install_osx_artifacts_python_${{ matrix.python-version }}/install.txt
-#      - shell: bash -l {0}
-#        run: esmvaltool --help
-#      - shell: bash -l {0}
-#        run: esmvaltool version 2>&1 | tee conda_install_osx_artifacts_python_${{ matrix.python-version }}/version.txt
+#      # - run: conda uninstall -y ncurses
+#      # - run: conda list ncurses
+#      # - run: conda install -y conda-forge::ncurses
+#      # - run: conda list ncurses
+#      - run: conda install esmvaltool --no-update-deps 2>&1 | tee conda_install_osx_artifacts_python_${{ matrix.python-version }}/install.txt
+#      - run: conda install esmvaltool-python esmvaltool-ncl 2>&1 | tee conda_install_osx_artifacts_python_${{ matrix.python-version }}/install.txt
+#      - run: esmvaltool --help
+#      - run: esmvaltool version 2>&1 | tee conda_install_osx_artifacts_python_${{ matrix.python-version }}/version.txt
 #      - name: Upload artifacts
 #        if: ${{ always() }}  # upload artifacts even if fail
 #        uses: actions/upload-artifact@v2
diff --git a/.github/workflows/install-from-condalock-file.yml b/.github/workflows/install-from-condalock-file.yml
index 99092069d8..a209c06f32 100644
--- a/.github/workflows/install-from-condalock-file.yml
+++ b/.github/workflows/install-from-condalock-file.yml
@@ -20,6 +20,11 @@ on:
   schedule:
     - cron: '0 0 * * *'
 
+# Required shell entrypoint to have properly configured bash shell
+defaults:
+  run:
+    shell: bash -l {0}
+
 jobs:
   linux:
     runs-on: "ubuntu-latest"
@@ -38,68 +43,21 @@ jobs:
           python-version: ${{ matrix.python-version }}
           miniconda-version: "latest"
           channels: conda-forge
-      - shell: bash -l {0}
-        run: mkdir -p source_install_linux_artifacts_python_${{ matrix.python-version }}
-      - shell: bash -l {0}
-        run: conda --version 2>&1 | tee source_install_linux_artifacts_python_${{ matrix.python-version }}/conda_version.txt
-      - shell: bash -l {0}
-        run: which python
-      - shell: bash -l {0}
-        run: python -V 2>&1 | tee source_install_linux_artifacts_python_${{ matrix.python-version }}/python_version.txt
-      - shell: bash -l {0}
-        run: conda create --name esmvaltool-fromlock --file conda-linux-64.lock
-      - shell: bash -l {0}
-        run: which python
-      - shell: bash -l {0}
-        run: pip --version
-      - shell: bash -l {0}
-        run: pip install -e .[develop]
-      - shell: bash -l {0}
-        run: esmvaltool --help
-      - shell: bash -l {0}
-        run: esmvaltool version 2>&1 | tee source_install_linux_artifacts_python_${{ matrix.python-version }}/version.txt
-      - shell: bash -l {0}
-        run: flake8
-      - shell: bash -l {0}
-        run: pytest -n 2 -m "not installation"
+      - run: mkdir -p source_install_linux_artifacts_python_${{ matrix.python-version }}
+      - run: conda --version 2>&1 | tee source_install_linux_artifacts_python_${{ matrix.python-version }}/conda_version.txt
+      - run: which python
+      - run: python -V 2>&1 | tee source_install_linux_artifacts_python_${{ matrix.python-version }}/python_version.txt
+      - run: conda create --name esmvaltool-fromlock --file conda-linux-64.lock
+      - run: which python
+      - run: pip --version
+      - run: pip install -e .[develop]
+      - run: esmvaltool --help
+      - run: esmvaltool version 2>&1 | tee source_install_linux_artifacts_python_${{ matrix.python-version }}/version.txt
+      - run: flake8
+      - run: pytest -n 2 -m "not installation"
       - name: Upload artifacts
         if: ${{ always() }}  # upload artifacts even if fail
         uses: actions/upload-artifact@v2
         with:
           name: Source_Install_Linux_python_${{ matrix.python-version }}
           path: source_install_linux_artifacts_python_${{ matrix.python-version }}
-
-#  osx:
-#    runs-on: "macos-latest"
-#    strategy:
-#      matrix:
-#        python-version: ["3.9", "3.10", "3.11"]
-#      fail-fast: false
-#    name: OSX Python ${{ matrix.python-version }}
-#    steps:
-#      - uses: actions/checkout@v2
-#      - uses: conda-incubator/setup-miniconda@v2
-#        with:
-#          activate-environment: esmvaltool
-#          environment-file: environment.yml
-#          python-version: ${{ matrix.python-version }}
-#          miniconda-version: "latest"
-#          channels: conda-forge
-#      - shell: bash -l {0}
-#        run: mkdir -p source_install_osx_artifacts_python_${{ matrix.python-version }}
-#      - shell: bash -l {0}
-#        run: conda --version 2>&1 | tee source_install_osx_artifacts_python_${{ matrix.python-version }}/conda_version.txt
-#      - shell: bash -l {0}
-#        run: python -V 2>&1 | tee source_install_osx_artifacts_python_${{ matrix.python-version }}/python_version.txt
-#      - shell: bash -l {0}
-#        run: pip install -e .[develop] 2>&1 | tee source_install_osx_artifacts_python_${{ matrix.python-version }}/install.txt
-#      - shell: bash -l {0}
-#        run: esmvaltool --help
-#      - shell: bash -l {0}
-#        run: esmvaltool version 2>&1 | tee source_install_osx_artifacts_python_${{ matrix.python-version }}/version.txt
-#      - name: Upload artifacts
-#        if: ${{ always() }}  # upload artifacts even if fail
-#        uses: actions/upload-artifact@v2
-#        with:
-#          name: Source_Install_OSX_python_${{ matrix.python-version }}
-#          path: source_install_osx_artifacts_python_${{ matrix.python-version }}
diff --git a/.github/workflows/install-from-source.yml b/.github/workflows/install-from-source.yml
index 8c86e273ac..2e24b8f049 100644
--- a/.github/workflows/install-from-source.yml
+++ b/.github/workflows/install-from-source.yml
@@ -9,6 +9,11 @@ on:
   schedule:
     - cron: '0 0 * * *'
 
+# Required shell entrypoint to have properly configured bash shell
+defaults:
+  run:
+    shell: bash -l {0}
+
 jobs:
   linux:
     runs-on: "ubuntu-latest"
@@ -29,18 +34,14 @@ jobs:
           miniforge-version: "latest"
           miniforge-variant: Mambaforge
           use-mamba: true
-      - shell: bash -l {0}
-        run: mkdir -p source_install_linux_artifacts_python_${{ matrix.python-version }}
+      - run: mkdir -p source_install_linux_artifacts_python_${{ matrix.python-version }}
       - name: Record versions
-        shell: bash -l {0}
         run: |
           mamba --version 2>&1 | tee source_install_linux_artifacts_python_${{ matrix.python-version }}/conda_version.txt
           python -V 2>&1 | tee source_install_linux_artifacts_python_${{ matrix.python-version }}/python_version.txt
       - name: Install
-        shell: bash -l {0}
         run: pip install -e .[develop] 2>&1 | tee source_install_linux_artifacts_python_${{ matrix.python-version }}/install.txt
       - name: Verify installation
-        shell: bash -l {0}
         run: |
           esmvaltool --help
           esmvaltool version 2>&1 | tee source_install_linux_artifacts_python_${{ matrix.python-version }}/version.txt
@@ -70,18 +71,12 @@ jobs:
 #          python-version: ${{ matrix.python-version }}
 #          miniconda-version: "latest"
 #          channels: conda-forge
-#      - shell: bash -l {0}
-#        run: mkdir -p source_install_osx_artifacts_python_${{ matrix.python-version }}
-#      - shell: bash -l {0}
-#        run: conda --version 2>&1 | tee source_install_osx_artifacts_python_${{ matrix.python-version }}/conda_version.txt
-#      - shell: bash -l {0}
-#        run: python -V 2>&1 | tee source_install_osx_artifacts_python_${{ matrix.python-version }}/python_version.txt
-#      - shell: bash -l {0}
-#        run: pip install -e .[develop] 2>&1 | tee source_install_osx_artifacts_python_${{ matrix.python-version }}/install.txt
-#      - shell: bash -l {0}
-#        run: esmvaltool --help
-#      - shell: bash -l {0}
-#        run: esmvaltool version 2>&1 | tee source_install_osx_artifacts_python_${{ matrix.python-version }}/version.txt
+#      - run: mkdir -p source_install_osx_artifacts_python_${{ matrix.python-version }}
+#      - run: conda --version 2>&1 | tee source_install_osx_artifacts_python_${{ matrix.python-version }}/conda_version.txt
+#      - run: python -V 2>&1 | tee source_install_osx_artifacts_python_${{ matrix.python-version }}/python_version.txt
+#      - run: pip install -e .[develop] 2>&1 | tee source_install_osx_artifacts_python_${{ matrix.python-version }}/install.txt
+#      - run: esmvaltool --help
+#      - run: esmvaltool version 2>&1 | tee source_install_osx_artifacts_python_${{ matrix.python-version }}/version.txt
 #      - name: Upload artifacts
 #        if: ${{ always() }}  # upload artifacts even if fail
 #        uses: actions/upload-artifact@v2
diff --git a/.github/workflows/run-tests-monitor.yml b/.github/workflows/run-tests-monitor.yml
index e23c7c0daf..1efe54a66a 100644
--- a/.github/workflows/run-tests-monitor.yml
+++ b/.github/workflows/run-tests-monitor.yml
@@ -12,6 +12,11 @@ on:
   schedule:
     - cron: '0 0 * * *'  # nightly
 
+# Required shell entrypoint to have properly configured bash shell
+defaults:
+  run:
+    shell: bash -l {0}
+
 jobs:
   linux:
     runs-on: "ubuntu-latest"
@@ -32,29 +37,22 @@ jobs:
           miniforge-version: "latest"
           miniforge-variant: Mambaforge
           use-mamba: true
-      - shell: bash -l {0}
-        run: mkdir -p test_linux_artifacts_python_${{ matrix.python-version }}
+      - run: mkdir -p test_linux_artifacts_python_${{ matrix.python-version }}
       - name: Record versions
-        shell: bash -l {0}
         run: |
           mamba --version 2>&1 | tee test_linux_artifacts_python_${{ matrix.python-version }}/conda_version.txt
           python -V 2>&1 | tee test_linux_artifacts_python_${{ matrix.python-version }}/python_version.txt
       - name: Install pytest-monitor
-        shell: bash -l {0}
         run: pip install pytest-monitor
       - name: Install ESMValTool
-        shell: bash -l {0}
         run: pip install -e .[develop] 2>&1 | tee test_linux_artifacts_python_${{ matrix.python-version }}/install.txt
       - name: Install Julia dependencies
-        shell: bash -l {0}
         run: esmvaltool install Julia
       - name: Run tests
-        shell: bash -l {0}
         run: >
           pytest -n 2 -m "not installation" --db ../.pymon 2>&1
           | tee test_linux_artifacts_python_${{ matrix.python-version }}/test_report.txt
       - name: Parse monitor information
-        shell: bash -l {0}
         run: python tests/parse_pymon.py
       - name: Upload artifacts
         if: ${{ always() }}  # upload artifacts even if fail
@@ -84,28 +82,22 @@ jobs:
           use-mamba: true
       # - name: Install libomp with homebrew
       #   run: brew install libomp
-      - shell: bash -l {0}
-        run: mkdir -p test_osx_artifacts_python_${{ matrix.python-version }}
+      - run: mkdir -p test_osx_artifacts_python_${{ matrix.python-version }}
       - name: Record versions
-        shell: bash -l {0}
         run: |
           mamba --version 2>&1 | tee test_osx_artifacts_python_${{ matrix.python-version }}/conda_version.txt
           python -V 2>&1 | tee test_osx_artifacts_python_${{ matrix.python-version }}/python_version.txt
       - name: Install pytest-monitor
-        shell: bash -l {0}
         run: pip install pytest-monitor
       - name: Install ESMValTool
-        shell: bash -l {0}
         run: >
           pip install -e .[develop] 2>&1
           | tee test_osx_artifacts_python_${{ matrix.python-version }}/install.txt
       - name: Run tests
-        shell: bash -l {0}
         run: >
           pytest -n 2 -m "not installation" --db ../.pymon 2>&1
           | tee test_osx_artifacts_python_${{ matrix.python-version }}/test_report.txt
       - name: Parse monitor information
-        shell: bash -l {0}
         run: python tests/parse_pymon.py
       - name: Upload artifacts
         if: ${{ always() }}  # upload artifacts even if fail
diff --git a/.github/workflows/test-development.yml b/.github/workflows/test-development.yml
index 2f115ed46e..dfede54280 100644
--- a/.github/workflows/test-development.yml
+++ b/.github/workflows/test-development.yml
@@ -15,6 +15,11 @@ on:
   schedule:
     - cron: '0 0 * * *'
 
+# Required shell entrypoint to have properly configured bash shell
+defaults:
+  run:
+    shell: bash -l {0}
+
 jobs:
   linux:
     runs-on: "ubuntu-latest"
@@ -35,31 +40,24 @@ jobs:
           miniforge-version: "latest"
           miniforge-variant: Mambaforge
           use-mamba: true
-      - shell: bash -l {0}
-        run: mkdir -p develop_test_linux_artifacts_python_${{ matrix.python-version }}
+      - run: mkdir -p develop_test_linux_artifacts_python_${{ matrix.python-version }}
       - name: Record versions
-        shell: bash -l {0}
         run: |
           mamba --version 2>&1 | tee develop_test_linux_artifacts_python_${{ matrix.python-version }}/conda_version.txt
           python -V 2>&1 | tee develop_test_linux_artifacts_python_${{ matrix.python-version }}/python_version.txt
       - name: Install ESMValTool
-        shell: bash -l {0}
         run: pip install -e .[develop] 2>&1 | tee develop_test_linux_artifacts_python_${{ matrix.python-version }}/install.txt
       - name: Install Julia dependencies
-        shell: bash -l {0}
         run: esmvaltool install Julia
       - name: Install development version of ESMValCore
-        shell: bash -l {0}
         run: |
           cd ..
           git clone https://github.com/ESMValGroup/ESMValCore.git
           cd ESMValCore
           pip install -e .[develop]
       - name: Run flake8
-        shell: bash -l {0}
         run: flake8
       - name: Run tests
-        shell: bash -l {0}
         run: pytest -n 2 -m "not installation" 2>&1 | tee develop_test_linux_artifacts_python_${{ matrix.python-version }}/test_report.txt
       - name: Upload artifacts
         if: ${{ always() }}  # upload artifacts even if fail
diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
index 9cb266eaed..4e2698454f 100644
--- a/.github/workflows/test.yml
+++ b/.github/workflows/test.yml
@@ -9,6 +9,11 @@ on:
   schedule:
     - cron: '0 0 * * *'
 
+# Required shell entrypoint to have properly configured bash shell
+defaults:
+  run:
+    shell: bash -l {0}
+
 jobs:
   linux:
     runs-on: "ubuntu-latest"
@@ -29,36 +34,28 @@ jobs:
           miniforge-version: "latest"
           miniforge-variant: Mambaforge
           use-mamba: true
-      - shell: bash -l {0}
-        run: mkdir -p test_linux_artifacts_python_${{ matrix.python-version }}
+      - run: mkdir -p test_linux_artifacts_python_${{ matrix.python-version }}
       - name: Record versions
-        shell: bash -l {0}
         run: |
           mamba --version 2>&1 | tee test_linux_artifacts_python_${{ matrix.python-version }}/conda_version.txt
           python -V 2>&1 | tee test_linux_artifacts_python_${{ matrix.python-version }}/python_version.txt
           # this is how to export variables to the GITHUB var environment
           echo "pver0=$(python -V)" >> $GITHUB_ENV
       - name: Install ESMValTool
-        shell: bash -l {0}
         run: pip install -e .[develop] 2>&1 | tee test_linux_artifacts_python_${{ matrix.python-version }}/install.txt
       - name: Install Julia dependencies
-        shell: bash -l {0}
         run: esmvaltool install Julia
       - name: Export Python minor version
-        shell: bash -l {0}
         run: echo "pver1=$(python -V)" >> $GITHUB_ENV
       - name: Exit if Python minor version changed
-        shell: bash -l {0}
         if: ${{ env.pver1 != env.pver0}}
         run: |
           echo "Python minor version changed after Julia install"
           python -V
           exit 1
       - name: Run flake8
-        shell: bash -l {0}
         run: flake8
       - name: Run tests
-        shell: bash -l {0}
         run: pytest -n 2 -m "not installation" 2>&1 | tee test_linux_artifacts_python_${{ matrix.python-version }}/test_report.txt
       - name: Upload artifacts
         if: ${{ always() }}  # upload artifacts even if fail
@@ -88,21 +85,16 @@ jobs:
           use-mamba: true
       # - name: Install libomp with homebrew
       #   run: brew install libomp
-      - shell: bash -l {0}
-        run: mkdir -p test_osx_artifacts_python_${{ matrix.python-version }}
+      - run: mkdir -p test_osx_artifacts_python_${{ matrix.python-version }}
       - name: Record versions
-        shell: bash -l {0}
         run: |
           mamba --version 2>&1 | tee test_osx_artifacts_python_${{ matrix.python-version }}/conda_version.txt
           python -V 2>&1 | tee test_osx_artifacts_python_${{ matrix.python-version }}/python_version.txt
       - name: Install ESMValTool
-        shell: bash -l {0}
         run: pip install -e .[develop] 2>&1 | tee test_osx_artifacts_python_${{ matrix.python-version }}/install.txt
       - name: Run flake8
-        shell: bash -l {0}
         run: flake8
       - name: Run tests
-        shell: bash -l {0}
         run: pytest -n 2 -m "not installation" 2>&1 | tee test_osx_artifacts_python_${{ matrix.python-version }}/test_report.txt
       - name: Upload artifacts
         if: ${{ always() }}  # upload artifacts even if fail

From 324648139fee953fc12a273b4a1e43a4d807cef8 Mon Sep 17 00:00:00 2001
From: Valeriu Predoi <valeriu.predoi@gmail.com>
Date: Tue, 8 Aug 2023 12:33:55 +0100
Subject: [PATCH 29/93] update `mamba` version in readthedocs configuration
 docs builds (#3310)

---
 .readthedocs.yaml | 8 +++++++-
 1 file changed, 7 insertions(+), 1 deletion(-)

diff --git a/.readthedocs.yaml b/.readthedocs.yaml
index 68b849dac3..07a53170b7 100644
--- a/.readthedocs.yaml
+++ b/.readthedocs.yaml
@@ -9,10 +9,16 @@ version: 2
 build:
   os: ubuntu-22.04
   tools:
-    python: "mambaforge-4.10"
+    # updated and deployed from Aug 1, 2023
+    python: "mambaforge-22.9"
   jobs:
+    pre_create_environment:
+      # update mamba just in case
+      - mamba update --yes --quiet --name=base mamba
+      - mamba --version
     post_create_environment:
       # use conda run executable wrapper to have all env variables
+      - conda run -n ${CONDA_DEFAULT_ENV} mamba --version
       - conda run -n ${CONDA_DEFAULT_ENV} pip install . --no-deps
 
 # Declare the requirements required to build your docs

From 653638d9651360006eb8d41c9d2e7c8e66bb1036 Mon Sep 17 00:00:00 2001
From: Valeriu Predoi <valeriu.predoi@gmail.com>
Date: Thu, 10 Aug 2023 09:48:06 +0100
Subject: [PATCH 30/93] add Romain Beucher to CITATION as contributor (#3318)

---
 CITATION.cff | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/CITATION.cff b/CITATION.cff
index 31404e4c7e..49226a7fda 100644
--- a/CITATION.cff
+++ b/CITATION.cff
@@ -349,6 +349,11 @@ authors:
     family-names: Winterstein
     given-names: Franziska
     orcid: "https://orcid.org/0000-0002-2406-4936"
+  -
+    affiliation: "ACCESS-NRI, Australia"
+    family-names: Beucher
+    given-names: Romain
+    orcid: "https://orcid.org/0000-0003-3891-5444"
 
 cff-version: 1.2.0
 date-released: 2023-07-06

From 6747e63b931d084df99011146487f2ebaef90832 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?R=C3=A9mi=20Kazeroni?= <remi.kazeroni@dlr.de>
Date: Fri, 11 Aug 2023 09:25:45 +0200
Subject: [PATCH 31/93] Removed recipe_carvalhais14nat from list of broken
 recipes (#3319)

---
 doc/sphinx/source/recipes/broken_recipe_list.rst | 4 ----
 1 file changed, 4 deletions(-)

diff --git a/doc/sphinx/source/recipes/broken_recipe_list.rst b/doc/sphinx/source/recipes/broken_recipe_list.rst
index 64f4437a96..18471b2382 100644
--- a/doc/sphinx/source/recipes/broken_recipe_list.rst
+++ b/doc/sphinx/source/recipes/broken_recipe_list.rst
@@ -16,10 +16,6 @@ More details can be found in the :ref:`broken recipe policy
      - Affected diagnostics
      - Problem
      - GitHub issue
-   * - :ref:`recipe_carvalhais14nat.yml <recipe_carvalhais14nat>`
-     - `global_turnover_time`
-     - ``cartopy`` issue
-     - `#3281 <https://github.com/ESMValGroup/ESMValTool/issues/3281>`_
    * - `recipe_check_obs.yml`
      - `ERA5_native6`
      - Derivation of custom variables `rlus` and `rsus`

From a8186dd04d445439ee1fac81a8b537277d085dd5 Mon Sep 17 00:00:00 2001
From: Valeriu Predoi <valeriu.predoi@gmail.com>
Date: Fri, 11 Aug 2023 11:37:31 +0100
Subject: [PATCH 32/93] Slight refactoring of diag
 `galytska23/select_variables_for_tigramite.py` for generality and portability
 (for Changelog v2.10: authors: @valeriupredoi and @egalytska) (#3298)

Co-authored-by: Evgenia Galytska <egalytska@iup.physik.uni-bremen.de>
---
 .../select_variables_for_tigramite.py         | 203 ++++++++++++------
 1 file changed, 132 insertions(+), 71 deletions(-)

diff --git a/esmvaltool/diag_scripts/galytska23/select_variables_for_tigramite.py b/esmvaltool/diag_scripts/galytska23/select_variables_for_tigramite.py
index 2ceba18b21..424f089d69 100644
--- a/esmvaltool/diag_scripts/galytska23/select_variables_for_tigramite.py
+++ b/esmvaltool/diag_scripts/galytska23/select_variables_for_tigramite.py
@@ -45,11 +45,27 @@
     save_data,
 )
 from esmvaltool.diag_scripts.shared._base import (
-    get_plot_filename,
-)
+    get_plot_filename, )
 
 logger = logging.getLogger(Path(__file__).stem)
 
+# Fixed parameters
+# list of variables to be ignored per model
+ignored_variables = {"HadISST": ["heat_flux"]}
+
+# list of variables per dataset that will be processed
+proc_vars = {
+    "ERA5": [
+        'PV', 'Arctic_temperature', 'Psl_Ural', 'Psl_Sib', 'Psl_Aleut',
+        'heat_flux'
+    ],
+    "HadISST": ['BK_sic', 'Ok_sic'],
+    "all_other_datasets": [
+        'PV', 'Arctic_temperature', 'Psl_Ural', 'Psl_Sib', 'Psl_Aleut',
+        'heat_flux', 'BK_sic', 'Ok_sic'
+    ],
+}
+
 
 def get_provenance_record(ancestor_files):
     """Create a provenance record describing the diagnostic data and plot."""
@@ -124,55 +140,68 @@ def calculate_heat_flux(list_va_ta):
     return hf_anom_zm
 
 
-def variable_cases(var, item):
+def variable_cases(var_name, var):
     """Match preprocessor name and corresponding calculations."""
-    if var == 'pv':
-        out_var = calculate_polar_vortex(item)
-    elif var == 'pre_tas':
-        out_var = calculate_arctic_tas(item)
-    elif var == 'pressure_ural':
-        out_var = calculate_slp(item)
+    if var_name == 'pv':
+        out_var = calculate_polar_vortex(var)
+    elif var_name == 'pre_tas':
+        out_var = calculate_arctic_tas(var)
+    elif var_name == 'pressure_ural':
+        out_var = calculate_slp(var)
         out_var.var_name = 'Psl_Ural'
-    elif var == 'pressure_sib':
-        out_var = calculate_slp(item)
+    elif var_name == 'pressure_sib':
+        out_var = calculate_slp(var)
         out_var.var_name = 'Psl_Sib'
-    elif var == 'pressure_aleut':
-        out_var = calculate_slp(item)
+    elif var_name == 'pressure_aleut':
+        out_var = calculate_slp(var)
         out_var.var_name = 'Psl_Aleut'
-    elif var == 'bk_ice':
-        out_var = finalize_bk_ice(item)
-    elif var == 'ok_ice':
-        out_var = finalize_ok_ice(item)
-    elif var == 'heat_flux':
-        out_var = prepare_heat_flux(item)
+    elif var_name == 'bk_ice':
+        out_var = finalize_bk_ice(var)
+    elif var_name == 'ok_ice':
+        out_var = finalize_ok_ice(var)
+    elif var_name == 'heat_flux':
+        out_var = prepare_heat_flux(var)
     else:
-        raise NotImplementedError(f"Variable '{var}' not supported")
+        raise NotImplementedError(f"Variable '{var_name}' not yet supported.")
     return out_var
 
 
-def calculate_variables(input_dict):
+def calculate_variables(dataset_dict):
     """Calculate all necessary variables."""
     logger.debug("Variables are calculated for the following datasources:%s",
-                 input_dict.keys())
-    dictionary = {}
-    for key, value in input_dict.items():
-        logger.debug("Calculating final variables for %s dataset", key)
-        dictionary.setdefault(key, {})
-        tmp_list = []
-        for item in value:
-            if item['preprocessor'] == "heat_flux":
-                tmp_list.append(variable_cases(item['preprocessor'], item))
-            else:
-                dictionary[key].setdefault(
-                    variable_cases(item['preprocessor'], item).var_name,
-                    variable_cases(item['preprocessor'], item)
-                )
-
-        if key != "HadISST":
-            # Calculate heat flux for all data sources except HadISST
+                 dataset_dict.keys())
+    processed_vars = {}
+    for dataset, variables in dataset_dict.items():
+        processed_vars[dataset] = {}
+
+        logger.debug("Calculating final variables %s for %s dataset",
+                     variables, dataset)
+
+        if dataset in ignored_variables:
+            to_ignore_vars = ignored_variables.get(dataset, None)
+            for var in variables:
+                var_name = var['preprocessor']
+                if var_name not in to_ignore_vars:
+                    new_var = variable_cases(var_name, var)
+                    new_var_name = new_var.var_name
+                    processed_vars[dataset][new_var_name] = new_var
+        else:
+            tmp_list = []
+            for var in variables:
+                var_name = var['preprocessor']
+                if var_name == "heat_flux":
+                    tmp_list.append(variable_cases(var_name, var))
+                else:
+                    new_var = variable_cases(var_name, var)
+                    new_var_name = new_var.var_name
+                    processed_vars[dataset][new_var_name] = new_var
+            if len(tmp_list) != 2:
+                raise IndexError("The preprocessor heat flux requests two \
+                                  variables in the recipe: va and ta")
             heat_flux = calculate_heat_flux(tmp_list)
-            dictionary[key].setdefault(heat_flux.var_name, heat_flux)
-    return dictionary
+            processed_vars[dataset][heat_flux.var_name] = heat_flux
+
+    return processed_vars
 
 
 def plotting_support(cube, key, **kwargs):
@@ -193,52 +222,84 @@ def plot_timeseries(dictionary, var, cfg):
     colors = plt.cm.viridis(np.linspace(0, 1, len(dictionary.keys())))
     baseplotname = f"Timeseries_{var}_anomalies"
     filename = get_plot_filename(baseplotname, cfg)
-    for i, key in enumerate(dictionary.keys()):
-        if var not in ('BK_sic', 'Ok_sic'):
-            if key == "HadISST":
+    for idx, dataset in enumerate(dictionary.keys()):
+        if var not in proc_vars["HadISST"]:
+            if dataset == "HadISST":
                 continue
-            if key != 'ERA5':
-                plotting_support(dictionary[key][var], key,
-                                 color=colors[i])
+            if dataset != 'ERA5':
+                plotting_support(dictionary[dataset][var],
+                                 dataset, color=colors[idx])
             else:
-                plotting_support(dictionary[key][var], key,
-                                 color='k', linewidth=2)
+                plotting_support(dictionary[dataset][var],
+                                 dataset,
+                                 color='k',
+                                 linewidth=2)
         else:
-            if key == "ERA5":
+            if dataset == "ERA5":
                 continue
-            if key != 'HadISST':
-                plotting_support(dictionary[key][var], key, color=colors[i])
+            if dataset != 'HadISST':
+                plotting_support(dictionary[dataset][var],
+                                 dataset, color=colors[idx])
             else:
-                plotting_support(dictionary[key][var], key, color='blue',
+                plotting_support(dictionary[dataset][var],
+                                 dataset,
+                                 color='blue',
                                  linewidth=2)
     fig.savefig(filename, bbox_inches='tight')
 
 
+def assemble_cube_list(dataset, var, special_datasets):
+    """
+    Assemble a list of processed vars cubes.
+
+    Depending on what vars are needed per dataset,
+    variables list differs per analyzed dataset. Dict holding the
+    needed variables per dataset needs updating everytime a new dataset
+    or variable gets included.
+
+    Parameters
+    ----------
+    dataset: str
+        dataset name.
+    var: dict
+        variable dictionary.
+    special_datasets: list
+        list of datasets to be treated separately,
+        with restricted variables.
+        type: list of datasets (list of strings).
+
+    Returns
+    -------
+    iris.cube.CubeList
+        list of cubes.
+    """
+    if dataset not in special_datasets:
+        cube_list = iris.cube.CubeList(
+            [var[proc_var] for proc_var in proc_vars["all_other_datasets"]])
+    else:
+        cube_list = iris.cube.CubeList(
+            [var[proc_var] for proc_var in proc_vars[dataset]])
+
+    return cube_list
+
+
 def main(cfg):
     """Calculate and save final variables into .nc files."""
+    special_datasets = ["ERA5", "HadISST"]
+
     my_files_dict = group_metadata(cfg['input_data'].values(), 'dataset')
     all_variables = calculate_variables(my_files_dict)
+
     # Check is timeseries should be plotted
-    if cfg['plot_timeseries'] is True:
+    if cfg['plot_timeseries']:
         plot_timeseries(all_variables, cfg['variable_to_plot'], cfg)
-    for key in my_files_dict:
-        logger.info("Processing final calculations in dataset %s", key)
-        prov_record = get_provenance_record([key])
-        var = all_variables[key]
-        if key == "ERA5":
-            cube_list = iris.cube.CubeList([
-                var['PV'], var['Arctic_temperature'], var['Psl_Ural'],
-                var['Psl_Sib'], var['Psl_Aleut'], var['heat_flux']])
-        elif key == "HadISST":
-            cube_list = iris.cube.CubeList([
-                var['BK_sic'], var['Ok_sic']])
-        else:
-            cube_list = iris.cube.CubeList([
-                var['PV'], var['Arctic_temperature'], var['Psl_Ural'],
-                var['Psl_Sib'], var['Psl_Aleut'], var['heat_flux'],
-                var['BK_sic'], var['Ok_sic']])
-        save_data(key, prov_record, cfg, cube_list)
-        logger.info("%s data is saved in .nc", key)
+    for dataset in my_files_dict:
+        logger.info("Processing final calculations in dataset %s", dataset)
+        prov_record = get_provenance_record([dataset])
+        var = all_variables[dataset]
+        cube_list = assemble_cube_list(dataset, var, special_datasets)
+        save_data(dataset, prov_record, cfg, cube_list)
+        logger.info("%s data is saved in .nc", dataset)
     logger.info("Done.")
 
 

From 7031ca0781d858af2f953c08465a9562f67df3a0 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Fri, 11 Aug 2023 11:38:29 +0100
Subject: [PATCH 33/93] [Condalock] Update Linux condalock file (#3321)

Co-authored-by: valeriupredoi <valeriupredoi@users.noreply.github.com>
---
 conda-linux-64.lock | 114 ++++++++++++++++++++++----------------------
 1 file changed, 57 insertions(+), 57 deletions(-)

diff --git a/conda-linux-64.lock b/conda-linux-64.lock
index 39331facf0..c7e91c6a20 100644
--- a/conda-linux-64.lock
+++ b/conda-linux-64.lock
@@ -34,7 +34,6 @@ https://conda.anaconda.org/conda-forge/linux-64/aws-c-common-0.8.23-hd590300_0.c
 https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-h7f98852_4.tar.bz2#a1fd65c7ccbf10880423d82bca54eb54
 https://conda.anaconda.org/conda-forge/linux-64/c-ares-1.19.1-hd590300_0.conda#e8c18d865be43e2fb3f7a145b6adf1f5
 https://conda.anaconda.org/conda-forge/linux-64/charls-2.4.2-h59595ed_0.conda#4336bd67920dd504cd8c6761d6a99645
-https://conda.anaconda.org/conda-forge/linux-64/cudatoolkit-11.8.0-h37601d7_11.conda#9d166760c8cfa83e2fc989928312da3d
 https://conda.anaconda.org/conda-forge/linux-64/dav1d-1.2.1-hd590300_0.conda#418c6ca5929a611cbd69204907a83995
 https://conda.anaconda.org/conda-forge/linux-64/fftw-3.3.10-nompi_hc118613_108.conda#6fa90698000b05dfe8ce6515794fe71a
 https://conda.anaconda.org/conda-forge/linux-64/freexl-1.0.6-h166bdaf_1.tar.bz2#897e772a157faf3330d72dd291486f62
@@ -84,19 +83,20 @@ https://conda.anaconda.org/conda-forge/linux-64/nccl-2.18.3.1-h12f7317_0.conda#c
 https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.4-hcb278e6_0.conda#681105bccc2a3f7f1a837d47d39c9179
 https://conda.anaconda.org/conda-forge/linux-64/nspr-4.35-h27087fc_0.conda#da0ec11a6454ae19bff5b02ed881a2b1
 https://conda.anaconda.org/conda-forge/linux-64/openlibm-0.8.1-h7f98852_0.tar.bz2#ba0c56761f2380babaa783b2a37b4d08
-https://conda.anaconda.org/conda-forge/linux-64/openssl-3.1.1-hd590300_1.conda#2e1d7b458ac8f1e3ca4e18b77add6277
+https://conda.anaconda.org/conda-forge/linux-64/openssl-3.1.2-hd590300_0.conda#e5ac5227582d6c83ccf247288c0eb095
 https://conda.anaconda.org/conda-forge/linux-64/p7zip-16.02-h9c3ff4c_1001.tar.bz2#941066943c0cac69d5aa52189451aa5f
 https://conda.anaconda.org/conda-forge/linux-64/pixman-0.40.0-h36c2ea0_0.tar.bz2#660e72c82f2e75a6b3fe6a6e75c79f19
 https://conda.anaconda.org/conda-forge/linux-64/pkg-config-0.29.2-h36c2ea0_1008.tar.bz2#fbef41ff6a4c8140c30057466a1cdd47
 https://conda.anaconda.org/conda-forge/linux-64/pthread-stubs-0.4-h36c2ea0_1001.tar.bz2#22dad4df6e8630e8dff2428f6f6a7036
 https://conda.anaconda.org/conda-forge/linux-64/rdma-core-28.9-h59595ed_1.conda#aeffb7c06b5f65e55e6c637408dc4100
 https://conda.anaconda.org/conda-forge/linux-64/re2-2023.03.02-h8c504da_0.conda#206f8fa808748f6e90599c3368a1114e
+https://conda.anaconda.org/conda-forge/linux-64/rocm-smi-5.6.0-h59595ed_1.conda#2980fb3b7777f495dacd46d5cc5d74bb
 https://conda.anaconda.org/conda-forge/linux-64/sed-4.8-he412f7d_0.tar.bz2#7362f0042e95681f5d371c46c83ebd08
 https://conda.anaconda.org/conda-forge/linux-64/snappy-1.1.10-h9fff704_0.conda#e6d228cd0bb74a51dd18f5bfce0b4115
 https://conda.anaconda.org/conda-forge/linux-64/tzcode-2023c-h0b41bf4_0.conda#0c0533894f21c3d35697cb8378d390e2
 https://conda.anaconda.org/conda-forge/linux-64/xorg-inputproto-2.3.2-h7f98852_1002.tar.bz2#bcd1b3396ec6960cbc1d2855a9e60b2b
 https://conda.anaconda.org/conda-forge/linux-64/xorg-kbproto-1.0.7-h7f98852_1002.tar.bz2#4b230e8381279d76131116660f5a241a
-https://conda.anaconda.org/conda-forge/linux-64/xorg-libice-1.0.10-h7f98852_0.tar.bz2#d6b0b50b49eccfe0be0373be628be0f3
+https://conda.anaconda.org/conda-forge/linux-64/xorg-libice-1.1.1-hd590300_0.conda#b462a33c0be1421532f28bfe8f4a7514
 https://conda.anaconda.org/conda-forge/linux-64/xorg-libxau-1.0.11-hd590300_0.conda#2c80dc38fface310c9bd81b17037fee5
 https://conda.anaconda.org/conda-forge/linux-64/xorg-libxdmcp-1.1.3-h7f98852_0.tar.bz2#be93aabceefa2fac576e971aef407908
 https://conda.anaconda.org/conda-forge/linux-64/xorg-makedepend-1.0.8-h59595ed_0.conda#eb9b80b3efdb29ad359dc0438e6755fa
@@ -122,7 +122,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libbrotlidec-1.0.9-h166bdaf_9.co
 https://conda.anaconda.org/conda-forge/linux-64/libbrotlienc-1.0.9-h166bdaf_9.conda#1f0a03af852a9659ed2bf08f2f1704fd
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 https://conda.anaconda.org/conda-forge/linux-64/libevent-2.1.12-hf998b51_1.conda#a1cfcc585f0c42bf8d5546bb1dfb668d
-https://conda.anaconda.org/conda-forge/linux-64/libllvm14-14.0.6-hcd5def8_3.conda#5c159aa79cab06c55aabcecdd9117f31
+https://conda.anaconda.org/conda-forge/linux-64/libllvm14-14.0.6-hcd5def8_4.conda#73301c133ded2bf71906aa2104edae8b
 https://conda.anaconda.org/conda-forge/linux-64/libnghttp2-1.52.0-h61bc06f_0.conda#613955a50485812985c059e7b269f42e
 https://conda.anaconda.org/conda-forge/linux-64/libpng-1.6.39-h753d276_0.conda#e1c890aebdebbfbf87e2c917187b4416
 https://conda.anaconda.org/conda-forge/linux-64/libprotobuf-4.23.3-hd1fb520_0.conda#c8da7f04073ed0fabcb60885a4c1a722
@@ -130,8 +130,8 @@ https://conda.anaconda.org/conda-forge/linux-64/librttopo-1.1.0-h0d5128d_13.cond
 https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.42.0-h2797004_0.conda#fdaae20a1cf7cd62130a0973190a31b7
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-https://conda.anaconda.org/conda-forge/linux-64/libxgboost-1.7.4-cuda112h1eddcb4_2.conda#37137a5e7d819fc19c52b0087e9be5db
-https://conda.anaconda.org/conda-forge/linux-64/libxml2-2.11.4-h0d562d8_0.conda#e46fad17d5fb57316b956f88dca765e4
+https://conda.anaconda.org/conda-forge/linux-64/libxgboost-1.7.6-cuda112h7a395e5_0.conda#8f5e1a6eb68812ed72cb7992f1db537d
+https://conda.anaconda.org/conda-forge/linux-64/libxml2-2.11.5-h0d562d8_0.conda#558ab736404275d7df61c473c1af35aa
 https://conda.anaconda.org/conda-forge/linux-64/libzip-1.9.2-hc929e4a_1.tar.bz2#5b122b50e738c4be5c3f2899f010d7cf
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@@ -142,7 +142,7 @@ https://conda.anaconda.org/conda-forge/linux-64/s2n-1.3.46-h06160fa_0.conda#413d
 https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.12-h27826a3_0.tar.bz2#5b8c42eb62e9fc961af70bdd6a26e168
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-https://conda.anaconda.org/conda-forge/linux-64/xorg-libsm-1.2.3-hd9c2040_1000.tar.bz2#9e856f78d5c80d5a78f61e72d1d473a3
+https://conda.anaconda.org/conda-forge/linux-64/xorg-libsm-1.2.4-h7391055_0.conda#93ee23f12bc2e684548181256edd2cf6
 https://conda.anaconda.org/conda-forge/linux-64/zeromq-4.3.4-h9c3ff4c_1.tar.bz2#21743a8d2ea0c8cfbbf8fe489b0347df
 https://conda.anaconda.org/conda-forge/linux-64/zlib-1.2.13-hd590300_5.conda#68c34ec6149623be41a1933ab996a209
 https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.2-hfc55251_7.conda#32ae18eb2a687912fc9e92a501c0a11b
@@ -163,7 +163,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libgit2-1.5.1-h1f77430_0.conda#1
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-https://conda.anaconda.org/conda-forge/linux-64/libhwloc-2.9.1-nocuda_h7313eea_6.conda#cd72a08ef4e84dea4c67edde33eb3191
+https://conda.anaconda.org/conda-forge/linux-64/libhwloc-2.9.2-nocuda_h7313eea_1008.conda#3b4cad0666b5a8ec5eaf2de0ef41d6c9
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@@ -250,7 +250,7 @@ https://conda.anaconda.org/conda-forge/linux-64/numpy-1.24.4-py311h64a7726_0.con
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-https://conda.anaconda.org/conda-forge/noarch/pathspec-0.11.1-pyhd8ed1ab_0.conda#dbb80d1e8dc2dba5c8b106dc0768ad45
+https://conda.anaconda.org/conda-forge/noarch/pathspec-0.11.2-pyhd8ed1ab_0.conda#e41debb259e68490e3ab81e46b639ab6
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@@ -258,7 +258,7 @@ https://conda.anaconda.org/conda-forge/noarch/py-1.11.0-pyh6c4a22f_0.tar.bz2#b46
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-https://conda.anaconda.org/conda-forge/noarch/pygments-2.15.1-pyhd8ed1ab_0.conda#d316679235612869eba305aa7d41d9bf
+https://conda.anaconda.org/conda-forge/noarch/pygments-2.16.1-pyhd8ed1ab_0.conda#40e5cb18165466773619e5c963f00a7b
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@@ -267,7 +267,7 @@ https://conda.anaconda.org/conda-forge/noarch/python-tzdata-2023.3-pyhd8ed1ab_0.
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+https://conda.anaconda.org/conda-forge/linux-64/pyzmq-25.1.1-py311h75c88c4_0.conda#af6d43afe0d179ac83b7e0c16b2caaad
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From fd2bee7de8c9933ef4ed86cc162d87849847ff95 Mon Sep 17 00:00:00 2001
From: Lisa Bock <lisa.bock@dlr.de>
Date: Mon, 14 Aug 2023 16:54:42 +0200
Subject: [PATCH 34/93] Cmorizer for NOAA-CIRES-20CR v3 reanalysis (clt, clwvi,
 hus, prw, rlut, rlutcs, rsut, rsutcs) (#3137)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Co-authored-by: Rémi Kazeroni <remi.kazeroni@dlr.de>
---
 doc/sphinx/source/input.rst                   |  4 +-
 ...-CIRES-20CR.yml => NOAA-CIRES-20CR-V2.yml} |  4 +-
 .../data/cmor_config/NOAA-CIRES-20CR-V3.yml   | 56 +++++++++++++++++++
 esmvaltool/cmorizers/data/datasets.yml        | 17 +++++-
 ...aa_cires_20cr.py => noaa_cires_20cr_v2.py} |  2 +-
 .../datasets/noaa_cires_20cr_v3.py            | 53 ++++++++++++++++++
 ...aa_cires_20cr.py => noaa_cires_20cr_v2.py} |  2 +-
 .../formatters/datasets/noaa_cires_20cr_v3.py | 32 +++++++++++
 .../recipes/examples/recipe_check_obs.yml     | 25 +++++++--
 ...-20cr.bibtex => noaa-cires-20cr-v2.bibtex} | 10 ++--
 .../references/noaa-cires-20cr-v3.bibtex      | 11 ++++
 11 files changed, 202 insertions(+), 14 deletions(-)
 rename esmvaltool/cmorizers/data/cmor_config/{NOAA-CIRES-20CR.yml => NOAA-CIRES-20CR-V2.yml} (88%)
 create mode 100644 esmvaltool/cmorizers/data/cmor_config/NOAA-CIRES-20CR-V3.yml
 rename esmvaltool/cmorizers/data/downloaders/datasets/{noaa_cires_20cr.py => noaa_cires_20cr_v2.py} (97%)
 create mode 100644 esmvaltool/cmorizers/data/downloaders/datasets/noaa_cires_20cr_v3.py
 rename esmvaltool/cmorizers/data/formatters/datasets/{noaa_cires_20cr.py => noaa_cires_20cr_v2.py} (92%)
 create mode 100644 esmvaltool/cmorizers/data/formatters/datasets/noaa_cires_20cr_v3.py
 rename esmvaltool/references/{noaa-cires-20cr.bibtex => noaa-cires-20cr-v2.bibtex} (62%)
 create mode 100644 esmvaltool/references/noaa-cires-20cr-v3.bibtex

diff --git a/doc/sphinx/source/input.rst b/doc/sphinx/source/input.rst
index 8bd0d5afd0..c453a0569e 100644
--- a/doc/sphinx/source/input.rst
+++ b/doc/sphinx/source/input.rst
@@ -380,7 +380,9 @@ A list of the datasets for which a CMORizers is available is provided in the fol
 +------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+
 | NIWA-BS                      | toz, tozStderr (Amon)                                                                                |   3  | NCL             |
 +------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+
-| NOAA-CIRES-20CR              | clt, clwvi, hus, prw, rlut, rsut (Amon)                                                              |   2  | Python          |
+| NOAA-CIRES-20CR-V2           | clt, clwvi, hus, prw, rlut, rsut (Amon)                                                              |   2  | Python          |
++------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+
+| NOAA-CIRES-20CR-V3           | clt, clwvi, hus, prw, rlut, rlutcs, rsut, rsutcs (Amon)                                              |   2  | Python          |
 +------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+
 | NOAAGlobalTemp               | tasa (Amon)                                                                                          |   2  | Python          |
 +------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+
diff --git a/esmvaltool/cmorizers/data/cmor_config/NOAA-CIRES-20CR.yml b/esmvaltool/cmorizers/data/cmor_config/NOAA-CIRES-20CR-V2.yml
similarity index 88%
rename from esmvaltool/cmorizers/data/cmor_config/NOAA-CIRES-20CR.yml
rename to esmvaltool/cmorizers/data/cmor_config/NOAA-CIRES-20CR-V2.yml
index cb3ccb38a8..7591e99257 100644
--- a/esmvaltool/cmorizers/data/cmor_config/NOAA-CIRES-20CR.yml
+++ b/esmvaltool/cmorizers/data/cmor_config/NOAA-CIRES-20CR-V2.yml
@@ -1,13 +1,13 @@
 ---
 # Global attributes of NetCDF file
 attributes:
-  dataset_id: NOAA-CIRES-20CR
+  dataset_id: NOAA-CIRES-20CR-V2
   project_id: OBS6
   tier: 2
   version: 'v2'
   modeling_realm: reanaly
   source: 'https://psl.noaa.gov/data/gridded/data.20thC_ReanV2.html'
-  reference: 'noaa-cires-20cr'
+  reference: 'noaa-cires-20cr-v2'
   comment: |
     ''
 
diff --git a/esmvaltool/cmorizers/data/cmor_config/NOAA-CIRES-20CR-V3.yml b/esmvaltool/cmorizers/data/cmor_config/NOAA-CIRES-20CR-V3.yml
new file mode 100644
index 0000000000..d16d5265e0
--- /dev/null
+++ b/esmvaltool/cmorizers/data/cmor_config/NOAA-CIRES-20CR-V3.yml
@@ -0,0 +1,56 @@
+---
+# Global attributes of NetCDF file
+attributes:
+  dataset_id: NOAA-CIRES-20CR-V3
+  project_id: OBS6
+  tier: 2
+  version: 'v3'
+  modeling_realm: reanaly
+  source: 'https://psl.noaa.gov/data/gridded/data.20thC_ReanV3.html'
+  reference: 'noaa-cires-20cr-v3'
+  comment: |
+    ''
+
+# Variables to CMORize
+variables:
+  # monthly frequency
+  clt_month:
+    short_name: clt
+    mip: Amon
+    raw: tcdc
+    file: 'tcdc.eatm.mon.mean.nc'
+  clwvi_month:
+    short_name: clwvi
+    mip: Amon
+    raw: cldwtr
+    file: 'cldwtr.eatm.mon.mean.nc'
+  prw_month:
+    short_name: prw
+    mip: Amon
+    raw: pr_wtr
+    file: 'pr_wtr.eatm.mon.mean.nc'
+  hus_month:
+    short_name: hus
+    mip: Amon
+    raw: shum
+    file: 'shum.mon.mean.nc'
+  rlut_month:
+    short_name: rlut
+    mip: Amon
+    raw: ulwrf
+    file: 'ulwrf.ntat.mon.mean.nc'
+  rsut_month:
+    short_name: rsut
+    mip: Amon
+    raw: uswrf
+    file: 'uswrf.ntat.mon.mean.nc'
+  rlutcs_month:
+    short_name: rlutcs
+    mip: Amon
+    raw: csulf
+    file: 'csulf.ntat.mon.mean.nc'
+  rsutcs_month:
+    short_name: rsutcs
+    mip: Amon
+    raw: csusf
+    file: 'csusf.ntat.mon.mean.nc'
diff --git a/esmvaltool/cmorizers/data/datasets.yml b/esmvaltool/cmorizers/data/datasets.yml
index 61b56e7f8f..d40de3988c 100644
--- a/esmvaltool/cmorizers/data/datasets.yml
+++ b/esmvaltool/cmorizers/data/datasets.yml
@@ -985,7 +985,7 @@ datasets:
       https://nsidc.org/data/NSIDC-0116
       Login required for download, and also requires citation only to use
 
-  NOAA-CIRES-20CR:
+  NOAA-CIRES-20CR-V2:
     tier: 2
     source: ftp.cdc.noaa.gov/Projects/20thC_ReanV2/Monthlies/
     last_access: 2022-11-17
@@ -998,6 +998,21 @@ datasets:
         gaussian/monolevel/ulwrf.ntat.mon.mean.nc
         gaussian/monolevel/uswrf.ntat.mon.mean.nc
 
+  NOAA-CIRES-20CR-V3:
+    tier: 2
+    source: ftp.cdc.noaa.gov/Projects/20thC_ReanV3/Monthlies/
+    last_access: 2023-03-27
+    info: |
+      Download the following files:
+        miscSI-MO/cldwtr.eatm.mon.mean.nc
+        miscSI-MO/pr_wtr.eatm.mon.mean.nc
+        prsSI-MO/shum.mon.mean.nc
+        miscMO/tcdc.eatm.mon.mean.nc
+        ntatFlxSI-MO/ulwrf.ntat.mon.mean.nc  
+        ntatFlxSI-MO/uswrf.ntat.mon.mean.nc
+        ntatFlxSI-MO/csulf.ntat.mon.mean.nc
+        ntatFlxSI-MO/csusf.ntat.mon.mean.nc
+
   NOAAGlobalTemp:
     tier: 2
     source: https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v5/access/
diff --git a/esmvaltool/cmorizers/data/downloaders/datasets/noaa_cires_20cr.py b/esmvaltool/cmorizers/data/downloaders/datasets/noaa_cires_20cr_v2.py
similarity index 97%
rename from esmvaltool/cmorizers/data/downloaders/datasets/noaa_cires_20cr.py
rename to esmvaltool/cmorizers/data/downloaders/datasets/noaa_cires_20cr_v2.py
index 836cfe8391..fb2d733f06 100644
--- a/esmvaltool/cmorizers/data/downloaders/datasets/noaa_cires_20cr.py
+++ b/esmvaltool/cmorizers/data/downloaders/datasets/noaa_cires_20cr_v2.py
@@ -1,4 +1,4 @@
-"""Script to download NOAA-CIRES-20CR."""
+"""Script to download NOAA-CIRES-20CR-V2."""
 import logging
 
 from esmvaltool.cmorizers.data.downloaders.ftp import FTPDownloader
diff --git a/esmvaltool/cmorizers/data/downloaders/datasets/noaa_cires_20cr_v3.py b/esmvaltool/cmorizers/data/downloaders/datasets/noaa_cires_20cr_v3.py
new file mode 100644
index 0000000000..67f1a38f33
--- /dev/null
+++ b/esmvaltool/cmorizers/data/downloaders/datasets/noaa_cires_20cr_v3.py
@@ -0,0 +1,53 @@
+"""Script to download NOAA-CIRES-20CR-V3."""
+import logging
+
+from esmvaltool.cmorizers.data.downloaders.ftp import FTPDownloader
+
+logger = logging.getLogger(__name__)
+
+
+def download_dataset(config, dataset, dataset_info, start_date, end_date,
+                     overwrite):
+    """Download dataset.
+
+    Parameters
+    ----------
+    config : dict
+        ESMValTool's user configuration
+    dataset : str
+        Name of the dataset
+    dataset_info : dict
+         Dataset information from the datasets.yml file
+    start_date : datetime
+        Start of the interval to download
+    end_date : datetime
+        End of the interval to download
+    overwrite : bool
+        Overwrite already downloaded files
+    """
+    downloader = FTPDownloader(
+        config=config,
+        server='ftp.cdc.noaa.gov',
+        dataset=dataset,
+        dataset_info=dataset_info,
+        overwrite=overwrite,
+    )
+    downloader.connect()
+
+    downloader.set_cwd("Datasets/20thC_ReanV3/Monthlies/")
+    downloader.download_file("miscSI-MO/cldwtr.eatm.mon.mean.nc",
+                             sub_folder='surface')
+    downloader.download_file("miscSI-MO/pr_wtr.eatm.mon.mean.nc",
+                             sub_folder='surface')
+    downloader.download_file("prsSI-MO/shum.mon.mean.nc",
+                             sub_folder='pressure')
+    downloader.download_file("miscMO/tcdc.eatm.mon.mean.nc",
+                             sub_folder='surface')
+    downloader.download_file("ntatFlxSI-MO/ulwrf.ntat.mon.mean.nc",
+                             sub_folder='surface')
+    downloader.download_file("ntatFlxSI-MO/uswrf.ntat.mon.mean.nc",
+                             sub_folder='surface')
+    downloader.download_file("ntatFlxSI-MO/csulf.ntat.mon.mean.nc",
+                             sub_folder='surface')
+    downloader.download_file("ntatFlxSI-MO/csusf.ntat.mon.mean.nc",
+                             sub_folder='surface')
diff --git a/esmvaltool/cmorizers/data/formatters/datasets/noaa_cires_20cr.py b/esmvaltool/cmorizers/data/formatters/datasets/noaa_cires_20cr_v2.py
similarity index 92%
rename from esmvaltool/cmorizers/data/formatters/datasets/noaa_cires_20cr.py
rename to esmvaltool/cmorizers/data/formatters/datasets/noaa_cires_20cr_v2.py
index cdc5efbd40..3744cdce67 100644
--- a/esmvaltool/cmorizers/data/formatters/datasets/noaa_cires_20cr.py
+++ b/esmvaltool/cmorizers/data/formatters/datasets/noaa_cires_20cr_v2.py
@@ -1,4 +1,4 @@
-"""ESMValTool CMORizer for NOAA-CIRES-20CR data.
+"""ESMValTool CMORizer for NOAA-CIRES-20CR-V2 data.
 
 Tier
     Tier 2: other freely-available dataset.
diff --git a/esmvaltool/cmorizers/data/formatters/datasets/noaa_cires_20cr_v3.py b/esmvaltool/cmorizers/data/formatters/datasets/noaa_cires_20cr_v3.py
new file mode 100644
index 0000000000..9405473931
--- /dev/null
+++ b/esmvaltool/cmorizers/data/formatters/datasets/noaa_cires_20cr_v3.py
@@ -0,0 +1,32 @@
+"""ESMValTool CMORizer for NOAA-CIRES-20CR-V3 data.
+
+Tier
+    Tier 2: other freely-available dataset.
+
+Source
+    https://psl.noaa.gov/data/gridded/data.ncep.reanalysis2.html
+
+Last access
+    20230327
+
+Download and processing instructions
+    To facilitate the download, the links to the ftp server are provided.
+
+    ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV3/Monthlies/
+
+        pr_wtr.eatm.mon.mean.nc
+        cldwtr.eatm.mon.mean.nc
+        tcdc.eatm.mon.mean.nc
+        ulwrf.ntat.mon.mean.nc
+        uswrf.ntat.mon.mean.nc
+        csulf.ntat.mon.mean.nc
+        csusf.ntat.mon.mean.nc
+        shum.mon.mean.nc
+
+Caveats
+
+"""
+from .ncep_ncar_r1 import cmorization
+
+# The following line makes it clear that the above import is not an error
+cmorization
diff --git a/esmvaltool/recipes/examples/recipe_check_obs.yml b/esmvaltool/recipes/examples/recipe_check_obs.yml
index 1bccda03b1..83ccc55607 100644
--- a/esmvaltool/recipes/examples/recipe_check_obs.yml
+++ b/esmvaltool/recipes/examples/recipe_check_obs.yml
@@ -632,21 +632,38 @@ diagnostics:
     scripts: null
 
 
-  NOAA-CIRES-20CR:
-    description: NOAA-CIRES-20CR check
+  NOAA-CIRES-20CR-V2:
+    description: NOAA-CIRES-20CR-V2 check
     variables:
       clt:
       clwvi:
       hus:
       prw:
-      rsut:
       rlut:
+      rsut:
     additional_datasets:
-      - {dataset: NOAA-CIRES-20CR, project: OBS6, mip: Amon, tier: 2,
+      - {dataset: NOAA-CIRES-20CR-V2, project: OBS6, mip: Amon, tier: 2,
          type: reanaly, version: v2, start_year: 1871, end_year: 2012}
     scripts: null
 
 
+  NOAA-CIRES-20CR-V3:
+    description: NOAA-CIRES-20CR-V3 check
+    variables:
+      clt:
+      clwvi:
+      hus:
+      prw:
+      rlut:
+      rlutcs:
+      rsut:
+      rsutcs:
+    additional_datasets:
+      - {dataset: NOAA-CIRES-20CR-V3, project: OBS6, mip: Amon, tier: 2,
+         type: reanaly, version: v3, start_year: 1836, end_year: 2015}
+    scripts: null
+
+
   NOAAGlobalTemp:
     description: NOAAGlobalTemp check
     variables:
diff --git a/esmvaltool/references/noaa-cires-20cr.bibtex b/esmvaltool/references/noaa-cires-20cr-v2.bibtex
similarity index 62%
rename from esmvaltool/references/noaa-cires-20cr.bibtex
rename to esmvaltool/references/noaa-cires-20cr-v2.bibtex
index 54d67ea7f3..79314b1d4b 100644
--- a/esmvaltool/references/noaa-cires-20cr.bibtex
+++ b/esmvaltool/references/noaa-cires-20cr-v2.bibtex
@@ -1,9 +1,11 @@
-@article{noaa-cire-20cr,
+@article{noaa-cires-20cr-v2,
 	doi = {10.1002/qj.776},
 	url = {https://doi.org/10.1002/qj.776},
-	publisher = {Royal Meteorological Society},
-	author = {Compo, G.P., Whitaker, J.S., Sardeshmukh, P.D., Matsui, N., Allan, R.J., Yin, X., Gleason, B.E., Vose, R.S., Rutledge, G., Bessemoulin, P., Brönnimann, S., Brunet, M., Crouthamel, R.I., Grant, A.N., Groisman, P.Y., Jones, P.D., Kruk, M.C., Kruger, A.C., Marshall, G.J., Maugeri, M., Mok, H.Y., Nordli, Ø., Ross, T.F., Trigo, R.M., Wang, X.L., Woodruff, S.D. and Worley, S.J.},
+	author = {Compo, G.P., Whitaker, J.S., Sardeshmukh, P.D., Matsui, N., Allan, R.J., Yin, X., Gleason, B.E., Vose, R.S., Rutledge, G., Bessemoulin, P., Brönnimann, S., Brunet, M., Crouthamel, R.I., Grant, A.N., Groisman, P.Y., Jones, P.D., Kruk, M.C., Kruger, A.C., Marshall, G.J., Maugeri, M., Mok, H.Y., Nordli, O., Ross, T.F., Trigo, R.M., Wang, X.L., Woodruff, S.D. and Worley, S.J.},
 	title = {The Twentieth Century Reanalysis Project},
-    year = {2011}
+        year = {2011},
 	journal = {Quarterly J. Roy. Meteorol. Soc.}
+        volume = {137},
+        number = {654},
+        pages = {1-28},
 }
diff --git a/esmvaltool/references/noaa-cires-20cr-v3.bibtex b/esmvaltool/references/noaa-cires-20cr-v3.bibtex
new file mode 100644
index 0000000000..d1bf482e9d
--- /dev/null
+++ b/esmvaltool/references/noaa-cires-20cr-v3.bibtex
@@ -0,0 +1,11 @@
+@article{noaa-cires-20cr-v3,
+	journal = {Quarterly J. Roy. Meteorol. Soc.}
+        author = {Slivinski, Laura C. and Compo, Gilbert P. and Whitaker, Jeffrey S. and Sardeshmukh, Prashant D. and Giese, Benjamin S. and McColl, Chesley and Allan, Rob and Yin, Xungang and Vose, Russell and Titchner, Holly and Kennedy, John and Spencer, Lawrence J. and Ashcroft, Linden and Brönnimann, Stefan and Brunet, Manola and Camuffo, Dario and Cornes, Richard and Cram, Thomas A. and Crouthamel, Richard and Domínguez-Castro, Fernando and Freeman, J. Eric and Gergis, Joëlle and Hawkins, Ed and Jones, Philip D. and Jourdain, Sylvie and Kaplan, Alexey and Kubota, Hisayuki and Blancq, Frank Le and Lee, Tsz-Cheung and Lorrey, Andrew and Luterbacher, Jürg and Maugeri, Maurizio and Mock, Cary J. and Moore, G.W. Kent and Przybylak, Rajmund and Pudmenzky, Christa and Reason, Chris and Slonosky, Victoria C. and Smith, Catherine A. and Tinz, Birger and Trewin, Blair and Valente, Maria Antónia and Wang, Xiaolan L. and Wilkinson, Clive and Wood, Kevin and Wyszynski, Przemysxslaw},
+        title = {Towards a more reliable historical reanalysis: Improvements for version 3 of the Twentieth Century Reanalysis system},
+        volume = {145},
+        number = {724},
+        pages = {2876-2908},
+        doi = {https://doi.org/10.1002/qj.3598},
+        url = {https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/qj.3598},
+        year = {2019}
+}

From d0624505fb2b063adfddb13b7538dafc1347d963 Mon Sep 17 00:00:00 2001
From: Manuel Schlund <32543114+schlunma@users.noreply.github.com>
Date: Fri, 18 Aug 2023 08:54:19 +0200
Subject: [PATCH 35/93] Fixed provenance tracking for NCL multipanel PNGs
 (#3332)

Co-authored-by: Axel Lauer <axel.lauer@dlr.de>
---
 esmvaltool/diag_scripts/clouds/clouds.ncl     | 19 ----------
 .../diag_scripts/clouds/clouds_dyn_matrix.ncl |  9 -----
 .../clouds/clouds_interannual.ncl             |  8 -----
 .../clouds/clouds_lifrac_scatter.ncl          | 15 --------
 esmvaltool/diag_scripts/clouds/clouds_pdf.ncl |  8 -----
 .../diag_scripts/clouds/clouds_scatter.ncl    |  9 -----
 .../clouds/clouds_seasonal_cycle.ncl          | 10 ------
 .../diag_scripts/clouds/clouds_zonal.ncl      | 17 ---------
 esmvaltool/interface_scripts/logging.ncl      | 35 +++++++++++++++++--
 9 files changed, 32 insertions(+), 98 deletions(-)

diff --git a/esmvaltool/diag_scripts/clouds/clouds.ncl b/esmvaltool/diag_scripts/clouds/clouds.ncl
index 928d7cc96d..c05c091cf4 100644
--- a/esmvaltool/diag_scripts/clouds/clouds.ncl
+++ b/esmvaltool/diag_scripts/clouds/clouds.ncl
@@ -688,7 +688,6 @@ begin
     ; function in aux_plotting.ncl
 
     if (ii.eq.0) then
-      nframe = 0
       ndframe = 0
       ; note: an array of workspaces (i.e. wks(numseas)) does not work as
       ;       attributes cannot be assigned to each array element
@@ -768,8 +767,6 @@ begin
       maps(imod, 0) = gsn_csm_contour_map(wks0, data1, res)
     end if
 
-    nframe = nframe + 1
-
     ; mandatory netcdf output
 
     data1@var = var0 + "_mean_" + names(imod)
@@ -1310,19 +1307,10 @@ begin
     end if
   end if  ; if embracesetup
 
-  nframe = nframe + 1
-
   do is = 0, numseas - 1
     log_info("Wrote " + outfile(is))
   end do
 
-  do is = 0, numseas - 1
-    suffix = get_file_suffix(outfile(is), 0)
-    if (suffix .eq. ".png") then
-      outfile(is) = suffix@fBase + "." + sprinti("%0.6i", nframe) + suffix
-    end if
-  end do
-
   ; ------------------------------------------------------------------------
   ; write provenance to netcdf output and plot file(s) (mean)
   ; ------------------------------------------------------------------------
@@ -1482,13 +1470,6 @@ begin
       end if
     end if  ; end if embracesetup
 
-    do is = 0, numseas - 1
-      suffix = get_file_suffix(outfile_d(is), 0)
-      if (suffix .eq. ".png") then
-        outfile_d(is) = suffix@fBase + "." + sprinti("%0.6i", ndframe) + suffix
-      end if
-    end do
-
     do is = 0, numseas - 1
       log_info(" Wrote " + outfile(is))
 
diff --git a/esmvaltool/diag_scripts/clouds/clouds_dyn_matrix.ncl b/esmvaltool/diag_scripts/clouds/clouds_dyn_matrix.ncl
index 9fcfadebbb..c18da6fe23 100644
--- a/esmvaltool/diag_scripts/clouds/clouds_dyn_matrix.ncl
+++ b/esmvaltool/diag_scripts/clouds/clouds_dyn_matrix.ncl
@@ -681,8 +681,6 @@ begin
   xyres2@tmXTLabelsOn = True
   xyres2@tmXBLabelsOn = False
 
-  nframe = 0
-
   do ii = 0, nplots - 1
     if (ii .lt. dim_MOD) then
       plotdata = result(ii, :, :)
@@ -775,8 +773,6 @@ begin
 
     delete(plotdata)
     delete(countdata)
-
-    nframe = nframe + 1
   end do
 
 ;  pres                      = True    ; needed to override
@@ -799,11 +795,6 @@ begin
   log_info("Wrote " + doutfile)
   log_info("Wrote " + coutfile)
 
-  suffix = get_file_suffix(outfile, 0)
-  if (suffix .eq. ".png") then
-    outfile = suffix@fBase + "." + sprinti("%0.6i", nframe) + suffix
-  end if
-
   ; ==========================================================================
 
   ; ----------------------------------------------------------------------
diff --git a/esmvaltool/diag_scripts/clouds/clouds_interannual.ncl b/esmvaltool/diag_scripts/clouds/clouds_interannual.ncl
index e27984a822..a3e318c556 100644
--- a/esmvaltool/diag_scripts/clouds/clouds_interannual.ncl
+++ b/esmvaltool/diag_scripts/clouds/clouds_interannual.ncl
@@ -445,11 +445,9 @@ begin
     if (ii.eq.0) then
       wks = get_wks("dummy_for_wks", DIAG_SCRIPT, "clouds_interannual_" \
                     + var0 + filename_add)
-      nframe = 0
     end if
 
     maps(ii) = gsn_csm_contour_map(wks, data1, res)
-    nframe = nframe + 1
 
     ; #########################################
     ; # output all datasets to common netCDF  #
@@ -478,7 +476,6 @@ begin
   pres@pmLabelBarOrthogonalPosF   = -0.01     ; shift label bar a bit to
                                               ; the bottom
   outfile = panelling(wks, maps, (dim_MOD + 3) / 4, 4, pres)
-  nframe = nframe + 1
 
   ; plot multi-obs and multi-model average (if requested)
 
@@ -535,11 +532,6 @@ begin
 
   log_info(" Wrote " + outfile)
 
-  suffix = get_file_suffix(outfile, 0)
-  if (suffix .eq. ".png") then
-    outfile = suffix@fBase + "." + sprinti("%0.6i", nframe) + suffix
-  end if
-
   ; ------------------------------------------------------------------------
   ; write provenance to common netcdf and plot file
   ; ------------------------------------------------------------------------
diff --git a/esmvaltool/diag_scripts/clouds/clouds_lifrac_scatter.ncl b/esmvaltool/diag_scripts/clouds/clouds_lifrac_scatter.ncl
index f9bf33f30d..b383753c90 100644
--- a/esmvaltool/diag_scripts/clouds/clouds_lifrac_scatter.ncl
+++ b/esmvaltool/diag_scripts/clouds/clouds_lifrac_scatter.ncl
@@ -652,8 +652,6 @@ begin
     data_l(0, :) = data@_FillValue
   end if
 
-  nframe = 0
-
   do ii = 0, dim_MOD + add_dim_MOD - 1
     if (ii .eq. refidx_ta) then
       continue
@@ -724,8 +722,6 @@ begin
     frame(wks_i)
     draw(plots_l(ii))
     frame(wks_l)
-
-    nframe = nframe + 1
   end do
 
   pres                      = True    ; needed to override
@@ -747,17 +743,6 @@ begin
   log_info("Wrote " + outfile_l)
   delete(idx0)
 
-  nframe = nframe + 1
-
-  suffix = get_file_suffix(outfile_i, 0)
-  if (suffix .eq. ".png") then
-    outfile_i = suffix@fBase + "." + sprinti("%0.6i", nframe) + suffix
-  end if
-  suffix = get_file_suffix(outfile_l, 0)
-  if (suffix .eq. ".png") then
-    outfile_l = suffix@fBase + "." + sprinti("%0.6i", nframe) + suffix
-  end if
-
   ; ==========================================================================
 
   ; ----------------------------------------------------------------------
diff --git a/esmvaltool/diag_scripts/clouds/clouds_pdf.ncl b/esmvaltool/diag_scripts/clouds/clouds_pdf.ncl
index 36f9f6fbef..bc94f08fc2 100644
--- a/esmvaltool/diag_scripts/clouds/clouds_pdf.ncl
+++ b/esmvaltool/diag_scripts/clouds/clouds_pdf.ncl
@@ -220,7 +220,6 @@ begin
     ; function in aux_plotting.ncl
 
     if (ii.eq.0) then
-      nframe = 0
       wks = get_wks("dummy_for_wks", DIAG_SCRIPT, "clouds_pdf_" + var0 \
                     + filename_add)
       wks_line = get_wks("dummy_for_wks", DIAG_SCRIPT, "clouds_pdf_" + var0 \
@@ -235,7 +234,6 @@ begin
     res@tiMainString             = names(imod)
 
     plot(ii) = gsn_histogram(wks, ndtooned(data1), res)
-    nframe = nframe + 1
 
     ; mandatory netcdf output
 
@@ -364,12 +362,6 @@ begin
 
   gsn_panel(wks, plot(plotind), plotsperline, pres)
   outfile = wks@fullname
-  nframe = nframe + 1
-
-  suffix = get_file_suffix(outfile, 0)
-  if (suffix .eq. ".png") then
-    outfile = suffix@fBase + "." + sprinti("%0.6i", nframe) + suffix
-  end if
 
   ; ========================================================================
 
diff --git a/esmvaltool/diag_scripts/clouds/clouds_scatter.ncl b/esmvaltool/diag_scripts/clouds/clouds_scatter.ncl
index 35e217613b..996fcd7121 100644
--- a/esmvaltool/diag_scripts/clouds/clouds_scatter.ncl
+++ b/esmvaltool/diag_scripts/clouds/clouds_scatter.ncl
@@ -434,8 +434,6 @@ begin
     data(0, :) = data@_FillValue
   end if
 
-  nframe = 0
-
   do ii = 0, dim_MOD - 1
     if (ii .eq. refidx_x) then
       continue
@@ -485,7 +483,6 @@ begin
     res@tiMainString = names(ii)
 
     plots(ii) = gsn_csm_xy(wks, result_avg&bin, data, res)
-    nframe = nframe + 1
 
     if (ii .eq. mm_ind) then
       res_std = True
@@ -554,16 +551,10 @@ begin
   pres@lbLabelFontHeightF               = min((/0.01, 0.01 * 6.0 \
                                               / tofloat((dim_MOD + 1) / 2)/))
   outfile = panelling(wks, plots(idx0), (n + 3) / 4, 4, pres)
-  nframe = nframe + 1
   delete(idx0)
 
   log_info("Wrote " + outfile)
 
-  suffix = get_file_suffix(outfile, 0)
-  if (suffix .eq. ".png") then
-    outfile = suffix@fBase + "." + sprinti("%0.6i", nframe) + suffix
-  end if
-
   ; ==========================================================================
 
   ; ----------------------------------------------------------------------
diff --git a/esmvaltool/diag_scripts/clouds/clouds_seasonal_cycle.ncl b/esmvaltool/diag_scripts/clouds/clouds_seasonal_cycle.ncl
index d918e9eccb..1b6ae7fdad 100644
--- a/esmvaltool/diag_scripts/clouds/clouds_seasonal_cycle.ncl
+++ b/esmvaltool/diag_scripts/clouds/clouds_seasonal_cycle.ncl
@@ -405,11 +405,9 @@ begin
     if (ii.eq.0) then
       wks = get_wks("dummy_for_wks", DIAG_SCRIPT, "clouds_seasonal_cycle_" \
                     + var0 + filename_add)
-      nframe = 0
     end if
 
     maps(ii) = gsn_csm_contour_map(wks, data1, res)
-    nframe = nframe + 1
 
     ; #########################################
     ; # output all datasets to common netCDF  #
@@ -438,12 +436,6 @@ begin
   pres@pmLabelBarOrthogonalPosF   = -0.01     ; shift label bar a bit to
                                               ; the bottom
   outfile = panelling(wks, maps, (dim_MOD + 3) / 4, 4, pres)
-  nframe = nframe + 1
-
-  suffix = get_file_suffix(outfile, 0)
-  if (suffix .eq. ".png") then
-    outfile = suffix@fBase + "." + sprinti("%0.6i", nframe) + suffix
-  end if
 
   ; plot multi-obs and multi-model average (if requested)
 
@@ -455,7 +447,6 @@ begin
     res@gsnLeftString = "mean = " + sprintf("%6.3f", gavg)
     res@tiMainString = "Multi-obs average"
     map_multiobs = gsn_csm_contour_map(wks, multiobs, res)
-    nframe = nframe + 1
   end if
 
   if (flag_multimod) then
@@ -488,7 +479,6 @@ begin
     res@gsnRightString = "rmsd = " + sprintf("%6.3f", rmsd)
     res@tiMainString = "Multi-model average"
     map_multimod = gsn_csm_contour_map(wks, multimod, res)
-    nframe = nframe + 1
   end if
 
   log_info(" Wrote " + outfile)
diff --git a/esmvaltool/diag_scripts/clouds/clouds_zonal.ncl b/esmvaltool/diag_scripts/clouds/clouds_zonal.ncl
index 32b7befb7f..a9ab9848c4 100644
--- a/esmvaltool/diag_scripts/clouds/clouds_zonal.ncl
+++ b/esmvaltool/diag_scripts/clouds/clouds_zonal.ncl
@@ -483,7 +483,6 @@ begin
       ;       individually
       wks0 = get_wks("dummy_for_wks", DIAG_SCRIPT, "clouds_zonal_" + var0 + \
                      "_" + season(0) + filename_add)
-      nframe = 0
       ; difference plots will be saved to a different file
       if (flag_diff) then
         wks0d = get_wks("dummy_for_wks", DIAG_SCRIPT, "clouds_zonal_" + \
@@ -575,7 +574,6 @@ begin
         maps(imod, 0) = gsn_csm_contour(wks0, data1, res)
       end if
     end if
-    nframe = nframe + 1
 
     ; mandatory netcdf output
 
@@ -1121,19 +1119,11 @@ begin
                              4, pres)
     end if
   end if  ; if embracesetup
-  nframe = nframe + 1
 
   do is = 0, numseas - 1
     log_info("Wrote " + outfile(is))
   end do
 
-  do is = 0, numseas - 1
-    suffix = get_file_suffix(outfile(is), 0)
-    if (suffix .eq. ".png") then
-      outfile(is) = suffix@fBase + "." + sprinti("%0.6i", nframe) + suffix
-    end if
-  end do
-
   ; ------------------------------------------------------------------------
   ; write provenance to netcdf output and plot file(s) (mean)
   ; ------------------------------------------------------------------------
@@ -1290,13 +1280,6 @@ begin
     end if  ; end if embracesetup
     ndframe = ndframe + 1
 
-    do is = 0, numseas - 1
-      suffix = get_file_suffix(outfile_d(is), 0)
-      if (suffix .eq. ".png") then
-        outfile_d(is) = suffix@fBase + "." + sprinti("%0.6i", ndframe) + suffix
-      end if
-    end do
-
     do is = 0, numseas - 1
       log_info(" Wrote " + outfile(is))
 
diff --git a/esmvaltool/interface_scripts/logging.ncl b/esmvaltool/interface_scripts/logging.ncl
index 8db7d8fe09..3e1b10b0b2 100644
--- a/esmvaltool/interface_scripts/logging.ncl
+++ b/esmvaltool/interface_scripts/logging.ncl
@@ -334,9 +334,38 @@ begin
 
   ; Save entries for outfile if not "n/a"
   if (outfile .ne. "n/a") then
-    outstring2 = outstring
-    outstring2(0) = "? " + outfile
-    outstring := array_append_record(outstring, outstring2, 0)
+    suffix = get_file_suffix(outfile, 0)
+
+    ; For PNGs, additionally check for existence of files like
+    ; "plot_file.000001.png", "plot_file.000002.png", etc. and save
+    ; provenance record for each of them
+    if ((suffix .eq. ".png") .and. (.not. fileexists(outfile))) then
+      do file_idx = 1, 999999
+        potential_outfile = suffix@fBase + "." + sprinti("%0.6i", file_idx) + \
+                            suffix
+        if (fileexists(potential_outfile)) then
+          if (.not. isvar("all_outfiles")) then
+            all_outfiles = potential_outfile
+          else
+            all_outfiles := array_append_record(all_outfiles, \
+                                                potential_outfile, 0)
+          end if
+        else
+          break
+        end if
+      end do
+    else
+      all_outfiles = outfile
+    end if
+
+    ; Save provenance record of all files
+    original_entry = outstring
+    do outfile_idx = 0, dimsizes(all_outfiles) - 1
+      file_to_add := all_outfiles(outfile_idx)
+      new_entry = (/original_entry/)
+      new_entry(0) = "? " + file_to_add
+      outstring := array_append_record(outstring, new_entry, 0)
+    end do
   end if
 
   ; Save existing information to avoid overwriting

From 9c0d9d48614f368b373102fac51c22c6a277ef01 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?R=C3=A9mi=20Kazeroni?= <remi.kazeroni@dlr.de>
Date: Fri, 18 Aug 2023 15:28:59 +0200
Subject: [PATCH 36/93] Add `OBS-maintainers` team to documentation on OBS data
 maintenance and CMORizer reviews (#3335)

---
 .github/CODEOWNERS                      |  2 +-
 .github/pull_request_template.md        |  1 +
 doc/sphinx/source/community/dataset.rst | 10 +++++-----
 doc/sphinx/source/community/review.rst  |  4 ++--
 4 files changed, 9 insertions(+), 8 deletions(-)

diff --git a/.github/CODEOWNERS b/.github/CODEOWNERS
index e1aaa42272..2086d60173 100644
--- a/.github/CODEOWNERS
+++ b/.github/CODEOWNERS
@@ -1,2 +1,2 @@
-esmvaltool/cmorizers @remi-kazeroni
+esmvaltool/cmorizers @ESMValGroup/obs-maintainers
 .github/workflows @valeriupredoi
diff --git a/.github/pull_request_template.md b/.github/pull_request_template.md
index 83cf97eb4c..5041b22420 100644
--- a/.github/pull_request_template.md
+++ b/.github/pull_request_template.md
@@ -62,6 +62,7 @@ It is the responsibility of the author to make sure the pull request is ready to
 
 - [ ] [🛠][1] [Documentation](https://docs.esmvaltool.org/en/latest/community/dataset.html#dataset-documentation) is available
 - [ ] [🛠][1] The dataset has been [added to the CMOR check recipe](https://docs.esmvaltool.org/en/latest/community/dataset.html#testing)
+- [ ] [🛠][1] The dataset has been added to the shared [data pools](https://docs.esmvaltool.org/en/latest/community/dataset.html#cmorized-data) of DKRZ and Jasmin by the @ESMValGroup/OBS-maintainers team
 - [ ] [🧪][2] Numbers and units of the data look [physically meaningful](https://docs.esmvaltool.org/en/latest/community/dataset.html#scientific-sanity-check)
 
 ***
diff --git a/doc/sphinx/source/community/dataset.rst b/doc/sphinx/source/community/dataset.rst
index d70438d9bc..424d4d4694 100644
--- a/doc/sphinx/source/community/dataset.rst
+++ b/doc/sphinx/source/community/dataset.rst
@@ -65,10 +65,10 @@ The scientific reviewer needs to check this.
 Data availability
 =================
 
-Once your pull request has been approved by the reviewers, ask
-`@remi-kazeroni <https://github.com/remi-kazeroni>`_
+Once your pull request has been approved by the reviewers, ask a member of
+`@OBS-maintainers <https://github.com/orgs/ESMValGroup/teams/obs-maintainers>`_
 to add the new dataset to the data pool at DKRZ and CEDA-Jasmin.
-He is also the person in charge of merging CMORizer pull requests.
+This team is in charge of merging CMORizer pull requests.
 
 .. _dataset_checklist:
 
@@ -165,14 +165,14 @@ Run ``esmvaltool/recipes/examples/recipe_check_obs.yml`` for new dataset.
 RAW data
 --------
 
-Contact person in charge of ESMValTool data pool (`@remi-kazeroni`_) and
+Contact the team in charge of ESMValTool data pool (`@OBS-maintainers`_) and
 request to copy RAW data to RAWOBS/Tier2 (Tier3).
 
 
 CMORized data
 -------------
 
-Contact person in charge of ESMValTool data pool (`@remi-kazeroni`_) and
+Contact the team in charge of ESMValTool data pool (`@OBS-maintainers`_) and
 request to
 
 * Merge the pull request
diff --git a/doc/sphinx/source/community/review.rst b/doc/sphinx/source/community/review.rst
index 41e596dda9..3429c0ef7a 100644
--- a/doc/sphinx/source/community/review.rst
+++ b/doc/sphinx/source/community/review.rst
@@ -69,7 +69,7 @@ GitHub.
 
 Pull requests are merged by the `@ESMValGroup/esmvaltool-coreteam`_.
 Specifically, pull requests containing a :ref:`CMORizer script<new-dataset>` can only be merged by
-`@remi-kazeroni`_, who will then add the CMORized data to the OBS data pool at
+a member of `@OBS-maintainers`_, who will then add the CMORized data to the OBS data pool at
 DKRZ and CEDA-Jasmin.
 The team member who does the merge first checks that both the technical and
 scientific reviewer approved the pull request and that the reviews were
@@ -215,7 +215,7 @@ their opinion and try to find a solution.
 .. _`@ESMValGroup/tech-reviewers`: https://github.com/orgs/ESMValGroup/teams/tech-reviewers
 .. _`@ESMValGroup/science-reviewers`: https://github.com/orgs/ESMValGroup/teams/science-reviewers
 .. _`@ESMValGroup/esmvaltool-coreteam`: https://github.com/orgs/ESMValGroup/teams/esmvaltool-coreteam
-.. _`@remi-kazeroni`: https://github.com/remi-kazeroni
+.. _`@OBS-maintainers`: https://github.com/orgs/ESMValGroup/teams/obs-maintainers
 .. _`pull request template`: https://raw.githubusercontent.com/ESMValGroup/ESMValTool/main/.github/pull_request_template.md
 .. _`Google meet`: https://meet.google.com
 .. _`Jitsi meet`: https://meet.jit.si

From b244fef254dd282e7fc9e34dbe355b77eb9e9025 Mon Sep 17 00:00:00 2001
From: Axel Lauer <axel.lauer@dlr.de>
Date: Fri, 18 Aug 2023 16:03:47 +0200
Subject: [PATCH 37/93] CMORizer for NASA MERRA reanalysis (#3039)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Co-authored-by: Rémi Kazeroni <remi.kazeroni@dlr.de>
---
 doc/sphinx/source/input.rst                   |   3 +
 esmvaltool/cmorizers/data/datasets.yml        |   7 +
 .../data/downloaders/datasets/merra.py        |  57 ++++
 esmvaltool/cmorizers/data/downloaders/wget.py |   4 +-
 .../data/formatters/datasets/merra.ncl        | 315 ++++++++++++++++++
 .../cmorizers/data/formatters/utilities.ncl   |   6 +-
 .../recipes/examples/recipe_check_obs.yml     |  32 ++
 esmvaltool/references/merra.bibtex            |  13 +
 8 files changed, 432 insertions(+), 5 deletions(-)
 create mode 100644 esmvaltool/cmorizers/data/downloaders/datasets/merra.py
 create mode 100644 esmvaltool/cmorizers/data/formatters/datasets/merra.ncl
 create mode 100644 esmvaltool/references/merra.bibtex

diff --git a/doc/sphinx/source/input.rst b/doc/sphinx/source/input.rst
index c453a0569e..fa6b9b00e4 100644
--- a/doc/sphinx/source/input.rst
+++ b/doc/sphinx/source/input.rst
@@ -355,6 +355,9 @@ A list of the datasets for which a CMORizers is available is provided in the fol
 +------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+
 | MAC-LWP                      | lwp, lwpStderr (Amon)                                                                                |   3  | NCL             |
 +------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+
+| MERRA                        | cli, clivi, clt, clw, clwvi, hur, hus, lwp, pr, prw, ps, psl, rlut, rlutcs, rsdt, rsut, rsutcs, ta,  |   3  | NCL             |
+|                              | tas, ts, ua, va, wap, zg (Amon)                                                                      |      |                 |
++------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+
 | MERRA2                       | sm (Lmon)                                                                                            |   3  | Python          |
 |                              | clt, pr, evspsbl, hfss, hfls, huss, prc, prsn, prw, ps, psl, rlds, rldscs, rlus, rlut, rlutcs, rsds, |      |                 |
 |                              | rsdscs, rsdt, tas, tasmin, tasmax, tauu, tauv, ts, uas, vas, rsus, rsuscs, rsut, rsutcs, ta, ua, va, |      |                 |
diff --git a/esmvaltool/cmorizers/data/datasets.yml b/esmvaltool/cmorizers/data/datasets.yml
index d40de3988c..57fa7076ba 100644
--- a/esmvaltool/cmorizers/data/datasets.yml
+++ b/esmvaltool/cmorizers/data/datasets.yml
@@ -836,6 +836,13 @@ datasets:
       individually or by using the option "download all".
       Data is freely available, but a registration is required.
 
+  MERRA:
+    tier: 3
+    source: https://goldsmr3.gesdisc.eosdis.nasa.gov/data/MERRA_MONTHLY/
+    last_access: 2023-02-01
+    info: |
+      Use automatic download. That will download monthly data.
+
   MERRA2:
     tier: 3
     source: https://goldsmr4.gesdisc.eosdis.nasa.gov/data/MERRA2_MONTHLY/ https://goldsmr5.gesdisc.eosdis.nasa.gov/data/MERRA2_MONTHLY/
diff --git a/esmvaltool/cmorizers/data/downloaders/datasets/merra.py b/esmvaltool/cmorizers/data/downloaders/datasets/merra.py
new file mode 100644
index 0000000000..df1d0ff7e9
--- /dev/null
+++ b/esmvaltool/cmorizers/data/downloaders/datasets/merra.py
@@ -0,0 +1,57 @@
+"""Script to download MERRA."""
+
+from datetime import datetime
+
+from dateutil import relativedelta
+
+from esmvaltool.cmorizers.data.downloaders.wget import NASADownloader
+
+
+def download_dataset(config, dataset, dataset_info, start_date, end_date,
+                     overwrite):
+    """Download dataset.
+
+    Parameters
+    ----------
+    config : dict
+        ESMValTool's user configuration
+    dataset : str
+        Name of the dataset
+    dataset_info : dict
+         Dataset information from the datasets.yml file
+    start_date : datetime
+        Start of the interval to download
+    end_date : datetime
+        End of the interval to download
+    overwrite : bool
+        Overwrite already downloaded files
+    """
+    if not start_date:
+        start_date = datetime(1979, 1, 1)
+    if not end_date:
+        end_date = datetime(2015, 12, 31)
+    loop_date = start_date
+
+    downloader = NASADownloader(
+        config=config,
+        dataset=dataset,
+        dataset_info=dataset_info,
+        overwrite=overwrite,
+    )
+
+    while loop_date <= end_date:
+        year = loop_date.year
+        downloader.download_folder(
+            "https://goldsmr3.gesdisc.eosdis.nasa.gov/data/MERRA_MONTHLY/"
+            f"MAIMNXINT.5.2.0/{year}/")
+        downloader.download_folder(
+            "https://goldsmr3.gesdisc.eosdis.nasa.gov/data/MERRA_MONTHLY/"
+            f"MAIMCPASM.5.2.0/{year}/")
+        downloader.download_folder(
+            "https://goldsmr3.gesdisc.eosdis.nasa.gov/data/MERRA_MONTHLY/"
+            f"MATMNXRAD.5.2.0/{year}/")
+        downloader.download_folder(
+            "https://goldsmr3.gesdisc.eosdis.nasa.gov/data/MERRA_MONTHLY/"
+            f"MATMFXCHM.5.2.0/{year}/")
+
+        loop_date += relativedelta.relativedelta(years=1)
diff --git a/esmvaltool/cmorizers/data/downloaders/wget.py b/esmvaltool/cmorizers/data/downloaders/wget.py
index 9db7afc478..8544e1d727 100644
--- a/esmvaltool/cmorizers/data/downloaders/wget.py
+++ b/esmvaltool/cmorizers/data/downloaders/wget.py
@@ -89,8 +89,8 @@ def download_folder(self, server_path, wget_options=None):
         """
         if wget_options is None:
             wget_options = []
-        wget_options = self._wget_common_options + ["-np", "--accept=nc,nc4"
-                                                    ] + wget_options
+        wget_options = self._wget_common_options + [
+            "-np", "--accept=nc,nc4,hdf"] + wget_options
         super().download_folder(server_path, wget_options)
 
     def download_file(self, server_path, wget_options=None):
diff --git a/esmvaltool/cmorizers/data/formatters/datasets/merra.ncl b/esmvaltool/cmorizers/data/formatters/datasets/merra.ncl
new file mode 100644
index 0000000000..b57bca6a09
--- /dev/null
+++ b/esmvaltool/cmorizers/data/formatters/datasets/merra.ncl
@@ -0,0 +1,315 @@
+; #############################################################################
+; ESMValTool CMORizer for NASA MERRA reanalysis v5.2.0
+; #############################################################################
+;
+; Tier
+;    Tier 3: restricted dataset (registration required).
+;
+; Source
+;    EarthData via https://goldsmr3.gesdisc.eosdis.nasa.gov/data/MERRA_MONTHLY/
+;
+; Last access
+;    20230201
+;
+; Download and processing instructions
+; (requires EarthData login; see https://urs.earthdata.nasa.gov/)
+;    Use ESMValTool automatic download:
+;       esmvaltool data download --config_file <config-user.yml> MERRA
+;
+; Modification history
+;    20230818-lauer_axel: added output of clwvi (iwp + lwp)
+;    20230201-lauer_axel: written
+;
+; #############################################################################
+loadscript(getenv("esmvaltool_root") + \
+           "/data/formatters/interface.ncl")
+
+begin
+
+  ; Script name (for logger)
+  DIAG_SCRIPT = "merra.ncl"
+
+  ; Source name
+  OBSNAME = "MERRA"
+
+  ; Tier
+  TIER = 3
+
+  ; Period (complete years only)
+  YEAR1 = get_year(start_year, 1979)
+  YEAR2 = get_year(end_year, 2015)
+
+  ; Selected variable (standard name)
+  VAR = (/"zg", "wap", "cli", "clw", "hus", "hur", "ta", "ua", "va",  \
+          "ps", "psl",                                                \
+          "clivi", "clwvi", "lwp", "prw",                             \
+          "clt", "rlut", "rlutcs", "rsdt", "rsut", "rsutcs", "ts",    \
+          "tas", "pr"/)
+
+  ; Name in the raw data
+  NAME = (/"H", "OMEGA", "QI", "QL", "QV", "RH", "T", "U", "V",  \  ; 3d asm
+           "PS", "SLP",                                          \
+           "TQI", "TQI", "TQL", "TQV",                           \  ; 2d int
+           "CLDTOT", "LWTUP", "LWTUPCLR", "SWTDN", "SWTNT",      \  ; 2d rad
+           "SWTNTCLR", "TS",                                     \
+           "T2M", "PRECLSC"/)                                       ; 2d chm
+
+  ; unit conversion factor
+  CONVFAC = (/1.0, 1.0, 1.0, 1.0, 1.0, 100.0, 1.0, 1.0, 1.0,  \  ; 3d asm
+             1.0, 1.0,                                        \
+             1.0, 1.0, 1.0, 1.0,                              \  ; 2d int
+             100.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,             \  ; 2d rad
+             1.0, 1.0/)                                          ; 2d chm
+
+  ; additional attribute "positive" (for radiative fluxes)
+  POSITIVE = (/"", "", "", "", "", "", "", "", "", "", "",    \  ; 3d asm
+               "", "", "", "",                                \  ; 2d int
+               "", "up", "up", "down", "up", "up", "",        \  ; 2d rad
+               "", ""/)                                          ; 2d chm
+
+  ; names source files
+  SOURCEFILE = (/"instM_3d_asm_Cp.", "instM_3d_asm_Cp.", \  ; 3d asm
+                 "instM_3d_asm_Cp.", "instM_3d_asm_Cp.", \
+                 "instM_3d_asm_Cp.", "instM_3d_asm_Cp.", \
+                 "instM_3d_asm_Cp.", "instM_3d_asm_Cp.", \
+                 "instM_3d_asm_Cp.", "instM_3d_asm_Cp.", \
+                 "instM_3d_asm_Cp.",                     \
+                 "instM_2d_int_Nx.", "instM_2d_int_Nx.", \  ; 2d int
+                 "instM_2d_int_Nx.", "instM_2d_int_Nx.", \
+                 "tavgM_2d_rad_Nx.", "tavgM_2d_rad_Nx.", \  ; 2d rad
+                 "tavgM_2d_rad_Nx.", "tavgM_2d_rad_Nx.", \
+                 "tavgM_2d_rad_Nx.", "tavgM_2d_rad_Nx.", \
+                 "tavgM_2d_rad_Nx.",                     \
+                 "tavgM_2d_chm_Fx.", "tavgM_2d_chm_Fx."/)   ; 2d chm
+
+  ; dataset doi numbers
+  DOI = (/"10.5067/YX0AVASQRTNW", "10.5067/YX0AVASQRTNW",  \  ; 3d asm
+          "10.5067/YX0AVASQRTNW", "10.5067/YX0AVASQRTNW",  \
+          "10.5067/YX0AVASQRTNW", "10.5067/YX0AVASQRTNW",  \
+          "10.5067/YX0AVASQRTNW", "10.5067/YX0AVASQRTNW",  \
+          "10.5067/YX0AVASQRTNW", "10.5067/YX0AVASQRTNW",  \
+          "10.5067/YX0AVASQRTNW",                          \
+          "10.5067/QL0PGBK2CYJS", "10.5067/QL0PGBK2CYJS",  \  ; 2d int
+          "10.5067/QL0PGBK2CYJS", "10.5067/QL0PGBK2CYJS",  \
+          "10.5067/6UX3EDUNVUFK", "10.5067/6UX3EDUNVUFK",  \  ; 2d rad
+          "10.5067/6UX3EDUNVUFK", "10.5067/6UX3EDUNVUFK",  \
+          "10.5067/6UX3EDUNVUFK", "10.5067/6UX3EDUNVUFK",  \
+          "10.5067/6UX3EDUNVUFK",                          \
+          "10.5067/IYDN3LNZ63UE", "10.5067/IYDN3LNZ63UE"/)    ; 2d chm
+
+  ; MIP
+  MIP = "Amon"
+
+  ; Frequency
+  FREQ = "mon"
+
+  ; CMOR table
+  CMOR_TABLE = getenv("cmor_tables") + \
+    (/"/cmip5/Tables/CMIP5_" + MIP, "/cmip5/Tables/CMIP5_" + MIP,  \  ; 3d asm
+      "/cmip5/Tables/CMIP5_" + MIP, "/cmip5/Tables/CMIP5_" + MIP,  \
+      "/cmip5/Tables/CMIP5_" + MIP, "/cmip5/Tables/CMIP5_" + MIP,  \
+      "/cmip5/Tables/CMIP5_" + MIP, "/cmip5/Tables/CMIP5_" + MIP,  \
+      "/cmip5/Tables/CMIP5_" + MIP, "/cmip5/Tables/CMIP5_" + MIP,  \
+      "/cmip5/Tables/CMIP5_" + MIP,                                \
+      "/cmip5/Tables/CMIP5_" + MIP, "/cmip5/Tables/CMIP5_" + MIP,  \  ; 2d int
+      "/custom/CMOR_lwp.dat", "/cmip5/Tables/CMIP5_" + MIP,        \
+      "/cmip5/Tables/CMIP5_" + MIP, "/cmip5/Tables/CMIP5_" + MIP,  \  ; 2d rad
+      "/cmip5/Tables/CMIP5_" + MIP, "/cmip5/Tables/CMIP5_" + MIP,  \
+      "/cmip5/Tables/CMIP5_" + MIP, "/cmip5/Tables/CMIP5_" + MIP,  \
+      "/cmip5/Tables/CMIP5_" + MIP,                                \
+      "/cmip5/Tables/CMIP5_" + MIP, "/cmip5/Tables/CMIP5_" + MIP/)    ; 2d chm
+
+  ; Type
+  TYPE = "reanaly"
+
+  ; Version
+  VERSION = "5.2.0"
+
+  ; Global attributes
+  SOURCE = "https://goldsmr3.gesdisc.eosdis.nasa.gov/data/MERRA_MONTHLY/"
+  COMMENT = "Goddard Earth Sciences Data and Information Services Center " + \
+            "(GES DISC)"
+
+end
+
+begin
+
+  ; Loop over variables
+  do vv = 0, dimsizes(VAR) - 1
+
+    log_info("Processing " + VAR(vv) + " (" + MIP + ")")
+    if (isvar("output")) then
+      delete(output)
+    end if
+
+    do yy = YEAR1, YEAR2
+      do mm = 1, 12
+
+        datestr = tostring(yy)
+        if (mm .lt. 10) then
+          datestr = datestr + "0"
+        end if
+        datestr = datestr + tostring(mm)
+
+        fname = systemfunc("ls " + input_dir_path + "MERRA???.prod.assim." + \
+                           SOURCEFILE(vv) + datestr + ".hdf")
+
+        f = addfile(fname, "r")
+        tmp = f->$NAME(vv)$
+
+        ; Extract time range
+        tmp&TIME_EOSGRID@calendar = "standard"
+        date = cd_calendar(tmp&TIME_EOSGRID, 0)
+        if ((date(0, 0) .ne. yy) .or. (date(0, 1) .ne. mm)) then
+          error_msg("f", DIAG_SCRIPT, "", \
+                    "date in input file does not match date in filename: " + \
+                    fname)
+        end if
+
+        delete(date)
+
+        if (.not.isvar("output")) then
+          dims = dimsizes(tmp)
+          ; overwrite time dimension
+          dims(0) = 12
+          output = new(dims, float)
+          delete(dims)
+          rank = dimsizes(dimsizes(output))
+
+          output!0 = "time"
+          if (rank.eq.4) then
+            output!1 = "plev"
+            output!2 = "lat"
+            output!3 = "lon"
+            output&plev = tmp&Height_EOSGRID * 100.  ; [hPa] --> [Pa]
+          elseif (rank.eq.3)
+            output!1 = "lat"
+            output!2 = "lon"
+          end if
+
+          output&time = fspan(1, 12, 12)
+          output&time@calendar = "standard"
+          output&time@units = "days since 1950-01-01 00:00:00"
+
+          output&lat = tmp&YDim_EOSGRID
+          output&lon = tmp&XDim_EOSGRID
+
+        end if
+
+        ; Unpack variable according to metadata information
+        if (isatt(tmp, "scale_factor") .or. isatt(tmp, "add_offset")) then
+          tmp = tmp * tmp@scale_factor + tmp@add_offset
+        end if
+
+        if (rank.eq.4) then
+          output(mm - 1, :, :, :) = (/ tmp(0, :, :, :) /)
+        else
+          output(mm - 1, :, :) = (/ tmp(0, :, :) /)
+        end if
+
+        delete(tmp)
+
+        ; calcuation of outgoing fluxes: out = in - net
+        if ((VAR(vv) .eq. "rsut") .or. (VAR(vv) .eq. "rsutcs")) then
+          tmp = f->SWTDN
+          if (isatt(tmp, "scale_factor") .or. isatt(tmp, "add_offset")) then
+            tmp = tmp * tmp@scale_factor + tmp@add_offset
+          end if
+          output(mm - 1, :, :) = (/ tmp(0, :, :) /) - output(mm - 1, :, :)
+
+          delete(tmp)
+        end if
+
+        ; calcuation of total precipitation flux = large-scale+convective+anvil
+        if (VAR(vv) .eq. "pr") then
+          tmp = f->PRECCON  ; surface precipitation flux from convection
+          if (isatt(tmp, "scale_factor") .or. isatt(tmp, "add_offset")) then
+            tmp = tmp * tmp@scale_factor + tmp@add_offset
+          end if
+          output(mm - 1, :, :) = output(mm - 1, :, :) + tmp(0, :, :)
+          delete(tmp)
+          tmp = f->PRECANV  ; surface precipitation flux from anvils
+          if (isatt(tmp, "scale_factor") .or. isatt(tmp, "add_offset")) then
+            tmp = tmp * tmp@scale_factor + tmp@add_offset
+          end if
+          output(mm - 1, :, :) = output(mm - 1, :, :) + tmp(0, :, :)
+          delete(tmp)
+        end if
+
+        ; calculation of clwvi
+        if (VAR(vv) .eq. "clwvi") then
+          tmp = f->TQL
+          if (isatt(tmp, "scale_factor") .or. isatt(tmp, "add_offset")) then
+            tmp = tmp * tmp@scale_factor + tmp@add_offset
+          end if
+          output(mm - 1, :, :) = output(mm - 1, :, :) + tmp(0, :, :)
+          delete(tmp)
+        end if
+
+        delete(f)
+
+      end do  ; loop over months (mm)
+
+      ; Convert units
+      if (CONVFAC(vv) .ne. 1.0) then
+        output = output * CONVFAC(vv)
+      end if
+
+      ; Format coordinates
+      format_coords(output, yy + "0101", yy + "1231", FREQ)
+
+      ; Set variable attributes
+      tmp = format_variable(output, VAR(vv), CMOR_TABLE(vv))
+      delete(output)
+      output = tmp
+      delete(tmp)
+
+      ; set additional attribute "positive" for radiative fluxes
+      if (POSITIVE(vv) .ne. "") then
+        output@positive = POSITIVE(vv)
+      end if
+
+      ; Calculate coordinate bounds
+      bounds = guess_coord_bounds(output, FREQ)
+
+      ; Set global attributes
+      REF = "doi: " + DOI(vv)
+      gAtt = set_global_atts(OBSNAME, TIER, SOURCE, REF, COMMENT)
+
+      ; Output file
+      DATESTR = yy + "01-" + yy + "12"
+      fout = output_dir_path + \
+        str_join((/"OBS", OBSNAME, TYPE, VERSION, \
+                   MIP, VAR(vv), DATESTR/), "_") + ".nc"
+
+      ; Add height coordinate to tas variable (required by the new backend)
+      if (VAR(vv).eq."tas") then
+        output@coordinates = "height"
+      end if
+
+      ; Write variable
+      write_nc(fout, VAR(vv), output, bounds, gAtt)
+      delete(gAtt)
+      delete(output)
+      delete(bounds)
+
+      ; Add height coordinate to tas variable (required by CMOR checker)
+      if (VAR(vv).eq."tas") then
+        height = 2.d
+        height!0 = "ncl_scalar"
+        height@units = "m"
+        height@axis = "Z"
+        height@positive = "up"
+        height@long_name = "height"
+        height@standard_name = "height"
+        w = addfile(fout, "w")
+        w->height = height
+        delete(w)
+      end if
+
+        ; ---------------------------------------------------------------------
+
+    end do  ; loop over years (yy)
+  end do  ; loop over variables (vv)
+
+end
diff --git a/esmvaltool/cmorizers/data/formatters/utilities.ncl b/esmvaltool/cmorizers/data/formatters/utilities.ncl
index 42632889ef..4c8cf6444e 100644
--- a/esmvaltool/cmorizers/data/formatters/utilities.ncl
+++ b/esmvaltool/cmorizers/data/formatters/utilities.ncl
@@ -209,11 +209,11 @@ begin
     ; Reset date (middle of the month)
     tt = 0
     do yy = year1, year2
-      date(tt, 0) = yy
       yy@calendar = calendar
       m1 = where(yy.eq.year1, month1, 1)
       m2 = where(yy.eq.year2, month2, 12)
       do mm = m1, m2
+        date(tt, 0) = yy
         date(tt, 1) = mm
         dm = days_in_month(yy, mm) / 2. + 1
         date(tt, 2) = toint(dm)
@@ -245,14 +245,14 @@ begin
     ; Reset date (middle of the day)
     tt = 0
     do yy = year1, year2
-      date(tt, 0) = yy
       m1 = where(yy.eq.year1, month1, 1)
       m2 = where(yy.eq.year2, month2, 12)
       do mm = m1, m2
-        date(tt, 1) = mm
         d1 = where(yy.eq.year1 .and. mm.eq.m1, day1, 1)
         d2 = where(yy.eq.year2 .and. mm.eq.m2, day2, days_in_month(yy, mm))
         do dd = d1, d2
+          date(tt, 0) = yy
+          date(tt, 1) = mm
           date(tt, 2) = dd
           tt = tt + 1
         end do
diff --git a/esmvaltool/recipes/examples/recipe_check_obs.yml b/esmvaltool/recipes/examples/recipe_check_obs.yml
index 83ccc55607..414b9e5b79 100644
--- a/esmvaltool/recipes/examples/recipe_check_obs.yml
+++ b/esmvaltool/recipes/examples/recipe_check_obs.yml
@@ -1612,6 +1612,38 @@ diagnostics:
          type: sat, version: v1, start_year: 1988, end_year: 2016}
     scripts: null
 
+  MERRA:
+    description: MERRA check
+    variables:
+      cli:
+      clivi:
+      clt:
+      clw:
+      clwvi:
+      hur:
+      hus:
+      lwp:
+      pr:
+      prw:
+      ps:
+      psl:
+      rlut:
+      rlutcs:
+      rsdt:
+      rsut:
+      rsutcs:
+      ta:
+      tas:
+      ts:
+      ua:
+      va:
+      wap:
+      zg:
+    additional_datasets:
+      - {dataset: MERRA, project: OBS, tier: 3, mip: Amon,
+         type: reanaly, version: 5.2.0, start_year: 1979, end_year: 2015}
+    scripts: null
+
 
   MERRA2:
     description: MERRA2 check
diff --git a/esmvaltool/references/merra.bibtex b/esmvaltool/references/merra.bibtex
new file mode 100644
index 0000000000..aa1df2c53d
--- /dev/null
+++ b/esmvaltool/references/merra.bibtex
@@ -0,0 +1,13 @@
+@article{merra,
+	doi = {10.1175/JCLI-D-11-00015.1},
+	url = {https://journals.ametsoc.org/view/journals/clim/24/14/jcli-d-11-00015.1.xml},
+	year = 2011,
+	month = {jul},
+	publisher = {American Meteorological Society},
+	volume = {24},
+	number = {14},
+	pages = {3624--3648},
+	author = {Michele M. Rienecker and Max J. Suarez and Ronald Gelaro and Ricardo Todling and Julio Bacmeister and Emily Liu and Michael G. Bosilovich and Siegfried D. Schubert and Lawrence Takacs and Gi-Kong Kim and Stephen Bloom and Junye Chen and Douglas Collins and Austin Conaty and Arlindo da Silva and Wei Gu and Joanna Joiner and Randal D. Koster and Robert Lucchesi and Andrea Molod and Tommy Owens and Steven Pawson and Philip Pegion and Christopher R. Redder and Rolf Reichle and Franklin R. Robertson and Albert G. Ruddick and Meta Sienkiewicz and Jack Woollen},
+	title = {{MERRA}: {NASA}’s Modern-Era Retrospective Analysis for Research and Applications},
+	journal = {Journal of Climate}
+}

From 0d2b68d6614c667141207affd7834cc49d34b203 Mon Sep 17 00:00:00 2001
From: Emma Hogan <ehogan@users.noreply.github.com>
Date: Thu, 24 Aug 2023 12:34:49 +0100
Subject: [PATCH 38/93] Add version to dataset in python example recipe to
 avoid "Unknown file format" issue on JASMIN (#3322)

---
 esmvaltool/recipes/examples/recipe_python.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/esmvaltool/recipes/examples/recipe_python.yml b/esmvaltool/recipes/examples/recipe_python.yml
index a6309d826e..d85e1ae437 100644
--- a/esmvaltool/recipes/examples/recipe_python.yml
+++ b/esmvaltool/recipes/examples/recipe_python.yml
@@ -29,7 +29,7 @@ documentation:
 
 datasets:
   - {dataset: BCC-ESM1, project: CMIP6, exp: historical, ensemble: r1i1p1f1, grid: gn}
-  - {dataset: bcc-csm1-1, project: CMIP5, exp: historical, ensemble: r1i1p1}
+  - {dataset: bcc-csm1-1, version: v1, project: CMIP5, exp: historical, ensemble: r1i1p1}
 
 preprocessors:
   # See https://docs.esmvaltool.org/projects/esmvalcore/en/latest/recipe/preprocessor.html

From 88b3cc9799d03aa109f9ab30bd7ecc048470b946 Mon Sep 17 00:00:00 2001
From: Manuel Schlund <32543114+schlunma@users.noreply.github.com>
Date: Wed, 6 Sep 2023 15:06:50 +0200
Subject: [PATCH 39/93] Allow custom variable grouping in
 `monitor/multi_datasets.py` (#3343)

---
 .../diag_scripts/monitor/multi_datasets.py    | 57 ++++++++++++-------
 1 file changed, 36 insertions(+), 21 deletions(-)

diff --git a/esmvaltool/diag_scripts/monitor/multi_datasets.py b/esmvaltool/diag_scripts/monitor/multi_datasets.py
index 6ac399652b..c6bda52e81 100644
--- a/esmvaltool/diag_scripts/monitor/multi_datasets.py
+++ b/esmvaltool/diag_scripts/monitor/multi_datasets.py
@@ -60,6 +60,9 @@
 figure_kwargs: dict, optional
     Optional keyword arguments for :func:`matplotlib.pyplot.figure`. By
     default, uses ``constrained_layout: true``.
+group_variables_by: str, optional (default: 'short_name')
+    Facet which is used to create variable groups. For each variable group, an
+    individual plot is created.
 plots: dict, optional
     Plot types plotted by this diagnostic (see list above). Dictionary keys
     must be ``timeseries``, ``annual_cycle``, ``map``, ``zonal_mean_profile``
@@ -401,12 +404,15 @@ def __init__(self, config):
         self.cfg = deepcopy(self.cfg)
         self.cfg.setdefault('facet_used_for_labels', 'dataset')
         self.cfg.setdefault('figure_kwargs', {'constrained_layout': True})
+        self.cfg.setdefault('group_variables_by', 'short_name')
         self.cfg.setdefault('savefig_kwargs', {
             'bbox_inches': 'tight',
             'dpi': 300,
             'orientation': 'landscape',
         })
         self.cfg.setdefault('seaborn_settings', {'style': 'ticks'})
+        logger.info("Using facet '%s' to group variables",
+                    self.cfg['group_variables_by'])
         logger.info("Using facet '%s' to create labels",
                     self.cfg['facet_used_for_labels'])
 
@@ -414,7 +420,7 @@ def __init__(self, config):
         self.input_data = self._load_and_preprocess_data()
         self.grouped_input_data = group_metadata(
             self.input_data,
-            'short_name',
+            self.cfg['group_variables_by'],
             sort=self.cfg['facet_used_for_labels'],
         )
 
@@ -1170,21 +1176,21 @@ def _get_multi_dataset_facets(datasets):
                 multi_dataset_facets[key] = f'ambiguous_{key}'
         return multi_dataset_facets
 
-    @staticmethod
-    def _get_reference_dataset(datasets, short_name):
+    def _get_reference_dataset(self, datasets):
         """Extract reference dataset."""
+        variable = datasets[0][self.cfg['group_variables_by']]
         ref_datasets = [d for d in datasets if
                         d.get('reference_for_monitor_diags', False)]
         if len(ref_datasets) > 1:
             raise ValueError(
                 f"Expected at most 1 reference dataset (with "
                 f"'reference_for_monitor_diags: true' for variable "
-                f"'{short_name}', got {len(ref_datasets):d}")
+                f"'{variable}', got {len(ref_datasets):d}")
         if ref_datasets:
             return ref_datasets[0]
         return None
 
-    def create_timeseries_plot(self, datasets, short_name):
+    def create_timeseries_plot(self, datasets):
         """Create time series plot."""
         plot_type = 'timeseries'
         if plot_type not in self.plots:
@@ -1227,7 +1233,10 @@ def create_timeseries_plot(self, datasets, short_name):
         multi_dataset_facets = self._get_multi_dataset_facets(datasets)
         axes.set_title(multi_dataset_facets['long_name'])
         axes.set_xlabel('Time')
-        axes.set_ylabel(f"{short_name} [{multi_dataset_facets['units']}]")
+        axes.set_ylabel(
+            f"{multi_dataset_facets[self.cfg['group_variables_by']]} "
+            f"[{multi_dataset_facets['units']}]"
+        )
         gridline_kwargs = self._get_gridline_kwargs(plot_type)
         if gridline_kwargs is not False:
             axes.grid(**gridline_kwargs)
@@ -1267,7 +1276,7 @@ def create_timeseries_plot(self, datasets, short_name):
             provenance_logger.log(plot_path, provenance_record)
             provenance_logger.log(netcdf_path, provenance_record)
 
-    def create_annual_cycle_plot(self, datasets, short_name):
+    def create_annual_cycle_plot(self, datasets):
         """Create annual cycle plot."""
         plot_type = 'annual_cycle'
         if plot_type not in self.plots:
@@ -1298,7 +1307,10 @@ def create_annual_cycle_plot(self, datasets, short_name):
         multi_dataset_facets = self._get_multi_dataset_facets(datasets)
         axes.set_title(multi_dataset_facets['long_name'])
         axes.set_xlabel('Month')
-        axes.set_ylabel(f"{short_name} [{multi_dataset_facets['units']}]")
+        axes.set_ylabel(
+            f"{multi_dataset_facets[self.cfg['group_variables_by']]} "
+            f"[{multi_dataset_facets['units']}]"
+        )
         axes.set_xticks(range(1, 13), [str(m) for m in range(1, 13)])
         gridline_kwargs = self._get_gridline_kwargs(plot_type)
         if gridline_kwargs is not False:
@@ -1339,7 +1351,7 @@ def create_annual_cycle_plot(self, datasets, short_name):
             provenance_logger.log(plot_path, provenance_record)
             provenance_logger.log(netcdf_path, provenance_record)
 
-    def create_map_plot(self, datasets, short_name):
+    def create_map_plot(self, datasets):
         """Create map plot."""
         plot_type = 'map'
         if plot_type not in self.plots:
@@ -1349,7 +1361,7 @@ def create_map_plot(self, datasets, short_name):
             raise ValueError(f"No input data to plot '{plot_type}' given")
 
         # Get reference dataset if possible
-        ref_dataset = self._get_reference_dataset(datasets, short_name)
+        ref_dataset = self._get_reference_dataset(datasets)
         if ref_dataset is None:
             logger.info("Plotting %s without reference dataset", plot_type)
         else:
@@ -1415,7 +1427,7 @@ def create_map_plot(self, datasets, short_name):
                 for netcdf_path in netcdf_paths:
                     provenance_logger.log(netcdf_path, provenance_record)
 
-    def create_zonal_mean_profile_plot(self, datasets, short_name):
+    def create_zonal_mean_profile_plot(self, datasets):
         """Create zonal mean profile plot."""
         plot_type = 'zonal_mean_profile'
         if plot_type not in self.plots:
@@ -1425,7 +1437,7 @@ def create_zonal_mean_profile_plot(self, datasets, short_name):
             raise ValueError(f"No input data to plot '{plot_type}' given")
 
         # Get reference dataset if possible
-        ref_dataset = self._get_reference_dataset(datasets, short_name)
+        ref_dataset = self._get_reference_dataset(datasets)
         if ref_dataset is None:
             logger.info("Plotting %s without reference dataset", plot_type)
         else:
@@ -1493,7 +1505,7 @@ def create_zonal_mean_profile_plot(self, datasets, short_name):
                 for netcdf_path in netcdf_paths:
                     provenance_logger.log(netcdf_path, provenance_record)
 
-    def create_1d_profile_plot(self, datasets, short_name):
+    def create_1d_profile_plot(self, datasets):
         """Create 1D profile plot."""
         plot_type = '1d_profile'
         if plot_type not in self.plots:
@@ -1525,7 +1537,10 @@ def create_1d_profile_plot(self, datasets, short_name):
 
         # Default plot appearance
         axes.set_title(multi_dataset_facets['long_name'])
-        axes.set_xlabel(f"{short_name} [{multi_dataset_facets['units']}]")
+        axes.set_xlabel(
+            f"{multi_dataset_facets[self.cfg['group_variables_by']]} "
+            f"[{multi_dataset_facets['units']}]"
+        )
         z_coord = cube.coord(axis='Z')
         axes.set_ylabel(f'{z_coord.long_name} [{z_coord.units}]')
 
@@ -1597,13 +1612,13 @@ def create_1d_profile_plot(self, datasets, short_name):
 
     def compute(self):
         """Plot preprocessed data."""
-        for (short_name, datasets) in self.grouped_input_data.items():
-            logger.info("Processing variable %s", short_name)
-            self.create_timeseries_plot(datasets, short_name)
-            self.create_annual_cycle_plot(datasets, short_name)
-            self.create_map_plot(datasets, short_name)
-            self.create_zonal_mean_profile_plot(datasets, short_name)
-            self.create_1d_profile_plot(datasets, short_name)
+        for (var_key, datasets) in self.grouped_input_data.items():
+            logger.info("Processing variable %s", var_key)
+            self.create_timeseries_plot(datasets)
+            self.create_annual_cycle_plot(datasets)
+            self.create_map_plot(datasets)
+            self.create_zonal_mean_profile_plot(datasets)
+            self.create_1d_profile_plot(datasets)
 
 
 def main():

From eb9ed85d39509c0d51557b4a68288240ed9124db Mon Sep 17 00:00:00 2001
From: ellensarauer <143390753+ellensarauer@users.noreply.github.com>
Date: Wed, 6 Sep 2023 16:52:49 +0200
Subject: [PATCH 40/93] Extended monitor diagnostic with plot type variable vs.
 latitude (#3340)

Co-authored-by: Ellen Sarauer <b309246@levante0.lvt.dkrz.de>
Co-authored-by: Ellen Sarauer <b309246@levante2.lvt.dkrz.de>
Co-authored-by: Ellen Sarauer <b309246@levante3.lvt.dkrz.de>
Co-authored-by: Manuel Schlund <32543114+schlunma@users.noreply.github.com>
Co-authored-by: Manuel Schlund <manuel.schlund@dlr.de>
---
 .zenodo.json                                  |   4 +
 CITATION.cff                                  |   4 +
 .../monitor/variable_vs_lat_with_ref.png      | Bin 0 -> 166402 bytes
 doc/sphinx/source/recipes/recipe_monitor.rst  |   7 ++
 esmvaltool/config-references.yml              |   5 +
 .../diag_scripts/monitor/multi_datasets.py    | 118 +++++++++++++++++-
 .../monitor/recipe_monitor_with_refs.yml      |  24 +++-
 7 files changed, 159 insertions(+), 3 deletions(-)
 create mode 100644 doc/sphinx/source/recipes/figures/monitor/variable_vs_lat_with_ref.png

diff --git a/.zenodo.json b/.zenodo.json
index 083fa51356..aca2f05a12 100644
--- a/.zenodo.json
+++ b/.zenodo.json
@@ -263,6 +263,10 @@
             "affiliation": "CICERO, Norway",
             "name": "Sandstad, Marit"
         },
+        {
+            "affiliation": "DLR, Germany",
+            "name": "Sarauer, Ellen"
+        },
         {
             "affiliation": "MetOffice, UK",
             "name": "Sellar, Alistair"
diff --git a/CITATION.cff b/CITATION.cff
index 49226a7fda..ffda318cdb 100644
--- a/CITATION.cff
+++ b/CITATION.cff
@@ -300,6 +300,10 @@ authors:
     family-names: Weigel
     given-names: Katja
     orcid: "https://orcid.org/0000-0001-6133-7801"
+  -
+    affiliation: "DLR, Germany"
+    family-names: Sarauer
+    given-names: Ellen
   -
     affiliation: "University of Reading, UK"
     family-names: Roberts
diff --git a/doc/sphinx/source/recipes/figures/monitor/variable_vs_lat_with_ref.png b/doc/sphinx/source/recipes/figures/monitor/variable_vs_lat_with_ref.png
new file mode 100644
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HcmV?d00001

diff --git a/doc/sphinx/source/recipes/recipe_monitor.rst b/doc/sphinx/source/recipes/recipe_monitor.rst
index 0358ec36a7..fa3899cde6 100644
--- a/doc/sphinx/source/recipes/recipe_monitor.rst
+++ b/doc/sphinx/source/recipes/recipe_monitor.rst
@@ -210,3 +210,10 @@ Zonal mean profile of ta including a reference dataset.
    :width:   14cm
 
 1D profile of ta including a reference dataset.
+
+.. _fig_variable_vs_lat_with_ref:
+.. figure::  /recipes/figures/monitor/variable_vs_lat_with_ref.png
+   :align:   center
+   :width:   14cm
+
+1D profile of pr over latitude.
diff --git a/esmvaltool/config-references.yml b/esmvaltool/config-references.yml
index baaaa44c96..a36e6d7d38 100644
--- a/esmvaltool/config-references.yml
+++ b/esmvaltool/config-references.yml
@@ -446,6 +446,11 @@ authors:
     name: Sandstad, Marit
     institute: Cicero, Norway
     orcid:
+  sarauer_ellen:
+    name: Sarauer, Ellen
+    institute: DLR, Germany
+    orcid:
+    github: ellensarauer
   serva_federico:
     name: Serva, Federico
     institute: CNR, Italy
diff --git a/esmvaltool/diag_scripts/monitor/multi_datasets.py b/esmvaltool/diag_scripts/monitor/multi_datasets.py
index c6bda52e81..6fcedd9470 100644
--- a/esmvaltool/diag_scripts/monitor/multi_datasets.py
+++ b/esmvaltool/diag_scripts/monitor/multi_datasets.py
@@ -32,6 +32,10 @@
       can use the preprocessors :func:`esmvalcore.preprocessor.regrid` and
       :func:`esmvalcore.preprocessor.extract_levels` for this). Input data
       needs to be 2D with dimensions `latitude`, `height`/`air_pressure`.
+    - Variable vs. latitude plot (plot type ``variable_vs_lat``):
+      for each variable separately, all datasets are plotted in one
+      single figure. Input data needs to be 1D with single
+      dimension `latitude`.
 
       .. warning::
 
@@ -355,6 +359,35 @@
 show_y_minor_ticklabels: bool, optional (default: False)
     Show tick labels for the minor ticks on the Y axis.
 
+Configuration options for plot type ``variable_vs_lat``
+-------------------------------------------------------
+gridline_kwargs: dict, optional
+    Optional keyword arguments for grid lines. By default, ``color: lightgrey,
+    alpha: 0.5`` are used. Use ``gridline_kwargs: false`` to not show grid
+    lines.
+legend_kwargs: dict, optional
+    Optional keyword arguments for :func:`matplotlib.pyplot.legend`. Use
+    ``legend_kwargs: false`` to not show legends.
+plot_kwargs: dict, optional
+    Optional keyword arguments for :func:`iris.plot.plot`. Dictionary keys are
+    elements identified by ``facet_used_for_labels`` or ``default``, e.g.,
+    ``CMIP6`` if ``facet_used_for_labels: project`` or ``historical`` if
+    ``facet_used_for_labels: exp``. Dictionary values are dictionaries used as
+    keyword arguments for :func:`iris.plot.plot`. String arguments can include
+    facets in curly brackets which will be derived from the corresponding
+    dataset, e.g., ``{project}``, ``{short_name}``, ``{exp}``. Examples:
+    ``default: {linestyle: '-', label: '{project}'}, CMIP6: {color: red,
+    linestyle: '--'}, OBS: {color: black}``.
+pyplot_kwargs: dict, optional
+    Optional calls to functions of :mod:`matplotlib.pyplot`. Dictionary keys
+    are functions of :mod:`matplotlib.pyplot`. Dictionary values are used as
+    single argument for these functions. String arguments can include facets in
+    curly brackets which will be derived from the datasets plotted in the
+    corresponding plot, e.g., ``{short_name}``, ``{exp}``. Facets like
+    ``{project}`` that vary between the different datasets will be transformed
+    to something like  ``ambiguous_project``. Examples: ``title: 'Awesome Plot
+    of {long_name}'``, ``xlabel: '{short_name}'``, ``xlim: [0, 5]``.
+
 .. hint::
 
    Extra arguments given to the recipe are ignored, so it is safe to use yaml
@@ -442,7 +475,8 @@ def __init__(self, config):
             'annual_cycle',
             'map',
             'zonal_mean_profile',
-            '1d_profile'
+            '1d_profile',
+            'variable_vs_lat',
         ]
         for (plot_type, plot_options) in self.plots.items():
             if plot_type not in self.supported_plot_types:
@@ -535,6 +569,11 @@ def __init__(self, config):
                 self.plots[plot_type].setdefault(
                     'show_y_minor_ticklabels', False
                 )
+            if plot_type == 'variable_vs_lat':
+                self.plots[plot_type].setdefault('gridline_kwargs', {})
+                self.plots[plot_type].setdefault('legend_kwargs', {})
+                self.plots[plot_type].setdefault('plot_kwargs', {})
+                self.plots[plot_type].setdefault('pyplot_kwargs', {})
 
         # Check that facet_used_for_labels is present for every dataset
         for dataset in self.input_data:
@@ -763,7 +802,8 @@ def _get_plot_kwargs(self, plot_type, dataset, bias=False):
                 plot_kwargs[key] = val
 
         # Default settings for different plot types
-        if plot_type in ('timeseries', 'annual_cycle', '1d_profile'):
+        if plot_type in ('timeseries', 'annual_cycle', '1d_profile',
+                         'variable_vs_lat'):
             plot_kwargs.setdefault('label', label)
 
         return deepcopy(plot_kwargs)
@@ -1137,6 +1177,7 @@ def _check_cube_dimensions(cube, plot_type):
             'timeseries': (['time'],),
             '1d_profile': (['air_pressure'],
                            ['altitude']),
+            'variable_vs_lat': (['latitude'],),
 
         }
         if plot_type not in expected_dimensions_dict:
@@ -1190,6 +1231,78 @@ def _get_reference_dataset(self, datasets):
             return ref_datasets[0]
         return None
 
+    def create_variable_vs_lat_plot(self, datasets):
+        """Create Variable as a function of latitude."""
+        plot_type = 'variable_vs_lat'
+        if plot_type not in self.plots:
+            return
+        if not datasets:
+            raise ValueError(f"No input data to plot '{plot_type}' given")
+        logger.info("Plotting %s", plot_type)
+        fig = plt.figure(**self.cfg['figure_kwargs'])
+        axes = fig.add_subplot()
+
+        # Plot all datasets in one single figure
+        ancestors = []
+        cubes = {}
+        for dataset in datasets:
+            ancestors.append(dataset['filename'])
+            cube = dataset['cube']
+            cubes[self._get_label(dataset)] = cube
+            self._check_cube_dimensions(cube, plot_type)
+
+            # Plot data
+            plot_kwargs = self._get_plot_kwargs(plot_type, dataset)
+            plot_kwargs['axes'] = axes
+            iris.plot.plot(cube, **plot_kwargs)
+
+        # Default plot appearance
+        multi_dataset_facets = self._get_multi_dataset_facets(datasets)
+        axes.set_title(multi_dataset_facets['long_name'])
+        axes.set_xlabel('latitude [°N]')
+        axes.set_ylabel(
+            f"{multi_dataset_facets[self.cfg['group_variables_by']]} "
+            f"[{multi_dataset_facets['units']}]"
+        )
+        gridline_kwargs = self._get_gridline_kwargs(plot_type)
+        if gridline_kwargs is not False:
+            axes.grid(**gridline_kwargs)
+
+        # Legend
+        legend_kwargs = self.plots[plot_type]['legend_kwargs']
+        if legend_kwargs is not False:
+            axes.legend(**legend_kwargs)
+
+        # Customize plot appearance
+        self._process_pyplot_kwargs(plot_type, multi_dataset_facets)
+
+        # Save plot
+        plot_path = self.get_plot_path(plot_type, multi_dataset_facets)
+        fig.savefig(plot_path, **self.cfg['savefig_kwargs'])
+        logger.info("Wrote %s", plot_path)
+        plt.close()
+
+        # Save netCDF file
+        netcdf_path = get_diagnostic_filename(Path(plot_path).stem, self.cfg)
+        var_attrs = {
+            n: datasets[0][n] for n in ('short_name', 'long_name', 'units')
+        }
+        io.save_1d_data(cubes, netcdf_path, 'latitude', var_attrs)
+
+        # Provenance tracking
+        caption = (f"{multi_dataset_facets['long_name']} vs. latitude for "
+                   f"various datasets.")
+        provenance_record = {
+            'ancestors': ancestors,
+            'authors': ['sarauer_ellen'],
+            'caption': caption,
+            'plot_types': ['line'],
+            'long_names': [var_attrs['long_name']],
+        }
+        with ProvenanceLogger(self.cfg) as provenance_logger:
+            provenance_logger.log(plot_path, provenance_record)
+            provenance_logger.log(netcdf_path, provenance_record)
+
     def create_timeseries_plot(self, datasets):
         """Create time series plot."""
         plot_type = 'timeseries'
@@ -1619,6 +1732,7 @@ def compute(self):
             self.create_map_plot(datasets)
             self.create_zonal_mean_profile_plot(datasets)
             self.create_1d_profile_plot(datasets)
+            self.create_variable_vs_lat_plot(datasets)
 
 
 def main():
diff --git a/esmvaltool/recipes/monitor/recipe_monitor_with_refs.yml b/esmvaltool/recipes/monitor/recipe_monitor_with_refs.yml
index 0d1415979a..b75d84df3e 100644
--- a/esmvaltool/recipes/monitor/recipe_monitor_with_refs.yml
+++ b/esmvaltool/recipes/monitor/recipe_monitor_with_refs.yml
@@ -17,7 +17,6 @@ datasets:
   - {project: CMIP6, dataset: EC-Earth3, exp: historical, ensemble: r1i1p1f1, grid: gr, plot_label: 'EC-Earth3 historical'}
   - {project: CMIP6, dataset: CanESM5,   exp: historical, ensemble: r1i1p1f1, grid: gn, plot_label: 'Reference (CanESM5 historical)', reference_for_monitor_diags: true}
 
-
 preprocessors:
 
   timeseries_regular:
@@ -67,6 +66,16 @@ preprocessors:
       scheme: linear
       coordinate: air_pressure
 
+  var_vs_lat:
+    climate_statistics:
+      operator: mean
+    regrid:
+      target_grid: 2x2
+      scheme:
+        reference: esmf_regrid.schemes:ESMFAreaWeighted
+    zonal_statistics:
+      operator: mean
+
 
 diagnostics:
 
@@ -168,3 +177,16 @@ diagnostics:
                 color: C0
               CanESM5:
                 color: black
+
+  plot_variable_vs_latitude:
+    description: Creates a single-panel variable plot over latitude.
+    variables:
+      pr:
+        preprocessor: var_vs_lat
+        mip: Amon
+        timerange: '20000101/20030101'
+    scripts:
+      plot:
+        script: monitor/multi_datasets.py
+        plots:
+          variable_vs_lat:

From f9c7e4afdd5038a2273d85f5896882caecd7c4f6 Mon Sep 17 00:00:00 2001
From: Paulinebonnet111 <123577048+Paulinebonnet111@users.noreply.github.com>
Date: Wed, 6 Sep 2023 17:15:24 +0200
Subject: [PATCH 41/93] Add Pauline Bonnet to citation (#3347)

Co-authored-by: Lukas <lukas@uni-bremen.de>
---
 .zenodo.json                     | 5 +++++
 CITATION.cff                     | 5 +++++
 esmvaltool/config-references.yml | 5 +++++
 3 files changed, 15 insertions(+)

diff --git a/.zenodo.json b/.zenodo.json
index aca2f05a12..348d2aa80f 100644
--- a/.zenodo.json
+++ b/.zenodo.json
@@ -86,6 +86,11 @@
             "name": "Bock, Lisa",
             "orcid": "0000-0001-7058-5938"
         },
+        {
+            "affiliation": "DLR, Germany",
+            "name": "Bonnet, Pauline",
+            "orcid": "0000-0003-3780-0784"
+        },
         {
             "affiliation": "BSC, Spain",
             "name": "Caron, Louis-Philippe",
diff --git a/CITATION.cff b/CITATION.cff
index ffda318cdb..64378d61ce 100644
--- a/CITATION.cff
+++ b/CITATION.cff
@@ -358,6 +358,11 @@ authors:
     family-names: Beucher
     given-names: Romain
     orcid: "https://orcid.org/0000-0003-3891-5444"
+  -
+    affiliation: "DLR, Germany"
+    family-names: Bonnet
+    given-names: Pauline
+    orcid: "https://orcid.org/0000-0003-3780-0784"
 
 cff-version: 1.2.0
 date-released: 2023-07-06
diff --git a/esmvaltool/config-references.yml b/esmvaltool/config-references.yml
index a36e6d7d38..fe28d612b5 100644
--- a/esmvaltool/config-references.yml
+++ b/esmvaltool/config-references.yml
@@ -124,6 +124,11 @@ authors:
     name: Bojovic, Dragana
     institute: BSC, Spain
     orcid: https://orcid.org/0000-0001-7354-1885
+  bonnet_pauline:
+    name: Bonnet, Pauline
+    institute: DLR, Germany
+    orcid: https://orcid.org/0000-0003-3780-0784
+    github: Paulinebonnet111
   brunner_lukas:
     name: Brunner, Lukas
     institute: ETH Zurich, Switzerland

From 41acdb3120a858e2b4b29a27127da796c93e9780 Mon Sep 17 00:00:00 2001
From: cubeme <cubeme@users.noreply.github.com>
Date: Thu, 7 Sep 2023 12:22:43 +0200
Subject: [PATCH 42/93] Add Hovmoeller Z vs. time plot to monitoring diagnostic
 (for Changelog v2.10: authors: @cubeme and @helgehr) (#3345)

Co-authored-by: Helge Heuer <helge.heuer@dlr.de>
Co-authored-by: helgehr <38046421+helgehr@users.noreply.github.com>
Co-authored-by: Manuel Schlund <32543114+schlunma@users.noreply.github.com>
Co-authored-by: Manuel Schlund <manuel.schlund@dlr.de>
---
 .zenodo.json                                  |   9 +
 CITATION.cff                                  |   9 +
 .../monitor/hovmoeller_z_vs_time_with_ref.png | Bin 0 -> 89153 bytes
 doc/sphinx/source/recipes/recipe_monitor.rst  |   9 +-
 esmvaltool/config-references.yml              |  10 +
 .../diag_scripts/monitor/multi_datasets.py    | 430 +++++++++++++++++-
 .../monitor/recipe_monitor_with_refs.yml      |  57 ++-
 7 files changed, 497 insertions(+), 27 deletions(-)
 create mode 100755 doc/sphinx/source/recipes/figures/monitor/hovmoeller_z_vs_time_with_ref.png

diff --git a/.zenodo.json b/.zenodo.json
index 348d2aa80f..df129dfcd1 100644
--- a/.zenodo.json
+++ b/.zenodo.json
@@ -181,6 +181,11 @@
             "name": "Hassler, Birgit",
             "orcid": "0000-0003-2724-709X"
         },
+        {
+            "affiliation": "DLR, Germany",
+            "name": "Heuer, Helge",
+            "orcid": "0000-0003-2411-7150"
+        },
         {
             "affiliation": "BSC, Spain",
             "name": "Hunter, Alasdair",
@@ -199,6 +204,10 @@
             "affiliation": "MPI for Biogeochemistry, Germany",
             "name": "Koirala, Sujan"
         },
+        {
+            "affiliation": "DLR, Germany",
+            "name": "Kuehbacher, Birgit"
+        },
         {
             "affiliation": "BSC, Spain",
             "name": "Lledó, Llorenç"
diff --git a/CITATION.cff b/CITATION.cff
index 64378d61ce..b9c77159f8 100644
--- a/CITATION.cff
+++ b/CITATION.cff
@@ -181,6 +181,11 @@ authors:
     family-names: Hassler
     given-names: Birgit
     orcid: "https://orcid.org/0000-0003-2724-709X"
+  -
+    affiliation: "DLR, Germany"
+    family-names: Heuer
+    given-names: Helge
+    orcid: "https://orcid.org/0000-0003-2411-7150"
   -
     affiliation: "BSC, Spain"
     family-names: Hunter
@@ -199,6 +204,10 @@ authors:
     affiliation: "MPI for Biogeochemistry, Germany"
     family-names: Koirala
     given-names: Sujan
+  -
+    affiliation: "DLR, Germany"
+    family-names: Kuehbacher
+    given-names: Birgit
   -
     affiliation: "BSC, Spain"
     family-names: Lledó
diff --git a/doc/sphinx/source/recipes/figures/monitor/hovmoeller_z_vs_time_with_ref.png b/doc/sphinx/source/recipes/figures/monitor/hovmoeller_z_vs_time_with_ref.png
new file mode 100755
index 0000000000000000000000000000000000000000..734913c60b9c28abbca5c43c154a57daa0e8b6eb
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diff --git a/doc/sphinx/source/recipes/recipe_monitor.rst b/doc/sphinx/source/recipes/recipe_monitor.rst
index fa3899cde6..87ac9d0b17 100644
--- a/doc/sphinx/source/recipes/recipe_monitor.rst
+++ b/doc/sphinx/source/recipes/recipe_monitor.rst
@@ -216,4 +216,11 @@ Zonal mean profile of ta including a reference dataset.
    :align:   center
    :width:   14cm
 
-1D profile of pr over latitude.
+Zonal mean pr including a reference dataset.
+
+.. _fig_hovmoeller_z_vs_time_with_ref:
+.. figure::  /recipes/figures/monitor/hovmoeller_z_vs_time_with_ref.png
+   :align:   center
+   :width:   14cm
+
+Hovmoeller plot (pressure vs time) of ta including a reference dataset.
diff --git a/esmvaltool/config-references.yml b/esmvaltool/config-references.yml
index fe28d612b5..8ad8bc1a50 100644
--- a/esmvaltool/config-references.yml
+++ b/esmvaltool/config-references.yml
@@ -257,6 +257,11 @@ authors:
     name: Hempelmann, Nils
     institute: IPSL, France
     orcid:
+  heuer_helge:
+    name: Heuer, Helge
+    institute: DLR, Germany
+    email: helge.heuer@dlr.de
+    orcid: https://orcid.org/0000-0003-2411-7150
   hogan_emma:
     name: Hogan, Emma
     institute: MetOffice, UK
@@ -297,6 +302,11 @@ authors:
     name: Krasting, John
     institute: NOAA, USA
     orcid: https://orcid.org/0000-0002-4650-9844
+  kuehbacher_birgit:
+    name: Kuehbacher, Birgit
+    institute: DLR, Germany
+    email: birgit.kuehbacher@dlr.de
+    orcid:
   lejeune_quentin:
     name: Lejeune, Quentin
     institute: Climate Analytics, Germany
diff --git a/esmvaltool/diag_scripts/monitor/multi_datasets.py b/esmvaltool/diag_scripts/monitor/multi_datasets.py
index 6fcedd9470..2f4bce5176 100644
--- a/esmvaltool/diag_scripts/monitor/multi_datasets.py
+++ b/esmvaltool/diag_scripts/monitor/multi_datasets.py
@@ -31,11 +31,7 @@
       datasets need to be given on the same horizontal and vertical grid (you
       can use the preprocessors :func:`esmvalcore.preprocessor.regrid` and
       :func:`esmvalcore.preprocessor.extract_levels` for this). Input data
-      needs to be 2D with dimensions `latitude`, `height`/`air_pressure`.
-    - Variable vs. latitude plot (plot type ``variable_vs_lat``):
-      for each variable separately, all datasets are plotted in one
-      single figure. Input data needs to be 1D with single
-      dimension `latitude`.
+      needs to be 2D with dimensions `latitude`, `altitude`/`air_pressure`.
 
       .. warning::
 
@@ -46,7 +42,19 @@
 
     - 1D profiles (plot type ``1d_profile``): for each variable separately, all
       datasets are plotted in one single figure. Input data needs to be 1D with
-      single dimension `height` / `air_pressure`
+      single dimension `altitude` / `air_pressure`
+    - Variable vs. latitude plot (plot type ``variable_vs_lat``):
+      for each variable separately, all datasets are plotted in one
+      single figure. Input data needs to be 1D with single
+      dimension `latitude`.
+    - Hovmoeller Z vs. time (plot type ``hovmoeller_z_vs_time``): for each
+      variable and dataset, an individual profile is plotted. If a reference
+      dataset is defined, also include this dataset and a bias plot into the
+      figure. Note that if a reference dataset is defined, all input datasets
+      need to be given on the same temporal and vertical grid (you can use
+      the preprocessors :func:`esmvalcore.preprocessor.regrid_time` and
+      :func:`esmvalcore.preprocessor.extract_levels` for this). Input data
+      needs to be 2D with dimensions `time`, `altitude`/`air_pressure`.
 
 Author
 ------
@@ -69,8 +77,8 @@
     individual plot is created.
 plots: dict, optional
     Plot types plotted by this diagnostic (see list above). Dictionary keys
-    must be ``timeseries``, ``annual_cycle``, ``map``, ``zonal_mean_profile``
-    or ``1d_profile``.
+    must be ``timeseries``, ``annual_cycle``, ``map``, ``zonal_mean_profile``,
+    ``1d_profile``, ``variable_vs_lat``, or ``hovmoeller_z_vs_time``.
     Dictionary values are dictionaries used as options for the corresponding
     plot. The allowed options for the different plot types are given below.
 plot_filename: str, optional
@@ -126,6 +134,10 @@
     ``{project}`` that vary between the different datasets will be transformed
     to something like  ``ambiguous_project``. Examples: ``title: 'Awesome Plot
     of {long_name}'``, ``xlabel: '{short_name}'``, ``xlim: [0, 5]``.
+time_format: str, optional (default: None)
+    :func:`~datetime.datetime.strftime` format string that is used to format
+    the time axis using :class:`matplotlib.dates.DateFormatter`. If ``None``,
+    use the default formatting imposed by the iris plotting function.
 
 Configuration options for plot type ``annual_cycle``
 ----------------------------------------------------
@@ -277,7 +289,7 @@
 plot_func: str, optional (default: 'contourf')
     Plot function used to plot the profiles. Must be a function of
     :mod:`iris.plot` that supports plotting of 2D cubes with coordinates
-    latitude and height/air_pressure.
+    latitude and altitude/air_pressure.
 plot_kwargs: dict, optional
     Optional keyword arguments for the plot function defined by ``plot_func``.
     Dictionary keys are elements identified by ``facet_used_for_labels`` or
@@ -388,6 +400,88 @@
     to something like  ``ambiguous_project``. Examples: ``title: 'Awesome Plot
     of {long_name}'``, ``xlabel: '{short_name}'``, ``xlim: [0, 5]``.
 
+Configuration options for plot type ``hovmoeller_z_vs_time``
+------------------------------------------------------------
+cbar_label: str, optional (default: '{short_name} [{units}]')
+    Colorbar label. Can include facets in curly brackets which will be derived
+    from the corresponding dataset, e.g., ``{project}``, ``{short_name}``,
+    ``{exp}``.
+cbar_label_bias: str, optional (default: 'Δ{short_name} [{units}]')
+    Colorbar label for plotting biases. Can include facets in curly brackets
+    which will be derived from the corresponding dataset, e.g., ``{project}``,
+    ``{short_name}``, ``{exp}``. This option has no effect if no reference
+    dataset is given.
+cbar_kwargs: dict, optional
+    Optional keyword arguments for :func:`matplotlib.pyplot.colorbar`. By
+    default, uses ``orientation: vertical``.
+cbar_kwargs_bias: dict, optional
+    Optional keyword arguments for :func:`matplotlib.pyplot.colorbar` for
+    plotting biases. These keyword arguments update (and potentially overwrite)
+    the ``cbar_kwargs`` for the bias plot. This option has no effect if no
+    reference dataset is given.
+common_cbar: bool, optional (default: False)
+    Use a common colorbar for the top panels (i.e., plots of the dataset and
+    the corresponding reference dataset) when using a reference dataset. If
+    neither ``vmin`` and ``vmix`` nor ``levels`` is given in ``plot_kwargs``,
+    the colorbar bounds are inferred from the dataset in the top left panel,
+    which might lead to an inappropriate colorbar for the reference dataset
+    (top right panel). Thus, the use of the ``plot_kwargs`` ``vmin`` and
+    ``vmax`` or ``levels`` is highly recommend when using this ``common_cbar:
+    true``. This option has no effect if no reference dataset is given.
+fontsize: int, optional (default: 10)
+    Fontsize used for ticks, labels and titles. For the latter, use the given
+    fontsize plus 2. Does not affect suptitles.
+log_y: bool, optional (default: True)
+    Use logarithmic Y-axis.
+plot_func: str, optional (default: 'contourf')
+    Plot function used to plot the profiles. Must be a function of
+    :mod:`iris.plot` that supports plotting of 2D cubes with coordinates
+    latitude and altitude/air_pressure.
+plot_kwargs: dict, optional
+    Optional keyword arguments for the plot function defined by ``plot_func``.
+    Dictionary keys are elements identified by ``facet_used_for_labels`` or
+    ``default``, e.g., ``CMIP6`` if ``facet_used_for_labels: project`` or
+    ``historical`` if ``facet_used_for_labels: exp``. Dictionary values are
+    dictionaries used as keyword arguments for the plot function defined by
+    ``plot_func``. String arguments can include facets in curly brackets which
+    will be derived from the corresponding dataset, e.g., ``{project}``,
+    ``{short_name}``, ``{exp}``. Examples: ``default: {levels: 2}, CMIP6:
+    {vmin: 200, vmax: 250}``.
+plot_kwargs_bias: dict, optional
+    Optional keyword arguments for the plot function defined by ``plot_func``
+    for plotting biases. These keyword arguments update (and potentially
+    overwrite) the ``plot_kwargs`` for the bias plot. This option has no effect
+    if no reference dataset is given. See option ``plot_kwargs`` for more
+    details. By default, uses ``cmap: bwr``.
+pyplot_kwargs: dict, optional
+    Optional calls to functions of :mod:`matplotlib.pyplot`. Dictionary keys
+    are functions of :mod:`matplotlib.pyplot`. Dictionary values are used as
+    single argument for these functions. String arguments can include facets in
+    curly brackets which will be derived from the corresponding dataset, e.g.,
+    ``{project}``, ``{short_name}``, ``{exp}``.  Examples: ``title: 'Awesome
+    Plot of {long_name}'``, ``xlabel: '{short_name}'``, ``xlim: [0, 5]``.
+rasterize: bool, optional (default: True)
+    If ``True``, use `rasterization
+    <https://matplotlib.org/stable/gallery/misc/rasterization_demo.html>`_ for
+    profile plots to produce smaller files. This is only relevant for vector
+    graphics (e.g., ``output_file_type=pdf,svg,ps``).
+show_stats: bool, optional (default: True)
+    Show basic statistics on the plots.
+show_y_minor_ticklabels: bool, optional (default: False)
+    Show tick labels for the minor ticks on the Y axis.
+x_pos_stats_avg: float, optional (default: 0.01)
+    Text x-position of average (shown on the left) in Axes coordinates. Can be
+    adjusted to avoid overlap with the figure. Only relevant if ``show_stats:
+    true``.
+x_pos_stats_bias: float, optional (default: 0.7)
+    Text x-position of bias statistics (shown on the right) in Axes
+    coordinates. Can be adjusted to avoid overlap with the figure. Only
+    relevant if ``show_stats: true``.
+time_format: str, optional (default: None)
+    :func:`~datetime.datetime.strftime` format string that is used to format
+    the time axis using :class:`matplotlib.dates.DateFormatter`. If ``None``,
+    use the default formatting imposed by the iris plotting function.
+
 .. hint::
 
    Extra arguments given to the recipe are ignored, so it is safe to use yaml
@@ -403,6 +497,7 @@
 import cartopy.crs as ccrs
 import iris
 import matplotlib as mpl
+import matplotlib.dates as mdates
 import matplotlib.pyplot as plt
 import numpy as np
 import seaborn as sns
@@ -476,7 +571,8 @@ def __init__(self, config):
             'map',
             'zonal_mean_profile',
             '1d_profile',
-            'variable_vs_lat',
+            'hovmoeller_z_vs_time',
+            'variable_vs_lat'
         ]
         for (plot_type, plot_options) in self.plots.items():
             if plot_type not in self.supported_plot_types:
@@ -493,6 +589,7 @@ def __init__(self, config):
                 self.plots[plot_type].setdefault('legend_kwargs', {})
                 self.plots[plot_type].setdefault('plot_kwargs', {})
                 self.plots[plot_type].setdefault('pyplot_kwargs', {})
+                self.plots[plot_type].setdefault('time_format', None)
 
             if plot_type == 'annual_cycle':
                 self.plots[plot_type].setdefault('gridline_kwargs', {})
@@ -575,6 +672,31 @@ def __init__(self, config):
                 self.plots[plot_type].setdefault('plot_kwargs', {})
                 self.plots[plot_type].setdefault('pyplot_kwargs', {})
 
+            if plot_type == 'hovmoeller_z_vs_time':
+                self.plots[plot_type].setdefault('cbar_label',
+                                                 '{short_name} [{units}]')
+                self.plots[plot_type].setdefault('cbar_label_bias',
+                                                 'Δ{short_name} [{units}]')
+                self.plots[plot_type].setdefault('cbar_kwargs',
+                                                 {'orientation': 'vertical'})
+                self.plots[plot_type].setdefault('cbar_kwargs_bias', {})
+                self.plots[plot_type].setdefault('common_cbar', False)
+                self.plots[plot_type].setdefault('fontsize', 10)
+                self.plots[plot_type].setdefault('log_y', True)
+                self.plots[plot_type].setdefault('plot_func', 'contourf')
+                self.plots[plot_type].setdefault('plot_kwargs', {})
+                self.plots[plot_type].setdefault('plot_kwargs_bias', {})
+                self.plots[plot_type]['plot_kwargs_bias'].setdefault(
+                    'cmap', 'bwr')
+                self.plots[plot_type].setdefault('pyplot_kwargs', {})
+                self.plots[plot_type].setdefault('rasterize', True)
+                self.plots[plot_type].setdefault('show_stats', True)
+                self.plots[plot_type].setdefault('show_y_minor_ticklabels',
+                                                 False)
+                self.plots[plot_type].setdefault('time_format', None)
+                self.plots[plot_type].setdefault('x_pos_stats_avg', 0.01)
+                self.plots[plot_type].setdefault('x_pos_stats_bias', 0.7)
+
         # Check that facet_used_for_labels is present for every dataset
         for dataset in self.input_data:
             if self.cfg['facet_used_for_labels'] not in dataset:
@@ -632,10 +754,10 @@ def _add_stats(self, plot_type, axes, dim_coords, dataset,
         # Different options for the different plots types
         fontsize = 6.0
         y_pos = 0.95
-        if plot_type == 'map':
-            x_pos_bias = self.plots[plot_type]['x_pos_stats_bias']
-            x_pos = self.plots[plot_type]['x_pos_stats_avg']
-        elif plot_type in ['zonal_mean_profile']:
+        if all([
+                'x_pos_stats_avg' in self.plots[plot_type],
+                'x_pos_stats_bias' in self.plots[plot_type],
+        ]):
             x_pos_bias = self.plots[plot_type]['x_pos_stats_bias']
             x_pos = self.plots[plot_type]['x_pos_stats_avg']
         else:
@@ -868,6 +990,7 @@ def _plot_map_with_ref(self, plot_func, dataset, ref_dataset):
                 axes_data.gridlines(**gridline_kwargs)
             axes_data.set_title(self._get_label(dataset), pad=3.0)
             self._add_stats(plot_type, axes_data, dim_coords_dat, dataset)
+            self._process_pyplot_kwargs(plot_type, dataset)
 
             # Plot reference dataset (top right)
             # Note: make sure to use the same vmin and vmax than the top left
@@ -884,6 +1007,7 @@ def _plot_map_with_ref(self, plot_func, dataset, ref_dataset):
                 axes_ref.gridlines(**gridline_kwargs)
             axes_ref.set_title(self._get_label(ref_dataset), pad=3.0)
             self._add_stats(plot_type, axes_ref, dim_coords_ref, ref_dataset)
+            self._process_pyplot_kwargs(plot_type, ref_dataset)
 
             # Add colorbar(s)
             self._add_colorbar(plot_type, plot_data, plot_ref, axes_data,
@@ -1027,6 +1151,7 @@ def _plot_zonal_mean_profile_with_ref(self, plot_func, dataset,
             else:
                 axes_data.get_yaxis().set_minor_formatter(NullFormatter())
             self._add_stats(plot_type, axes_data, dim_coords_dat, dataset)
+            self._process_pyplot_kwargs(plot_type, dataset)
 
             # Plot reference dataset (top right)
             # Note: make sure to use the same vmin and vmax than the top left
@@ -1041,6 +1166,7 @@ def _plot_zonal_mean_profile_with_ref(self, plot_func, dataset,
             axes_ref.set_title(self._get_label(ref_dataset), pad=3.0)
             plt.setp(axes_ref.get_yticklabels(), visible=False)
             self._add_stats(plot_type, axes_ref, dim_coords_ref, ref_dataset)
+            self._process_pyplot_kwargs(plot_type, ref_dataset)
 
             # Add colorbar(s)
             self._add_colorbar(plot_type, plot_data, plot_ref, axes_data,
@@ -1151,6 +1277,196 @@ def _plot_zonal_mean_profile_without_ref(self, plot_func, dataset):
 
         return (plot_path, {netcdf_path: cube})
 
+    def _plot_hovmoeller_z_vs_time_without_ref(self, plot_func, dataset):
+        """Plot Hovmoeller Z vs. time for single dataset without reference."""
+        plot_type = 'hovmoeller_z_vs_time'
+        logger.info(
+            "Plotting Hovmoeller Z vs. time without reference dataset"
+            " for '%s'", self._get_label(dataset))
+
+        # Make sure that the data has the correct dimensions
+        cube = dataset['cube']
+        dim_coords_dat = self._check_cube_dimensions(cube, plot_type)
+
+        time_coord = cube.coord(axis='T')
+
+        # Create plot with desired settings
+        with mpl.rc_context(self._get_custom_mpl_rc_params(plot_type)):
+            fig = plt.figure(**self.cfg['figure_kwargs'])
+            axes = fig.add_subplot()
+            plot_kwargs = self._get_plot_kwargs(plot_type, dataset)
+            plot_kwargs['axes'] = axes
+            plot_hovmoeller = plot_func(cube, **plot_kwargs)
+
+            # Print statistics if desired
+            self._add_stats(plot_type, axes, dim_coords_dat, dataset)
+
+            # Setup colorbar
+            fontsize = self.plots[plot_type]['fontsize']
+            colorbar = fig.colorbar(plot_hovmoeller,
+                                    ax=axes,
+                                    **self._get_cbar_kwargs(plot_type))
+            colorbar.set_label(self._get_cbar_label(plot_type, dataset),
+                               fontsize=fontsize)
+            colorbar.ax.tick_params(labelsize=fontsize)
+
+            # Customize plot
+            axes.set_title(self._get_label(dataset))
+            fig.suptitle(f"{dataset['long_name']} ({dataset['start_year']}-"
+                         f"{dataset['end_year']})")
+            z_coord = cube.coord(axis='Z')
+            axes.set_ylabel(f'{z_coord.long_name} [{z_coord.units}]')
+            if self.plots[plot_type]['log_y']:
+                axes.set_yscale('log')
+                axes.get_yaxis().set_major_formatter(
+                    FormatStrFormatter('%.1f'))
+            if self.plots[plot_type]['show_y_minor_ticklabels']:
+                axes.get_yaxis().set_minor_formatter(
+                    FormatStrFormatter('%.1f'))
+            else:
+                axes.get_yaxis().set_minor_formatter(NullFormatter())
+            if self.plots[plot_type]['time_format'] is not None:
+                axes.get_xaxis().set_major_formatter(
+                    mdates.DateFormatter(self.plots[plot_type]['time_format']))
+            axes.set_xlabel(f'{time_coord.long_name}')
+            self._process_pyplot_kwargs(plot_type, dataset)
+
+            # Rasterization
+            if self.plots[plot_type]['rasterize']:
+                self._set_rasterized([axes])
+
+        # File paths
+        plot_path = self.get_plot_path(plot_type, dataset)
+        netcdf_path = get_diagnostic_filename(Path(plot_path).stem, self.cfg)
+
+        return (plot_path, {netcdf_path: cube})
+
+    def _plot_hovmoeller_z_vs_time_with_ref(self, plot_func, dataset,
+                                            ref_dataset):
+        """Plot Hovmoeller Z vs. time for single dataset with reference."""
+        plot_type = 'hovmoeller_z_vs_time'
+        logger.info(
+            "Plotting Hovmoeller z vs. time with reference dataset"
+            " '%s' for '%s'", self._get_label(ref_dataset),
+            self._get_label(dataset))
+
+        # Make sure that the data has the correct dimensions
+        cube = dataset['cube']
+        ref_cube = ref_dataset['cube']
+        dim_coords_dat = self._check_cube_dimensions(cube, plot_type)
+        dim_coords_ref = self._check_cube_dimensions(ref_cube, plot_type)
+
+        time_coord = cube.coord(axis='T')
+
+        # Create single figure with multiple axes
+        with mpl.rc_context(self._get_custom_mpl_rc_params(plot_type)):
+            fig = plt.figure(**self.cfg['figure_kwargs'])
+            gridspec = GridSpec(5,
+                                4,
+                                figure=fig,
+                                height_ratios=[1.0, 1.0, 0.4, 1.0, 1.0])
+
+            # Options used for all subplots
+            plot_kwargs = self._get_plot_kwargs(plot_type, dataset)
+            fontsize = self.plots[plot_type]['fontsize']
+
+            # Plot dataset (top left)
+            axes_data = fig.add_subplot(gridspec[0:2, 0:2])
+            plot_kwargs['axes'] = axes_data
+            plot_data = plot_func(cube, **plot_kwargs)
+            axes_data.set_title(self._get_label(dataset), pad=3.0)
+            z_coord = cube.coord(axis='Z')
+            axes_data.set_ylabel(f'{z_coord.long_name} [{z_coord.units}]')
+            if self.plots[plot_type]['log_y']:
+                axes_data.set_yscale('log')
+                axes_data.get_yaxis().set_major_formatter(
+                    FormatStrFormatter('%.1f'))
+            if self.plots[plot_type]['show_y_minor_ticklabels']:
+                axes_data.get_yaxis().set_minor_formatter(
+                    FormatStrFormatter('%.1f'))
+            else:
+                axes_data.get_yaxis().set_minor_formatter(NullFormatter())
+            if self.plots[plot_type]['time_format'] is not None:
+                axes_data.get_xaxis().set_major_formatter(
+                    mdates.DateFormatter(self.plots[plot_type]['time_format']))
+            self._add_stats(plot_type, axes_data, dim_coords_dat, dataset)
+            self._process_pyplot_kwargs(plot_type, dataset)
+
+            # Plot reference dataset (top right)
+            # Note: make sure to use the same vmin and vmax than the top left
+            # plot if a common colorbar is desired
+            axes_ref = fig.add_subplot(gridspec[0:2, 2:4],
+                                       sharex=axes_data,
+                                       sharey=axes_data)
+            plot_kwargs['axes'] = axes_ref
+            if self.plots[plot_type]['common_cbar']:
+                plot_kwargs.setdefault('vmin', plot_data.get_clim()[0])
+                plot_kwargs.setdefault('vmax', plot_data.get_clim()[1])
+            plot_ref = plot_func(ref_cube, **plot_kwargs)
+            axes_ref.set_title(self._get_label(ref_dataset), pad=3.0)
+            plt.setp(axes_ref.get_yticklabels(), visible=False)
+            if self.plots[plot_type]['time_format'] is not None:
+                axes_ref.get_xaxis().set_major_formatter(
+                    mdates.DateFormatter(self.plots[plot_type]['time_format']))
+            self._add_stats(plot_type, axes_ref, dim_coords_ref, ref_dataset)
+            self._process_pyplot_kwargs(plot_type, ref_dataset)
+
+            # Add colorbar(s)
+            self._add_colorbar(plot_type, plot_data, plot_ref, axes_data,
+                               axes_ref, dataset, ref_dataset)
+
+            # Plot bias (bottom center)
+            bias_cube = cube - ref_cube
+            axes_bias = fig.add_subplot(gridspec[3:5, 1:3],
+                                        sharex=axes_data,
+                                        sharey=axes_data)
+            plot_kwargs_bias = self._get_plot_kwargs(plot_type,
+                                                     dataset,
+                                                     bias=True)
+            plot_kwargs_bias['axes'] = axes_bias
+            plot_bias = plot_func(bias_cube, **plot_kwargs_bias)
+            axes_bias.set_title(
+                f"{self._get_label(dataset)} - {self._get_label(ref_dataset)}",
+                pad=3.0,
+            )
+            axes_bias.set_xlabel(time_coord.long_name)
+            axes_bias.set_ylabel(f'{z_coord.long_name} [{z_coord.units}]')
+            if self.plots[plot_type]['time_format'] is not None:
+                axes_bias.get_xaxis().set_major_formatter(
+                    mdates.DateFormatter(self.plots[plot_type]['time_format']))
+            cbar_kwargs_bias = self._get_cbar_kwargs(plot_type, bias=True)
+            cbar_bias = fig.colorbar(plot_bias,
+                                     ax=axes_bias,
+                                     **cbar_kwargs_bias)
+            cbar_bias.set_label(
+                self._get_cbar_label(plot_type, dataset, bias=True),
+                fontsize=fontsize,
+            )
+            cbar_bias.ax.tick_params(labelsize=fontsize)
+            self._add_stats(plot_type, axes_bias, dim_coords_dat, dataset,
+                            ref_dataset)
+
+            # Customize plot
+            fig.suptitle(f"{dataset['long_name']} ({dataset['start_year']}-"
+                         f"{dataset['end_year']})")
+            self._process_pyplot_kwargs(plot_type, dataset)
+
+            # Rasterization
+            if self.plots[plot_type]['rasterize']:
+                self._set_rasterized([axes_data, axes_ref, axes_bias])
+
+        # File paths
+        plot_path = self.get_plot_path(plot_type, dataset)
+        netcdf_path = (get_diagnostic_filename(
+            Path(plot_path).stem + "_{pos}", self.cfg))
+        netcdf_paths = {
+            netcdf_path.format(pos='top_left'): cube,
+            netcdf_path.format(pos='top_right'): ref_cube,
+            netcdf_path.format(pos='bottom'): bias_cube,
+        }
+
+        return (plot_path, netcdf_paths)
+
     def _process_pyplot_kwargs(self, plot_type, dataset):
         """Process functions for :mod:`matplotlib.pyplot`."""
         pyplot_kwargs = self.plots[plot_type]['pyplot_kwargs']
@@ -1177,8 +1493,9 @@ def _check_cube_dimensions(cube, plot_type):
             'timeseries': (['time'],),
             '1d_profile': (['air_pressure'],
                            ['altitude']),
-            'variable_vs_lat': (['latitude'],),
-
+            'hovmoeller_z_vs_time': (['time', 'air_pressure'],
+                                     ['time', 'altitude']),
+            'variable_vs_lat': (['latitude'],)
         }
         if plot_type not in expected_dimensions_dict:
             raise NotImplementedError(f"plot_type '{plot_type}' not supported")
@@ -1346,6 +1663,10 @@ def create_timeseries_plot(self, datasets):
         multi_dataset_facets = self._get_multi_dataset_facets(datasets)
         axes.set_title(multi_dataset_facets['long_name'])
         axes.set_xlabel('Time')
+        # apply time formatting
+        if self.plots[plot_type]['time_format'] is not None:
+            axes.get_xaxis().set_major_formatter(
+                mdates.DateFormatter(self.plots[plot_type]['time_format']))
         axes.set_ylabel(
             f"{multi_dataset_facets[self.cfg['group_variables_by']]} "
             f"[{multi_dataset_facets['units']}]"
@@ -1723,6 +2044,82 @@ def create_1d_profile_plot(self, datasets):
             provenance_logger.log(plot_path, provenance_record)
             provenance_logger.log(netcdf_path, provenance_record)
 
+    def create_hovmoeller_z_vs_time_plot(self, datasets):
+        """Create Hovmoeller Z vs. time plot."""
+        plot_type = 'hovmoeller_z_vs_time'
+        if plot_type not in self.plots:
+            return
+
+        if not datasets:
+            raise ValueError(f"No input data to plot '{plot_type}' given")
+
+        # Get reference dataset if possible
+        ref_dataset = self._get_reference_dataset(datasets)
+        if ref_dataset is None:
+            logger.info("Plotting %s without reference dataset", plot_type)
+        else:
+            logger.info("Plotting %s with reference dataset '%s'", plot_type,
+                        self._get_label(ref_dataset))
+
+        # Get plot function
+        plot_func = self._get_plot_func(plot_type)
+
+        # Create a single plot for each dataset (incl. reference dataset if
+        # given)
+        for dataset in datasets:
+            if dataset == ref_dataset:
+                continue
+            ancestors = [dataset['filename']]
+            if ref_dataset is None:
+                (plot_path,
+                 netcdf_paths) = (self._plot_hovmoeller_z_vs_time_without_ref(
+                     plot_func, dataset))
+                caption = (
+                    f"Hovmoeller Z vs. time plot of {dataset['long_name']} "
+                    f"of dataset "
+                    f"{dataset['dataset']} (project {dataset['project']}) "
+                    f"from {dataset['start_year']} to {dataset['end_year']}.")
+            else:
+                (plot_path,
+                 netcdf_paths) = (self._plot_hovmoeller_z_vs_time_with_ref(
+                     plot_func, dataset, ref_dataset))
+                caption = (
+                    f"Hovmoeller Z vs. time plot of {dataset['long_name']} "
+                    f"of dataset "
+                    f"{dataset['dataset']} (project {dataset['project']}) "
+                    f"including bias relative to {ref_dataset['dataset']} "
+                    f"(project {ref_dataset['project']}) from "
+                    f"{dataset['start_year']} to {dataset['end_year']}.")
+                ancestors.append(ref_dataset['filename'])
+
+            # If statistics are shown add a brief description to the caption
+            if self.plots[plot_type]['show_stats']:
+                caption += (
+                    " The number in the top left corner corresponds to the "
+                    "spatiotemporal mean.")
+
+            # Save plot
+            plt.savefig(plot_path, **self.cfg['savefig_kwargs'])
+            logger.info("Wrote %s", plot_path)
+            plt.close()
+
+            # Save netCDFs
+            for (netcdf_path, cube) in netcdf_paths.items():
+                io.iris_save(cube, netcdf_path)
+
+            # Provenance tracking
+            provenance_record = {
+                'ancestors': ancestors,
+                'authors': ['kuehbacher_birgit', 'heuer_helge'],
+                'caption': caption,
+                'plot_types': ['vert'],
+                'long_names': [dataset['long_name']],
+            }
+            with ProvenanceLogger(self.cfg) as provenance_logger:
+                provenance_logger.log(plot_path, provenance_record)
+                for netcdf_path in netcdf_paths:
+                    provenance_logger.log(netcdf_path, provenance_record)
+
     def compute(self):
         """Plot preprocessed data."""
         for (var_key, datasets) in self.grouped_input_data.items():
@@ -1733,6 +2130,7 @@ def compute(self):
             self.create_zonal_mean_profile_plot(datasets)
             self.create_1d_profile_plot(datasets)
             self.create_variable_vs_lat_plot(datasets)
+            self.create_hovmoeller_z_vs_time_plot(datasets)
 
 
 def main():
diff --git a/esmvaltool/recipes/monitor/recipe_monitor_with_refs.yml b/esmvaltool/recipes/monitor/recipe_monitor_with_refs.yml
index b75d84df3e..3db01e6a4a 100644
--- a/esmvaltool/recipes/monitor/recipe_monitor_with_refs.yml
+++ b/esmvaltool/recipes/monitor/recipe_monitor_with_refs.yml
@@ -8,14 +8,17 @@ documentation:
   authors:
     - schlund_manuel
     - winterstein_franziska
+    - sarauer_ellen
+    - kuehbacher_birgit
+    - heuer_helge
   maintainer:
     - schlund_manuel
 
 
 datasets:
   # Note: plot_label currently only used by diagnostic plot_multiple_annual_cycles
-  - {project: CMIP6, dataset: EC-Earth3, exp: historical, ensemble: r1i1p1f1, grid: gr, plot_label: 'EC-Earth3 historical'}
-  - {project: CMIP6, dataset: CanESM5,   exp: historical, ensemble: r1i1p1f1, grid: gn, plot_label: 'Reference (CanESM5 historical)', reference_for_monitor_diags: true}
+  - {project: CMIP6, dataset: MPI-ESM1-2-HR, exp: historical, ensemble: r1i1p1f1, grid: gn, plot_label: 'MPI-ESM1-2-HR historical'}
+  - {project: CMIP6, dataset: MPI-ESM1-2-LR, exp: historical, ensemble: r1i1p1f1, grid: gn, plot_label: 'Reference (MPI-ESM1-2-LR historical)', reference_for_monitor_diags: true}
 
 preprocessors:
 
@@ -71,10 +74,23 @@ preprocessors:
       operator: mean
     regrid:
       target_grid: 2x2
-      scheme:
-        reference: esmf_regrid.schemes:ESMFAreaWeighted
+      scheme: linear
     zonal_statistics:
       operator: mean
+    convert_units:
+      units: mm day-1
+
+  global_mean_extract_levels:
+    custom_order: true
+    extract_levels:
+      levels: {cmor_table: CMIP6, coordinate: alt16}
+      scheme: linear
+      coordinate: altitude
+    regrid:
+      target_grid: 2x2
+      scheme: linear
+    area_statistics:
+      operator: mean
 
 
 diagnostics:
@@ -96,9 +112,9 @@ diagnostics:
             annual_mean_kwargs:
               linestyle: '--'
             plot_kwargs:
-              EC-Earth3:  # = dataset since 'facet_used_for_labels' is 'dataset' by default
+              MPI-ESM1-2-HR:  # = dataset since 'facet_used_for_labels' is 'dataset' by default
                 color: C0
-              CanESM5:
+              MPI-ESM1-2-LR:
                 color: black
 
   plot_multiple_annual_cycles:
@@ -117,9 +133,9 @@ diagnostics:
             legend_kwargs:
               loc: upper right
             plot_kwargs:
-              'EC-Earth3 historical':  # = plot_label since 'facet_used_for_labels: plot_label'
+              'MPI-ESM1-2-HR historical':  # = plot_label since 'facet_used_for_labels: plot_label'
                 color: C0
-              'Reference (CanESM5 historical)':
+              'Reference (MPI-ESM1-2-LR historical)':
                 color: black
             pyplot_kwargs:
               title: Near-Surface Air Temperature on Northern Hemisphere
@@ -173,9 +189,9 @@ diagnostics:
         plots:
           1d_profile:
             plot_kwargs:
-              EC-Earth3:  # = dataset since 'facet_used_for_labels' is 'dataset' by default
+              MPI-ESM1-2-HR:  # = dataset since 'facet_used_for_labels' is 'dataset' by default
                 color: C0
-              CanESM5:
+              MPI-ESM1-2-LR:
                 color: black
 
   plot_variable_vs_latitude:
@@ -187,6 +203,27 @@ diagnostics:
         timerange: '20000101/20030101'
     scripts:
       plot:
+        <<: *plot_multi_dataset_default
         script: monitor/multi_datasets.py
         plots:
           variable_vs_lat:
+
+  plot_hovmoeller_z_vs_time:
+    description: Plot Hovmoeller Z vs. time including reference datasets.
+    variables:
+      ta:
+        preprocessor: global_mean_extract_levels
+        mip: Amon
+        timerange: '2000/2004'
+    scripts:
+      plot:
+        <<: *plot_multi_dataset_default
+        script: monitor/multi_datasets.py
+        plots:
+          hovmoeller_z_vs_time:
+            plot_func: contourf
+            common_cbar: true
+            time_format: '%Y'
+            log_y: false
+            pyplot_kwargs:
+              ylim: [0, 20000]

From a8071476ee34cb3a75276754473db35d39806eda Mon Sep 17 00:00:00 2001
From: Lukas <lukas@uni-bremen.de>
Date: Thu, 7 Sep 2023 17:38:11 +0200
Subject: [PATCH 43/93] Adding Hovmoeller time vs latlon plots to monitoring
 recipes (for Changelog v2.10: authors: @lukruh and @jeremykraftdlr) (#3341)

Co-authored-by: Jeremy Kraft <jeremy.kraft@dlr.de>
Co-authored-by: helgehr <38046421+helgehr@users.noreply.github.com>
Co-authored-by: Manuel Schlund <manuel.schlund@dlr.de>
---
 .zenodo.json                                  |   9 +
 CITATION.cff                                  |   9 +
 .../hovmoeller_time_vs_lat_with_ref.png       | Bin 0 -> 108200 bytes
 doc/sphinx/source/recipes/recipe_monitor.rst  |   9 +-
 esmvaltool/config-references.yml              |   5 +
 .../diag_scripts/monitor/multi_datasets.py    | 547 ++++++++++++++----
 .../monitor/recipe_monitor_with_refs.yml      |  34 +-
 7 files changed, 510 insertions(+), 103 deletions(-)
 create mode 100644 doc/sphinx/source/recipes/figures/monitor/hovmoeller_time_vs_lat_with_ref.png

diff --git a/.zenodo.json b/.zenodo.json
index df129dfcd1..43d9d2638a 100644
--- a/.zenodo.json
+++ b/.zenodo.json
@@ -356,6 +356,15 @@
             "affiliation": "DLR, Germany",
             "name": "Kazeroni, Rémi",
             "orcid": "0000-0001-7205-9528"
+        },
+        {
+            "affiliation": "DLR, Germany",
+            "name": "Kraft, Jeremy"
+        },
+        {
+            "affiliation": "University of Bremen, Germany",
+            "name": "Ruhe, Lukas",
+            "orcid": "0000-0001-6349-9118"
         }
     ],
     "description": "ESMValTool: A community diagnostic and performance metrics tool for routine evaluation of Earth system models in CMIP.",
diff --git a/CITATION.cff b/CITATION.cff
index b9c77159f8..b6f6d45f77 100644
--- a/CITATION.cff
+++ b/CITATION.cff
@@ -367,6 +367,15 @@ authors:
     family-names: Beucher
     given-names: Romain
     orcid: "https://orcid.org/0000-0003-3891-5444"
+  -
+    affiliation: "DLR, Germany"
+    family-names: Kraft
+    given-names: Jeremy
+  -
+    affiliation: "University of Bremen, Germany"
+    family-names: Ruhe
+    given-names: Lukas
+    orcid: "https://orcid.org/0000-0001-6349-9118"
   -
     affiliation: "DLR, Germany"
     family-names: Bonnet
diff --git a/doc/sphinx/source/recipes/figures/monitor/hovmoeller_time_vs_lat_with_ref.png b/doc/sphinx/source/recipes/figures/monitor/hovmoeller_time_vs_lat_with_ref.png
new file mode 100644
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zcAXf^D#-(tjz1@sKrOMmZz)=Qco<w>QQ>53oBwkIXP+Ie5(Yy)YY_v#MNuFBh1(5I
zUk0@)Tnt7uu8jbLv1AA(!(iG(ap^Ib5G#0P4CW27>HmE|0MQ@qq;@NvVjK83jE1VV
K$_pjSu>S>;%4bpl

literal 0
HcmV?d00001

diff --git a/doc/sphinx/source/recipes/recipe_monitor.rst b/doc/sphinx/source/recipes/recipe_monitor.rst
index 87ac9d0b17..9bdfd5d40b 100644
--- a/doc/sphinx/source/recipes/recipe_monitor.rst
+++ b/doc/sphinx/source/recipes/recipe_monitor.rst
@@ -223,4 +223,11 @@ Zonal mean pr including a reference dataset.
    :align:   center
    :width:   14cm
 
-Hovmoeller plot (pressure vs time) of ta including a reference dataset.
+Hovmoeller plot (pressure vs. time) of ta including a reference dataset.
+
+.. _fig_hovmoeller_time_vs_lat_with_ref:
+.. figure:: /recipes/figures/monitor/hovmoeller_time_vs_lat_with_ref.png
+   :align:   center
+   :width:   14cm
+
+Hovmoeller plot (time vs. latitude) of tas including a reference dataset
diff --git a/esmvaltool/config-references.yml b/esmvaltool/config-references.yml
index 8ad8bc1a50..cea1a0561b 100644
--- a/esmvaltool/config-references.yml
+++ b/esmvaltool/config-references.yml
@@ -298,6 +298,11 @@ authors:
     name: Koirala, Sujan
     institute: MPI-BGC, Germany
     orcid: https://orcid.org/0000-0001-5681-1986
+  kraft_jeremy:
+    name: Kraft, Jeremy
+    institute: DLR, Germany
+    orcid:
+    github: jeremykraftdlr
   krasting_john:
     name: Krasting, John
     institute: NOAA, USA
diff --git a/esmvaltool/diag_scripts/monitor/multi_datasets.py b/esmvaltool/diag_scripts/monitor/multi_datasets.py
index 2f4bce5176..4299e2538c 100644
--- a/esmvaltool/diag_scripts/monitor/multi_datasets.py
+++ b/esmvaltool/diag_scripts/monitor/multi_datasets.py
@@ -48,13 +48,22 @@
       single figure. Input data needs to be 1D with single
       dimension `latitude`.
     - Hovmoeller Z vs. time (plot type ``hovmoeller_z_vs_time``): for each
-      variable and dataset, an individual profile is plotted. If a reference
+      variable and dataset, an individual figure is plotted. If a reference
       dataset is defined, also include this dataset and a bias plot into the
       figure. Note that if a reference dataset is defined, all input datasets
       need to be given on the same temporal and vertical grid (you can use
       the preprocessors :func:`esmvalcore.preprocessor.regrid_time` and
       :func:`esmvalcore.preprocessor.extract_levels` for this). Input data
       needs to be 2D with dimensions `time`, `altitude`/`air_pressure`.
+    - Hovmoeller time vs. latitude or longitude (plot type
+      ``hovmoeller_time_vs_lat_or_lon``): for each variable and dataset, an
+      individual figure is plotted. If a reference dataset is defined, also
+      include this dataset and a bias plot into the figure. Note that if a
+      reference dataset is defined, all input datasets need to be given on the
+      same temporal and horizontal grid (you can use the preprocessors
+      :func:`esmvalcore.preprocessor.regrid_time` and
+      :func:`esmvalcore.preprocessor.regrid` for this). Input data
+      needs to be 2D with dimensions `time`, `latitude`/`longitude`.
 
 Author
 ------
@@ -78,9 +87,10 @@
 plots: dict, optional
     Plot types plotted by this diagnostic (see list above). Dictionary keys
     must be ``timeseries``, ``annual_cycle``, ``map``, ``zonal_mean_profile``,
-    ``1d_profile``, ``variable_vs_lat``, or ``hovmoeller_z_vs_time``.
-    Dictionary values are dictionaries used as options for the corresponding
-    plot. The allowed options for the different plot types are given below.
+    ``1d_profile``, ``variable_vs_lat``, ``hovmoeller_z_vs_time``,
+    ``hovmoeller_time_vs_lat_or_lon``. Dictionary values are dictionaries used
+    as options for the corresponding plot. The allowed options for the
+    different plot types are given below.
 plot_filename: str, optional
     Filename pattern for the plots.
     Defaults to ``{plot_type}_{real_name}_{dataset}_{mip}_{exp}_{ensemble}``.
@@ -482,6 +492,78 @@
     the time axis using :class:`matplotlib.dates.DateFormatter`. If ``None``,
     use the default formatting imposed by the iris plotting function.
 
+Configuration options for plot type ``hovmoeller_time_vs_lat_or_lon``
+---------------------------------------------------------------------
+cbar_label: str, optional (default: '{short_name} [{units}]')
+    Colorbar label. Can include facets in curly brackets which will be derived
+    from the corresponding dataset, e.g., ``{project}``, ``{short_name}``,
+    ``{exp}``.
+cbar_label_bias: str, optional (default: 'Δ{short_name} [{units}]')
+    Colorbar label for plotting biases. Can include facets in curly brackets
+    which will be derived from the corresponding dataset, e.g., ``{project}``,
+    ``{short_name}``, ``{exp}``. This option has no effect if no reference
+    dataset is given.
+cbar_kwargs: dict, optional
+    Optional keyword arguments for :func:`matplotlib.pyplot.colorbar`. By
+    default, uses ``orientation: vertical``.
+cbar_kwargs_bias: dict, optional
+    Optional keyword arguments for :func:`matplotlib.pyplot.colorbar` for
+    plotting biases. These keyword arguments update (and potentially overwrite)
+    the ``cbar_kwargs`` for the bias plot. This option has no effect if no
+    reference dataset is given.
+common_cbar: bool, optional (default: False)
+    Use a common colorbar for the top panels (i.e., plots of the dataset and
+    the corresponding reference dataset) when using a reference dataset. If
+    neither ``vmin`` and ``vmix`` nor ``levels`` is given in ``plot_kwargs``,
+    the colorbar bounds are inferred from the dataset in the top left panel,
+    which might lead to an inappropriate colorbar for the reference dataset
+    (top right panel). Thus, the use of the ``plot_kwargs`` ``vmin`` and
+    ``vmax`` or ``levels`` is highly recommend when using this ``common_cbar:
+    true``. This option has no effect if no reference dataset is given.
+fontsize: int, optional (default: 10)
+    Fontsize used for ticks, labels and titles. For the latter, use the given
+    fontsize plus 2. Does not affect suptitles.
+plot_func: str, optional (default: 'contourf')
+    Plot function used to plot the profiles. Must be a function of
+    :mod:`iris.plot` that supports plotting of 2D cubes with coordinates
+    latitude and height/air_pressure.
+plot_kwargs: dict, optional
+    Optional keyword arguments for the plot function defined by ``plot_func``.
+    Dictionary keys are elements identified by ``facet_used_for_labels`` or
+    ``default``, e.g., ``CMIP6`` if ``facet_used_for_labels: project`` or
+    ``historical`` if ``facet_used_for_labels: exp``. Dictionary values are
+    dictionaries used as keyword arguments for the plot function defined by
+    ``plot_func``. String arguments can include facets in curly brackets which
+    will be derived from the corresponding dataset, e.g., ``{project}``,
+    ``{short_name}``, ``{exp}``. Examples: ``default: {levels: 2}, CMIP6:
+    {vmin: 200, vmax: 250}``.
+plot_kwargs_bias: dict, optional
+    Optional keyword arguments for the plot function defined by ``plot_func``
+    for plotting biases. These keyword arguments update (and potentially
+    overwrite) the ``plot_kwargs`` for the bias plot. This option has no effect
+    if no reference dataset is given. See option ``plot_kwargs`` for more
+    details. By default, uses ``cmap: bwr``.
+pyplot_kwargs: dict, optional
+    Optional calls to functions of :mod:`matplotlib.pyplot`. Dictionary keys
+    are functions of :mod:`matplotlib.pyplot`. Dictionary values are used as
+    single argument for these functions. String arguments can include facets in
+    curly brackets which will be derived from the corresponding dataset, e.g.,
+    ``{project}``, ``{short_name}``, ``{exp}``.  Examples: ``title: 'Awesome
+    Plot of {long_name}'``, ``xlabel: '{short_name}'``, ``xlim: [0, 5]``.
+rasterize: bool, optional (default: False)
+    If ``True``, use `rasterization
+    <https://matplotlib.org/stable/gallery/misc/rasterization_demo.html>`_ for
+    profile plots to produce smaller files. This is only relevant for vector
+    graphics (e.g., ``output_file_type=pdf,svg,ps``).
+show_y_minor_ticks: bool, optional (default: True)
+    Show minor ticks for time on the Y axis.
+show_x_minor_ticks: bool, optional (default: True)
+    Show minor ticks for latitude or longitude on the X axis.
+time_format: str, optional (default: None)
+    :func:`~datetime.datetime.strftime` format string that is used to format
+    the time axis using :class:`matplotlib.dates.DateFormatter`. If ``None``,
+    use the default formatting imposed by the iris plotting function.
+
 .. hint::
 
    Extra arguments given to the recipe are ignored, so it is safe to use yaml
@@ -505,7 +587,12 @@
 from iris.coord_categorisation import add_year
 from iris.coords import AuxCoord
 from matplotlib.gridspec import GridSpec
-from matplotlib.ticker import FormatStrFormatter, LogLocator, NullFormatter
+from matplotlib.ticker import (
+    AutoMinorLocator,
+    FormatStrFormatter,
+    LogLocator,
+    NullFormatter,
+)
 from sklearn.metrics import r2_score
 
 import esmvaltool.diag_scripts.shared.iris_helpers as ih
@@ -528,7 +615,7 @@ def __init__(self, config):
         """Initialize class member."""
         super().__init__(config)
 
-        # Get default stettings
+        # Get default settings
         self.cfg = deepcopy(self.cfg)
         self.cfg.setdefault('facet_used_for_labels', 'dataset')
         self.cfg.setdefault('figure_kwargs', {'constrained_layout': True})
@@ -571,8 +658,9 @@ def __init__(self, config):
             'map',
             'zonal_mean_profile',
             '1d_profile',
+            'variable_vs_lat',
             'hovmoeller_z_vs_time',
-            'variable_vs_lat'
+            'hovmoeller_time_vs_lat_or_lon',
         ]
         for (plot_type, plot_options) in self.plots.items():
             if plot_type not in self.supported_plot_types:
@@ -591,13 +679,13 @@ def __init__(self, config):
                 self.plots[plot_type].setdefault('pyplot_kwargs', {})
                 self.plots[plot_type].setdefault('time_format', None)
 
-            if plot_type == 'annual_cycle':
+            elif plot_type == 'annual_cycle':
                 self.plots[plot_type].setdefault('gridline_kwargs', {})
                 self.plots[plot_type].setdefault('legend_kwargs', {})
                 self.plots[plot_type].setdefault('plot_kwargs', {})
                 self.plots[plot_type].setdefault('pyplot_kwargs', {})
 
-            if plot_type == 'map':
+            elif plot_type == 'map':
                 self.plots[plot_type].setdefault(
                     'cbar_label', '{short_name} [{units}]')
                 self.plots[plot_type].setdefault(
@@ -628,7 +716,7 @@ def __init__(self, config):
                 self.plots[plot_type].setdefault('x_pos_stats_avg', 0.0)
                 self.plots[plot_type].setdefault('x_pos_stats_bias', 0.92)
 
-            if plot_type == 'zonal_mean_profile':
+            elif plot_type == 'zonal_mean_profile':
                 self.plots[plot_type].setdefault(
                     'cbar_label', '{short_name} [{units}]')
                 self.plots[plot_type].setdefault(
@@ -655,7 +743,7 @@ def __init__(self, config):
                 self.plots[plot_type].setdefault('x_pos_stats_avg', 0.01)
                 self.plots[plot_type].setdefault('x_pos_stats_bias', 0.7)
 
-            if plot_type == '1d_profile':
+            elif plot_type == '1d_profile':
                 self.plots[plot_type].setdefault('aspect_ratio', 1.5)
                 self.plots[plot_type].setdefault('gridline_kwargs', {})
                 self.plots[plot_type].setdefault('legend_kwargs', {})
@@ -666,13 +754,13 @@ def __init__(self, config):
                 self.plots[plot_type].setdefault(
                     'show_y_minor_ticklabels', False
                 )
-            if plot_type == 'variable_vs_lat':
+            elif plot_type == 'variable_vs_lat':
                 self.plots[plot_type].setdefault('gridline_kwargs', {})
                 self.plots[plot_type].setdefault('legend_kwargs', {})
                 self.plots[plot_type].setdefault('plot_kwargs', {})
                 self.plots[plot_type].setdefault('pyplot_kwargs', {})
 
-            if plot_type == 'hovmoeller_z_vs_time':
+            elif plot_type == 'hovmoeller_z_vs_time':
                 self.plots[plot_type].setdefault('cbar_label',
                                                  '{short_name} [{units}]')
                 self.plots[plot_type].setdefault('cbar_label_bias',
@@ -697,6 +785,33 @@ def __init__(self, config):
                 self.plots[plot_type].setdefault('x_pos_stats_avg', 0.01)
                 self.plots[plot_type].setdefault('x_pos_stats_bias', 0.7)
 
+            elif plot_type == 'hovmoeller_time_vs_lat_or_lon':
+                self.plots[plot_type].setdefault(
+                    'cbar_label', '{short_name} [{units}]')
+                self.plots[plot_type].setdefault(
+                    'cbar_label_bias', 'Δ{short_name} [{units}]')
+                self.plots[plot_type].setdefault(
+                    'cbar_kwargs', {'orientation': 'vertical'}
+                )
+                self.plots[plot_type].setdefault('cbar_kwargs_bias', {})
+                self.plots[plot_type].setdefault('common_cbar', False)
+                self.plots[plot_type].setdefault('fontsize', 10)
+                self.plots[plot_type].setdefault('plot_func', 'contourf')
+                self.plots[plot_type].setdefault('plot_kwargs', {})
+                self.plots[plot_type].setdefault('plot_kwargs_bias', {})
+                self.plots[plot_type]['plot_kwargs_bias'].setdefault(
+                    'cmap', 'bwr'
+                )
+                self.plots[plot_type].setdefault('pyplot_kwargs', {})
+                self.plots[plot_type].setdefault('rasterize', False)
+                self.plots[plot_type].setdefault(
+                    'show_y_minor_ticks', True
+                )
+                self.plots[plot_type].setdefault(
+                    'show_x_minor_ticks', True
+                )
+                self.plots[plot_type].setdefault('time_format', None)
+
         # Check that facet_used_for_labels is present for every dataset
         for dataset in self.input_data:
             if self.cfg['facet_used_for_labels'] not in dataset:
@@ -1288,8 +1403,6 @@ def _plot_hovmoeller_z_vs_time_without_ref(self, plot_func, dataset):
         cube = dataset['cube']
         dim_coords_dat = self._check_cube_dimensions(cube, plot_type)
 
-        time_coord = cube.coord(axis='T')
-
         # Create plot with desired settings
         with mpl.rc_context(self._get_custom_mpl_rc_params(plot_type)):
             fig = plt.figure(**self.cfg['figure_kwargs'])
@@ -1328,7 +1441,7 @@ def _plot_hovmoeller_z_vs_time_without_ref(self, plot_func, dataset):
             if self.plots[plot_type]['time_format'] is not None:
                 axes.get_xaxis().set_major_formatter(
                     mdates.DateFormatter(self.plots[plot_type]['time_format']))
-            axes.set_xlabel(f'{time_coord.long_name}')
+            axes.set_xlabel('time')
             self._process_pyplot_kwargs(plot_type, dataset)
 
             # Rasterization
@@ -1356,8 +1469,6 @@ def _plot_hovmoeller_z_vs_time_with_ref(self, plot_func, dataset,
         dim_coords_dat = self._check_cube_dimensions(cube, plot_type)
         dim_coords_ref = self._check_cube_dimensions(ref_cube, plot_type)
 
-        time_coord = cube.coord(axis='T')
-
         # Create single figure with multiple axes
         with mpl.rc_context(self._get_custom_mpl_rc_params(plot_type)):
             fig = plt.figure(**self.cfg['figure_kwargs'])
@@ -1405,9 +1516,6 @@ def _plot_hovmoeller_z_vs_time_with_ref(self, plot_func, dataset,
             plot_ref = plot_func(ref_cube, **plot_kwargs)
             axes_ref.set_title(self._get_label(ref_dataset), pad=3.0)
             plt.setp(axes_ref.get_yticklabels(), visible=False)
-            if self.plots[plot_type]['time_format'] is not None:
-                axes_ref.get_xaxis().set_major_formatter(
-                    mdates.DateFormatter(self.plots[plot_type]['time_format']))
             self._add_stats(plot_type, axes_ref, dim_coords_ref, ref_dataset)
             self._process_pyplot_kwargs(plot_type, ref_dataset)
 
@@ -1429,11 +1537,8 @@ def _plot_hovmoeller_z_vs_time_with_ref(self, plot_func, dataset,
                 f"{self._get_label(dataset)} - {self._get_label(ref_dataset)}",
                 pad=3.0,
             )
-            axes_bias.set_xlabel(time_coord.long_name)
+            axes_bias.set_xlabel('time')
             axes_bias.set_ylabel(f'{z_coord.long_name} [{z_coord.units}]')
-            if self.plots[plot_type]['time_format'] is not None:
-                axes_bias.get_xaxis().set_major_formatter(
-                    mdates.DateFormatter(self.plots[plot_type]['time_format']))
             cbar_kwargs_bias = self._get_cbar_kwargs(plot_type, bias=True)
             cbar_bias = fig.colorbar(plot_bias,
                                      ax=axes_bias,
@@ -1467,6 +1572,174 @@ def _plot_hovmoeller_z_vs_time_with_ref(self, plot_func, dataset,
 
         return (plot_path, netcdf_paths)
 
+    def _plot_hovmoeller_time_vs_lat_or_lon_with_ref(self, plot_func, dataset,
+                                                     ref_dataset):
+        """Plot the hovmoeller profile for single dataset with reference."""
+        plot_type = 'hovmoeller_time_vs_lat_or_lon'
+        logger.info("Plotting Hovmoeller plots with reference dataset"
+                    " '%s' for '%s'",
+                    self._get_label(ref_dataset), self._get_label(dataset))
+
+        # Make sure that the data has the correct dimensions
+        cube = dataset['cube']
+        ref_cube = ref_dataset['cube']
+        dim_coords_dat = self._check_cube_dimensions(cube, plot_type)
+        self._check_cube_dimensions(ref_cube, plot_type)
+
+        # Create single figure with multiple axes
+        with mpl.rc_context(self._get_custom_mpl_rc_params(plot_type)):
+            fig = plt.figure(**self.cfg['figure_kwargs'])
+            gridspec = GridSpec(5, 4, figure=fig,
+                                height_ratios=[1.0, 1.0, 0.4, 1.0, 1.0])
+
+            # Options used for all subplots
+            plot_kwargs = self._get_plot_kwargs(plot_type, dataset)
+            fontsize = self.plots[plot_type]['fontsize']
+
+            # Plot dataset (top left)
+            axes_data = fig.add_subplot(gridspec[0:2, 0:2])
+            plot_kwargs['axes'] = axes_data
+            coord_names = [coord[0].name() for coord in cube.dim_coords]
+            if coord_names[0] == "time":
+                coord_names.reverse()
+            plot_kwargs['coords'] = coord_names
+            plot_data = plot_func(cube, **plot_kwargs)
+            axes_data.set_title(self._get_label(dataset), pad=3.0)
+            axes_data.set_ylabel('time')
+            if self.plots[plot_type]['time_format'] is not None:
+                axes_data.get_yaxis().set_major_formatter(mdates.DateFormatter(
+                    self.plots[plot_type]['time_format']))
+            if self.plots[plot_type]['show_y_minor_ticks']:
+                axes_data.get_yaxis().set_minor_locator(AutoMinorLocator())
+            if self.plots[plot_type]['show_x_minor_ticks']:
+                axes_data.get_xaxis().set_minor_locator(AutoMinorLocator())
+            self._process_pyplot_kwargs(plot_type, dataset)
+
+            # Plot reference dataset (top right)
+            # Note: make sure to use the same vmin and vmax than the top left
+            # plot if a common colorbar is desired
+            axes_ref = fig.add_subplot(gridspec[0:2, 2:4], sharex=axes_data,
+                                       sharey=axes_data)
+            plot_kwargs['axes'] = axes_ref
+            if self.plots[plot_type]['common_cbar']:
+                plot_kwargs.setdefault('vmin', plot_data.get_clim()[0])
+                plot_kwargs.setdefault('vmax', plot_data.get_clim()[1])
+            plot_ref = plot_func(ref_cube, **plot_kwargs)
+            axes_ref.set_title(self._get_label(ref_dataset), pad=3.0)
+            plt.setp(axes_ref.get_yticklabels(), visible=False)
+            self._process_pyplot_kwargs(plot_type, ref_dataset)
+
+            # Add colorbar(s)
+            self._add_colorbar(plot_type, plot_data, plot_ref, axes_data,
+                               axes_ref, dataset, ref_dataset)
+
+            # Plot bias (bottom center)
+            bias_cube = cube - ref_cube
+            axes_bias = fig.add_subplot(gridspec[3:5, 1:3], sharex=axes_data,
+                                        sharey=axes_data)
+            plot_kwargs_bias = self._get_plot_kwargs(plot_type, dataset,
+                                                     bias=True)
+            plot_kwargs_bias['axes'] = axes_bias
+            plot_kwargs_bias['coords'] = coord_names
+            plot_bias = plot_func(bias_cube, **plot_kwargs_bias)
+            axes_bias.set_title(
+                f"{self._get_label(dataset)} - {self._get_label(ref_dataset)}",
+                pad=3.0,
+            )
+            axes_bias.set_ylabel('time')
+            if 'latitude' in dim_coords_dat:
+                axes_bias.set_xlabel('latitude [°N]')
+            elif 'longitude' in dim_coords_dat:
+                axes_bias.set_xlabel('longitude [°E]')
+            cbar_kwargs_bias = self._get_cbar_kwargs(plot_type, bias=True)
+            cbar_bias = fig.colorbar(plot_bias, ax=axes_bias,
+                                     **cbar_kwargs_bias)
+            cbar_bias.set_label(
+                self._get_cbar_label(plot_type, dataset, bias=True),
+                fontsize=fontsize,
+            )
+            cbar_bias.ax.tick_params(labelsize=fontsize)
+
+            # Customize plot
+            fig.suptitle(f"{dataset['long_name']} ({dataset['start_year']}-"
+                         f"{dataset['end_year']})")
+            self._process_pyplot_kwargs(plot_type, dataset)
+
+            # Rasterization
+            if self.plots[plot_type]['rasterize']:
+                self._set_rasterized([axes_data, axes_ref, axes_bias])
+
+        # File paths
+        plot_path = self.get_plot_path(plot_type, dataset)
+        netcdf_path = (
+            get_diagnostic_filename(Path(plot_path).stem + "_{pos}", self.cfg)
+        )
+        netcdf_paths = {
+            netcdf_path.format(pos='top_left'): cube,
+            netcdf_path.format(pos='top_right'): ref_cube,
+            netcdf_path.format(pos='bottom'): bias_cube,
+        }
+
+        return (plot_path, netcdf_paths)
+
+    def _plot_hovmoeller_time_vs_lat_or_lon_without_ref(self, plot_func,
+                                                        dataset):
+        """Plot time vs zonal or meridional Hovmoeller without reference."""
+        plot_type = 'hovmoeller_time_vs_lat_or_lon'
+        logger.info("Plotting Hovmoeller plots without reference dataset"
+                    " for '%s'", self._get_label(dataset))
+
+        # Make sure that the data has the correct dimensions
+        cube = dataset['cube']
+        dim_coords_dat = self._check_cube_dimensions(cube, plot_type)
+
+        # Create plot with desired settings
+        with mpl.rc_context(self._get_custom_mpl_rc_params(plot_type)):
+            fig = plt.figure(**self.cfg['figure_kwargs'])
+            axes = fig.add_subplot()
+            plot_kwargs = self._get_plot_kwargs(plot_type, dataset)
+            plot_kwargs['axes'] = axes
+
+            # Make sure time is on y-axis
+            plot_kwargs['coords'] = list(reversed(dim_coords_dat))
+            plot_hovmoeller = plot_func(cube, **plot_kwargs)
+
+            # Setup colorbar
+            fontsize = self.plots[plot_type]['fontsize']
+            colorbar = fig.colorbar(plot_hovmoeller, ax=axes,
+                                    **self._get_cbar_kwargs(plot_type))
+            colorbar.set_label(self._get_cbar_label(plot_type, dataset),
+                               fontsize=fontsize)
+            colorbar.ax.tick_params(labelsize=fontsize)
+
+            # Customize plot
+            axes.set_title(self._get_label(dataset))
+            fig.suptitle(f"{dataset['long_name']} ({dataset['start_year']}-"
+                         f"{dataset['end_year']})")
+            if 'latitude' in dim_coords_dat:
+                axes.set_xlabel('latitude [°N]')
+            elif 'longitude' in dim_coords_dat:
+                axes.set_xlabel('longitude [°E]')
+            axes.set_ylabel('time')
+            if self.plots[plot_type]['time_format'] is not None:
+                axes.get_yaxis().set_major_formatter(mdates.DateFormatter(
+                    self.plots[plot_type]['time_format'])
+                )
+            if self.plots[plot_type]['show_y_minor_ticks']:
+                axes.get_yaxis().set_minor_locator(AutoMinorLocator())
+            if self.plots[plot_type]['show_x_minor_ticks']:
+                axes.get_xaxis().set_minor_locator(AutoMinorLocator())
+            self._process_pyplot_kwargs(plot_type, dataset)
+
+            # Rasterization
+            if self.plots[plot_type]['rasterize']:
+                self._set_rasterized([axes])
+
+        # File paths
+        plot_path = self.get_plot_path(plot_type, dataset)
+        netcdf_path = get_diagnostic_filename(Path(plot_path).stem, self.cfg)
+        return (plot_path, {netcdf_path: cube})
+
     def _process_pyplot_kwargs(self, plot_type, dataset):
         """Process functions for :mod:`matplotlib.pyplot`."""
         pyplot_kwargs = self.plots[plot_type]['pyplot_kwargs']
@@ -1493,9 +1766,11 @@ def _check_cube_dimensions(cube, plot_type):
             'timeseries': (['time'],),
             '1d_profile': (['air_pressure'],
                            ['altitude']),
+            'variable_vs_lat': (['latitude'],),
             'hovmoeller_z_vs_time': (['time', 'air_pressure'],
                                      ['time', 'altitude']),
-            'variable_vs_lat': (['latitude'],)
+            'hovmoeller_time_vs_lat_or_lon': (['time', 'latitude'],
+                                              ['time', 'longitude']),
         }
         if plot_type not in expected_dimensions_dict:
             raise NotImplementedError(f"plot_type '{plot_type}' not supported")
@@ -1548,78 +1823,6 @@ def _get_reference_dataset(self, datasets):
             return ref_datasets[0]
         return None
 
-    def create_variable_vs_lat_plot(self, datasets):
-        """Create Variable as a function of latitude."""
-        plot_type = 'variable_vs_lat'
-        if plot_type not in self.plots:
-            return
-        if not datasets:
-            raise ValueError(f"No input data to plot '{plot_type}' given")
-        logger.info("Plotting %s", plot_type)
-        fig = plt.figure(**self.cfg['figure_kwargs'])
-        axes = fig.add_subplot()
-
-        # Plot all datasets in one single figure
-        ancestors = []
-        cubes = {}
-        for dataset in datasets:
-            ancestors.append(dataset['filename'])
-            cube = dataset['cube']
-            cubes[self._get_label(dataset)] = cube
-            self._check_cube_dimensions(cube, plot_type)
-
-            # Plot data
-            plot_kwargs = self._get_plot_kwargs(plot_type, dataset)
-            plot_kwargs['axes'] = axes
-            iris.plot.plot(cube, **plot_kwargs)
-
-        # Default plot appearance
-        multi_dataset_facets = self._get_multi_dataset_facets(datasets)
-        axes.set_title(multi_dataset_facets['long_name'])
-        axes.set_xlabel('latitude [°N]')
-        axes.set_ylabel(
-            f"{multi_dataset_facets[self.cfg['group_variables_by']]} "
-            f"[{multi_dataset_facets['units']}]"
-        )
-        gridline_kwargs = self._get_gridline_kwargs(plot_type)
-        if gridline_kwargs is not False:
-            axes.grid(**gridline_kwargs)
-
-        # Legend
-        legend_kwargs = self.plots[plot_type]['legend_kwargs']
-        if legend_kwargs is not False:
-            axes.legend(**legend_kwargs)
-
-        # Customize plot appearance
-        self._process_pyplot_kwargs(plot_type, multi_dataset_facets)
-
-        # Save plot
-        plot_path = self.get_plot_path(plot_type, multi_dataset_facets)
-        fig.savefig(plot_path, **self.cfg['savefig_kwargs'])
-        logger.info("Wrote %s", plot_path)
-        plt.close()
-
-        # Save netCDF file
-        netcdf_path = get_diagnostic_filename(Path(plot_path).stem, self.cfg)
-        var_attrs = {
-            n: datasets[0][n] for n in ('short_name', 'long_name', 'units')
-        }
-        io.save_1d_data(cubes, netcdf_path, 'latitude', var_attrs)
-
-        # Provenance tracking
-        caption = (f"{multi_dataset_facets['long_name']} vs. latitude for "
-                   f"various datasets.")
-        provenance_record = {
-            'ancestors': ancestors,
-            'authors': ['sarauer_ellen'],
-            'caption': caption,
-            'plot_types': ['line'],
-            'long_names': [var_attrs['long_name']],
-        }
-        with ProvenanceLogger(self.cfg) as provenance_logger:
-            provenance_logger.log(plot_path, provenance_record)
-            provenance_logger.log(netcdf_path, provenance_record)
-
     def create_timeseries_plot(self, datasets):
         """Create time series plot."""
         plot_type = 'timeseries'
@@ -1662,7 +1865,7 @@ def create_timeseries_plot(self, datasets):
         # Default plot appearance
         multi_dataset_facets = self._get_multi_dataset_facets(datasets)
         axes.set_title(multi_dataset_facets['long_name'])
-        axes.set_xlabel('Time')
+        axes.set_xlabel('time')
         # apply time formatting
         if self.plots[plot_type]['time_format'] is not None:
             axes.get_xaxis().set_major_formatter(
@@ -2044,6 +2247,78 @@ def create_1d_profile_plot(self, datasets):
             provenance_logger.log(plot_path, provenance_record)
             provenance_logger.log(netcdf_path, provenance_record)
 
+    def create_variable_vs_lat_plot(self, datasets):
+        """Create Variable as a function of latitude."""
+        plot_type = 'variable_vs_lat'
+        if plot_type not in self.plots:
+            return
+        if not datasets:
+            raise ValueError(f"No input data to plot '{plot_type}' given")
+        logger.info("Plotting %s", plot_type)
+        fig = plt.figure(**self.cfg['figure_kwargs'])
+        axes = fig.add_subplot()
+
+        # Plot all datasets in one single figure
+        ancestors = []
+        cubes = {}
+        for dataset in datasets:
+            ancestors.append(dataset['filename'])
+            cube = dataset['cube']
+            cubes[self._get_label(dataset)] = cube
+            self._check_cube_dimensions(cube, plot_type)
+
+            # Plot data
+            plot_kwargs = self._get_plot_kwargs(plot_type, dataset)
+            plot_kwargs['axes'] = axes
+            iris.plot.plot(cube, **plot_kwargs)
+
+        # Default plot appearance
+        multi_dataset_facets = self._get_multi_dataset_facets(datasets)
+        axes.set_title(multi_dataset_facets['long_name'])
+        axes.set_xlabel('latitude [°N]')
+        axes.set_ylabel(
+            f"{multi_dataset_facets[self.cfg['group_variables_by']]} "
+            f"[{multi_dataset_facets['units']}]"
+        )
+        gridline_kwargs = self._get_gridline_kwargs(plot_type)
+        if gridline_kwargs is not False:
+            axes.grid(**gridline_kwargs)
+
+        # Legend
+        legend_kwargs = self.plots[plot_type]['legend_kwargs']
+        if legend_kwargs is not False:
+            axes.legend(**legend_kwargs)
+
+        # Customize plot appearance
+        self._process_pyplot_kwargs(plot_type, multi_dataset_facets)
+
+        # Save plot
+        plot_path = self.get_plot_path(plot_type, multi_dataset_facets)
+        fig.savefig(plot_path, **self.cfg['savefig_kwargs'])
+        logger.info("Wrote %s", plot_path)
+        plt.close()
+
+        # Save netCDF file
+        netcdf_path = get_diagnostic_filename(Path(plot_path).stem, self.cfg)
+        var_attrs = {
+            n: datasets[0][n] for n in ('short_name', 'long_name', 'units')
+        }
+        io.save_1d_data(cubes, netcdf_path, 'latitude', var_attrs)
+
+        # Provenance tracking
+        caption = (f"{multi_dataset_facets['long_name']} vs. latitude for "
+                   f"various datasets.")
+        provenance_record = {
+            'ancestors': ancestors,
+            'authors': ['sarauer_ellen'],
+            'caption': caption,
+            'plot_types': ['line'],
+            'long_names': [var_attrs['long_name']],
+        }
+        with ProvenanceLogger(self.cfg) as provenance_logger:
+            provenance_logger.log(plot_path, provenance_record)
+            provenance_logger.log(netcdf_path, provenance_record)
+
     def create_hovmoeller_z_vs_time_plot(self, datasets):
         """Create Hovmoeller Z vs. time plot."""
         plot_type = 'hovmoeller_z_vs_time'
@@ -2120,6 +2395,79 @@ def create_hovmoeller_z_vs_time_plot(self, datasets):
                 for netcdf_path in netcdf_paths:
                     provenance_logger.log(netcdf_path, provenance_record)
 
+    def create_hovmoeller_time_vs_lat_or_lon_plot(self, datasets):
+        """Create the Hovmoeller plot with time vs latitude or longitude."""
+        plot_type = 'hovmoeller_time_vs_lat_or_lon'
+        if plot_type not in self.plots:
+            return
+
+        if not datasets:
+            raise ValueError(f"No input data to plot '{plot_type}' given")
+
+        # Get reference dataset if possible
+        ref_dataset = self._get_reference_dataset(datasets)
+        if ref_dataset is None:
+            logger.info("Plotting %s without reference dataset", plot_type)
+        else:
+            logger.info("Plotting %s with reference dataset '%s'", plot_type,
+                        self._get_label(ref_dataset))
+
+        # Get plot function
+        plot_func = self._get_plot_func(plot_type)
+
+        # Create a single plot for each dataset (incl. reference dataset if
+        # given)
+        for dataset in datasets:
+            if dataset == ref_dataset:
+                continue
+            ancestors = [dataset['filename']]
+            if ref_dataset is None:
+                (plot_path, netcdf_paths) = (
+                    self._plot_hovmoeller_time_vs_lat_or_lon_without_ref(
+                        plot_func,
+                        dataset)
+                )
+                caption = (
+                    f"Hovmoeller plot of {dataset['long_name']} of dataset "
+                    f"{dataset['dataset']} (project {dataset['project']}) "
+                    f"from {dataset['start_year']} to {dataset['end_year']}."
+                )
+            else:
+                (plot_path, netcdf_paths) = (
+                    self._plot_hovmoeller_time_vs_lat_or_lon_with_ref(
+                        plot_func, dataset, ref_dataset)
+                )
+                caption = (
+                    f"Hovmoeller plot of {dataset['long_name']} of dataset "
+                    f"{dataset['dataset']} (project {dataset['project']}) "
+                    f"including bias relative to {ref_dataset['dataset']} "
+                    f"(project {ref_dataset['project']}) from "
+                    f"{dataset['start_year']} to {dataset['end_year']}."
+                )
+                ancestors.append(ref_dataset['filename'])
+
+            # Save plot
+            plt.savefig(plot_path, **self.cfg['savefig_kwargs'])
+            logger.info("Wrote %s", plot_path)
+            plt.close()
+
+            # Save netCDFs
+            for (netcdf_path, cube) in netcdf_paths.items():
+                io.iris_save(cube, netcdf_path)
+
+            # Provenance tracking
+            provenance_record = {
+                'ancestors': ancestors,
+                'authors': ['schlund_manuel', 'kraft_jeremy', 'ruhe_lukas'],
+                'caption': caption,
+                'plot_types': ['zonal'],
+                'long_names': [dataset['long_name']],
+            }
+            with ProvenanceLogger(self.cfg) as provenance_logger:
+                provenance_logger.log(plot_path, provenance_record)
+                for netcdf_path in netcdf_paths:
+                    provenance_logger.log(netcdf_path, provenance_record)
+
     def compute(self):
         """Plot preprocessed data."""
         for (var_key, datasets) in self.grouped_input_data.items():
@@ -2131,6 +2479,7 @@ def compute(self):
             self.create_1d_profile_plot(datasets)
             self.create_variable_vs_lat_plot(datasets)
             self.create_hovmoeller_z_vs_time_plot(datasets)
+            self.create_hovmoeller_time_vs_lat_or_lon_plot(datasets)
 
 
 def main():
diff --git a/esmvaltool/recipes/monitor/recipe_monitor_with_refs.yml b/esmvaltool/recipes/monitor/recipe_monitor_with_refs.yml
index 3db01e6a4a..e75cc763da 100644
--- a/esmvaltool/recipes/monitor/recipe_monitor_with_refs.yml
+++ b/esmvaltool/recipes/monitor/recipe_monitor_with_refs.yml
@@ -7,10 +7,12 @@ documentation:
     (ongoing) model simulations.
   authors:
     - schlund_manuel
-    - winterstein_franziska
-    - sarauer_ellen
-    - kuehbacher_birgit
     - heuer_helge
+    - kraft_jeremy
+    - kuehbacher_birgit
+    - ruhe_lukas
+    - sarauer_ellen
+    - winterstein_franziska
   maintainer:
     - schlund_manuel
 
@@ -20,6 +22,7 @@ datasets:
   - {project: CMIP6, dataset: MPI-ESM1-2-HR, exp: historical, ensemble: r1i1p1f1, grid: gn, plot_label: 'MPI-ESM1-2-HR historical'}
   - {project: CMIP6, dataset: MPI-ESM1-2-LR, exp: historical, ensemble: r1i1p1f1, grid: gn, plot_label: 'Reference (MPI-ESM1-2-LR historical)', reference_for_monitor_diags: true}
 
+
 preprocessors:
 
   timeseries_regular:
@@ -92,6 +95,13 @@ preprocessors:
     area_statistics:
       operator: mean
 
+  zonal_mean_2d:
+    regrid:
+      target_grid: 2x2
+      scheme: linear
+    zonal_statistics:
+      operator: mean
+
 
 diagnostics:
 
@@ -175,6 +185,7 @@ diagnostics:
             plot_kwargs_bias:
               levels: [-10.0, -7.5, -5.0, -2.5, 0.0, 2.5, 5.0, 7.5, 10.0]
 
+
   plot_1D_profiles_with_references:
     description: Plot 1D profiles including reference datasets.
     variables:
@@ -227,3 +238,20 @@ diagnostics:
             log_y: false
             pyplot_kwargs:
               ylim: [0, 20000]
+
+  plot_time_vs_lat_with_references:
+    description: Plot Hovmoeller time vs. latitude including reference datasets.
+    variables:
+      tas:
+        mip: Amon
+        preprocessor: zonal_mean_2d
+        timerange: '2000/2004'
+    scripts:
+      plot:
+        <<: *plot_multi_dataset_default
+        script: monitor/multi_datasets.py
+        plots:
+          hovmoeller_time_vs_lat_or_lon:
+            common_cbar: true
+            show_x_minor_ticks: false
+            time_format: '%Y'

From de112361445037ed0d0fbdc3a7d671631a423b50 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Thu, 14 Sep 2023 16:32:41 +0100
Subject: [PATCH 44/93] [Condalock] Update Linux condalock file (#3336)

Co-authored-by: valeriupredoi <valeriupredoi@users.noreply.github.com>
---
 conda-linux-64.lock | 197 ++++++++++++++++++++++----------------------
 1 file changed, 98 insertions(+), 99 deletions(-)

diff --git a/conda-linux-64.lock b/conda-linux-64.lock
index c7e91c6a20..20df33b8a2 100644
--- a/conda-linux-64.lock
+++ b/conda-linux-64.lock
@@ -13,22 +13,22 @@ https://conda.anaconda.org/conda-forge/noarch/font-ttf-source-code-pro-2.038-h77
 https://conda.anaconda.org/conda-forge/noarch/font-ttf-ubuntu-0.83-hab24e00_0.tar.bz2#19410c3df09dfb12d1206132a1d357c5
 https://conda.anaconda.org/conda-forge/noarch/kernel-headers_linux-64-2.6.32-he073ed8_16.conda#7ca122655873935e02c91279c5b03c8c
 https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.40-h41732ed_0.conda#7aca3059a1729aa76c597603f10b0dd3
-https://conda.anaconda.org/conda-forge/linux-64/libgcc-devel_linux-64-13.1.0-he3cc6c4_0.conda#5ec50dcd74ba7461709c4ac9c4cc4190
-https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-13.1.0-h15d22d2_0.conda#afb656a334c409dd9805508af1c89c7a
-https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-devel_linux-64-13.1.0-he3cc6c4_0.conda#e703914ad2288ab24cf5ac94d812fc11
-https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-ng-13.1.0-hfd8a6a1_0.conda#067bcc23164642f4c226da631f2a2e1d
+https://conda.anaconda.org/conda-forge/linux-64/libgcc-devel_linux-64-13.2.0-ha9c7c90_0.conda#9a5cb396c9f40a5310ed88ed6ac9d632
+https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-13.2.0-ha4646dd_0.conda#aa3ee989b0eba634e47197adbaa84fdd
+https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-devel_linux-64-13.2.0-ha9c7c90_0.conda#65f1916f317ff8169e0d25b00b3dde72
+https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-ng-13.2.0-h7e041cc_0.conda#47d33bfb38632133412c20d1dee8eeae
 https://conda.anaconda.org/conda-forge/noarch/poppler-data-0.4.12-hd8ed1ab_0.conda#d8d7293c5b37f39b2ac32940621c6592
 https://conda.anaconda.org/conda-forge/linux-64/python_abi-3.11-3_cp311.conda#c2e2630ddb68cf52eec74dc7dfab20b5
 https://conda.anaconda.org/conda-forge/noarch/tzdata-2023c-h71feb2d_0.conda#939e3e74d8be4dac89ce83b20de2492a
 https://conda.anaconda.org/conda-forge/linux-64/xorg-imake-1.0.7-0.tar.bz2#23acfc5a339a6a34cc2241f64e4111be
 https://conda.anaconda.org/conda-forge/noarch/fonts-conda-forge-1-0.tar.bz2#f766549260d6815b0c52253f1fb1bb29
-https://conda.anaconda.org/conda-forge/linux-64/libgfortran-ng-13.1.0-h69a702a_0.conda#506dc07710dd5b0ba63cbf134897fc10
-https://conda.anaconda.org/conda-forge/linux-64/libgomp-13.1.0-he5830b7_0.conda#56ca14d57ac29a75d23a39eb3ee0ddeb
+https://conda.anaconda.org/conda-forge/linux-64/libgfortran-ng-13.2.0-h69a702a_0.conda#bdaebefa4f6c436741187c8a304681a5
+https://conda.anaconda.org/conda-forge/linux-64/libgomp-13.2.0-h807b86a_0.conda#33c2353e425610c69ad58a8e29694724
 https://conda.anaconda.org/conda-forge/noarch/sysroot_linux-64-2.12-he073ed8_16.conda#071ea8dceff4d30ac511f4a2f8437cd1
 https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-2_gnu.tar.bz2#73aaf86a425cc6e73fcf236a5a46396d
 https://conda.anaconda.org/conda-forge/linux-64/binutils_impl_linux-64-2.40-hf600244_0.conda#33084421a8c0af6aef1b439707f7662a
 https://conda.anaconda.org/conda-forge/noarch/fonts-conda-ecosystem-1-0.tar.bz2#fee5683a3f04bd15cbd8318b096a27ab
-https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-13.1.0-he5830b7_0.conda#cd93f779ff018dd85c7544c015c9db3c
+https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-13.2.0-h807b86a_0.conda#3934dca6107fad668d036a4cafca1015
 https://conda.anaconda.org/conda-forge/linux-64/aom-3.5.0-h27087fc_0.tar.bz2#a08150fd2298460cd1fcccf626305642
 https://conda.anaconda.org/conda-forge/linux-64/aws-c-common-0.8.23-hd590300_0.conda#cc4f06f7eedb1523f3b83fd0fb3942ff
 https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-h7f98852_4.tar.bz2#a1fd65c7ccbf10880423d82bca54eb54
@@ -41,7 +41,7 @@ https://conda.anaconda.org/conda-forge/linux-64/fribidi-1.0.10-h36c2ea0_0.tar.bz
 https://conda.anaconda.org/conda-forge/linux-64/geos-3.11.2-hcb278e6_0.conda#3b8e364995e3575e57960d29c1e5ab14
 https://conda.anaconda.org/conda-forge/linux-64/gettext-0.21.1-h27087fc_0.tar.bz2#14947d8770185e5153fdd04d4673ed37
 https://conda.anaconda.org/conda-forge/linux-64/gflags-2.2.2-he1b5a44_1004.tar.bz2#cddaf2c63ea4a5901cf09524c490ecdc
-https://conda.anaconda.org/conda-forge/linux-64/ghostscript-9.54.0-h27087fc_2.tar.bz2#c3b35ac18d09ffc8d46064fb09a696af
+https://conda.anaconda.org/conda-forge/linux-64/ghostscript-9.56.1-h59595ed_0.conda#0ecb8c9d30157cee294f9ae2546d6789
 https://conda.anaconda.org/conda-forge/linux-64/giflib-5.2.1-h0b41bf4_3.conda#96f3b11872ef6fad973eac856cd2624f
 https://conda.anaconda.org/conda-forge/linux-64/gmp-6.2.1-h58526e2_0.tar.bz2#b94cf2db16066b242ebd26db2facbd56
 https://conda.anaconda.org/conda-forge/linux-64/graphite2-1.3.13-h58526e2_1001.tar.bz2#8c54672728e8ec6aa6db90cf2806d220
@@ -63,9 +63,9 @@ https://conda.anaconda.org/conda-forge/linux-64/libiconv-1.17-h166bdaf_0.tar.bz2
 https://conda.anaconda.org/conda-forge/linux-64/libjpeg-turbo-2.1.5.1-h0b41bf4_0.conda#1edd9e67bdb90d78cea97733ff6b54e6
 https://conda.anaconda.org/conda-forge/linux-64/libnsl-2.0.0-h7f98852_0.tar.bz2#39b1328babf85c7c3a61636d9cd50206
 https://conda.anaconda.org/conda-forge/linux-64/libnuma-2.0.16-h0b41bf4_1.conda#28bfe2cb11357ccc5be21101a6b7ce86
-https://conda.anaconda.org/conda-forge/linux-64/libopenblas-0.3.23-pthreads_h80387f5_0.conda#9c5ea51ccb8ffae7d06c645869d24ce6
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+https://conda.anaconda.org/conda-forge/noarch/xesmf-0.8.1-pyhd8ed1ab_0.conda#8c2810704a9bac2743402b1ca22ec312
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@@ -648,11 +647,11 @@ https://conda.anaconda.org/conda-forge/linux-64/r-geomap-2.5_0-r41h06615bd_1.tar
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-https://conda.anaconda.org/conda-forge/noarch/nbsphinx-0.9.2-pyhd8ed1ab_0.conda#d1212b423fdd10d2da59601385561ff7
+https://conda.anaconda.org/conda-forge/noarch/nbsphinx-0.9.3-pyhd8ed1ab_0.conda#0dbaa7d08d3d79b2a1a4dd6a02cc4581
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+https://conda.anaconda.org/conda-forge/noarch/sphinx-7.2.5-pyhd8ed1ab_0.conda#bc7881d37168b6731affdd89a2433c64
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From dcc6fe468503a7fdcf306f5eea5254842684cb2a Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Tue, 26 Sep 2023 16:12:00 +0100
Subject: [PATCH 45/93] [Condalock] Update Linux condalock file (#3359)

Co-authored-by: valeriupredoi <valeriupredoi@users.noreply.github.com>
---
 conda-linux-64.lock | 202 ++++++++++++++++++++++----------------------
 1 file changed, 101 insertions(+), 101 deletions(-)

diff --git a/conda-linux-64.lock b/conda-linux-64.lock
index 20df33b8a2..128ace6209 100644
--- a/conda-linux-64.lock
+++ b/conda-linux-64.lock
@@ -13,35 +13,32 @@ https://conda.anaconda.org/conda-forge/noarch/font-ttf-source-code-pro-2.038-h77
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 https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.40-h41732ed_0.conda#7aca3059a1729aa76c597603f10b0dd3
-https://conda.anaconda.org/conda-forge/linux-64/libgcc-devel_linux-64-13.2.0-ha9c7c90_0.conda#9a5cb396c9f40a5310ed88ed6ac9d632
-https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-13.2.0-ha4646dd_0.conda#aa3ee989b0eba634e47197adbaa84fdd
-https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-devel_linux-64-13.2.0-ha9c7c90_0.conda#65f1916f317ff8169e0d25b00b3dde72
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+https://conda.anaconda.org/conda-forge/linux-64/libgcc-devel_linux-64-13.2.0-ha9c7c90_2.conda#401c5cf212e568dab47e0677a000d2a7
+https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-devel_linux-64-13.2.0-ha9c7c90_2.conda#a0bf59008336aa76ad2a097a652c60bd
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-https://conda.anaconda.org/conda-forge/linux-64/ghostscript-9.56.1-h59595ed_0.conda#0ecb8c9d30157cee294f9ae2546d6789
+https://conda.anaconda.org/conda-forge/linux-64/ghostscript-10.02.0-h59595ed_0.conda#8ab9369b573e62ddf9456f1fe4dfc39d
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+https://conda.anaconda.org/conda-forge/linux-64/psyplot-1.4.3-py311h38be061_1.tar.bz2#f0c9a1067c03e8f05e53ef0c5ad5fab3
+https://conda.anaconda.org/conda-forge/linux-64/py-xgboost-1.7.6-cuda112py311h2344cce_2.conda#cca8982f2b80ffe50124d5cdbbcfdda8
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@@ -556,16 +555,17 @@ https://conda.anaconda.org/conda-forge/linux-64/r-xfun-0.39-r41ha503ecb_0.conda#
 https://conda.anaconda.org/conda-forge/noarch/r-xmlparsedata-1.0.5-r41hc72bb7e_1.tar.bz2#921c0ef7104d8df0ab506f1bb81a062c
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-https://conda.anaconda.org/conda-forge/linux-64/scikit-learn-1.3.0-py311hc009520_0.conda#847797c4a9c0c3363ffcfe7571dedfee
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-https://conda.anaconda.org/conda-forge/noarch/sparse-0.14.0-pyhd8ed1ab_0.conda#ee01b310177a0612554b9d20e537fdbe
+https://conda.anaconda.org/conda-forge/linux-64/statsmodels-0.14.0-py311h1f0f07a_1.conda#a1daa39fa0bfed4d91a3640c2274034a
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-https://conda.anaconda.org/conda-forge/noarch/psy-maps-1.4.2-pyhd8ed1ab_0.tar.bz2#3ed13103dfd46f71dc870d188bd0b276
-https://conda.anaconda.org/conda-forge/linux-64/py-xgboost-1.7.6-cuda112py311h2344cce_2.conda#cca8982f2b80ffe50124d5cdbbcfdda8
+https://conda.anaconda.org/conda-forge/linux-64/psy-simple-1.4.1-py311h38be061_2.tar.bz2#4c9101d329f6bc09c2617a80e3eb9c89
+https://conda.anaconda.org/conda-forge/noarch/py-cordex-0.6.3-pyhd8ed1ab_0.conda#de9f9392273a1e6095930a21561a37e9
 https://conda.anaconda.org/conda-forge/linux-64/pyarrow-12.0.1-py311h39c9aba_7_cpu.conda#d513ab8d10ec5f3ee45b419c836195ec
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@@ -594,11 +594,13 @@ https://conda.anaconda.org/conda-forge/linux-64/r-spam-2.9_1-r41hb20cf53_1.conda
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-https://conda.anaconda.org/conda-forge/linux-64/statsmodels-0.14.0-py311h1f0f07a_1.conda#a1daa39fa0bfed4d91a3640c2274034a
-https://conda.anaconda.org/conda-forge/noarch/xesmf-0.8.1-pyhd8ed1ab_0.conda#8c2810704a9bac2743402b1ca22ec312
-https://conda.anaconda.org/conda-forge/noarch/dask-2023.9.1-pyhd8ed1ab_0.conda#7192f8f126e50d6d0274fbbf4e73e9cf
+https://conda.anaconda.org/conda-forge/noarch/seaborn-0.12.2-hd8ed1ab_0.conda#50847a47c07812f88581081c620f5160
+https://conda.anaconda.org/conda-forge/noarch/xesmf-0.8.2-pyhd8ed1ab_0.conda#8e765a0eca0ce1cfa889cd9af82a23a8
+https://conda.anaconda.org/conda-forge/linux-64/xgboost-1.7.6-cuda112py311h2344cce_2.conda#97cd4e1589b8ea11e0f78d2f0c7cc217
+https://conda.anaconda.org/conda-forge/noarch/dask-2023.9.2-pyhd8ed1ab_0.conda#29e33df59c9eac1a599b9cd18d54b4d3
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 https://conda.anaconda.org/conda-forge/noarch/prov-2.0.0-pyhd3deb0d_0.tar.bz2#aa9b3ad140f6c0668c646f32e20ccf82
+https://conda.anaconda.org/conda-forge/noarch/psy-maps-1.4.2-pyhd8ed1ab_0.tar.bz2#3ed13103dfd46f71dc870d188bd0b276
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@@ -618,8 +620,6 @@ https://conda.anaconda.org/conda-forge/noarch/r-scales-1.2.1-r41hc72bb7e_1.tar.b
 https://conda.anaconda.org/conda-forge/linux-64/r-specsverification-0.5_3-r41ha503ecb_3.conda#2bc51f0d44b98092ba57cf2f8671b490
 https://conda.anaconda.org/conda-forge/linux-64/r-splancs-2.01_43-r41h8da6f51_1.tar.bz2#3a6aad0706541141d10e3b514467a080
 https://conda.anaconda.org/conda-forge/linux-64/r-vctrs-0.6.2-r41ha503ecb_0.conda#1f7610a1863648cab254a9f85bd29dcd
-https://conda.anaconda.org/conda-forge/noarch/seaborn-0.12.2-hd8ed1ab_0.conda#50847a47c07812f88581081c620f5160
-https://conda.anaconda.org/conda-forge/linux-64/xgboost-1.7.6-cuda112py311h2344cce_2.conda#97cd4e1589b8ea11e0f78d2f0c7cc217
 https://conda.anaconda.org/conda-forge/noarch/iris-esmf-regrid-0.8.0-pyhd8ed1ab_0.conda#56e85460d22fa7d4fb06300f785dd1e1
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@@ -648,10 +648,10 @@ https://conda.anaconda.org/conda-forge/noarch/r-lintr-3.0.2-r41hc72bb7e_0.tar.bz
 https://conda.anaconda.org/conda-forge/noarch/r-s2dverification-2.10.3-r41hc72bb7e_1.tar.bz2#2253f130c8dab435824d6ddb10a41c73
 https://conda.anaconda.org/conda-forge/noarch/autodocsumm-0.2.6-pyhd8ed1ab_0.tar.bz2#4409dd7e06a62c3b2aa9e96782c49c6d
 https://conda.anaconda.org/conda-forge/noarch/nbsphinx-0.9.3-pyhd8ed1ab_0.conda#0dbaa7d08d3d79b2a1a4dd6a02cc4581
-https://conda.anaconda.org/conda-forge/noarch/pydata-sphinx-theme-0.13.3-pyhd8ed1ab_0.conda#07aca5f2dea315dcc16680d6891e9056
+https://conda.anaconda.org/conda-forge/noarch/pydata-sphinx-theme-0.14.1-pyhd8ed1ab_0.conda#78153addf629c51fab775ef360012ca3
 https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-applehelp-1.0.7-pyhd8ed1ab_0.conda#aebfabcb60c33a89c1f9290cab49bc93
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-https://conda.anaconda.org/conda-forge/noarch/sphinx-7.2.5-pyhd8ed1ab_0.conda#bc7881d37168b6731affdd89a2433c64
+https://conda.anaconda.org/conda-forge/noarch/sphinx-7.2.6-pyhd8ed1ab_0.conda#bbfd1120d1824d2d073bc65935f0e4c0
 https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-serializinghtml-1.1.9-pyhd8ed1ab_0.conda#0612e497d7860728f2cda421ea2aec09

From b5050ab7cff6daebd2664a4d3016a62767f23b12 Mon Sep 17 00:00:00 2001
From: Klaus Zimmermann <klaus.zimmermann@smhi.se>
Date: Tue, 26 Sep 2023 17:50:28 +0200
Subject: [PATCH 46/93] Ensure compatible zstandard and zstd in readthedocs
 builds (#3362)

---
 .readthedocs.yaml | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/.readthedocs.yaml b/.readthedocs.yaml
index 07a53170b7..071686d373 100644
--- a/.readthedocs.yaml
+++ b/.readthedocs.yaml
@@ -14,9 +14,11 @@ build:
   jobs:
     pre_create_environment:
       # update mamba just in case
-      - mamba update --yes --quiet --name=base mamba
+      - mamba update --yes --quiet --name=base mamba 'zstd=1.5.2'
       - mamba --version
+      - mamba list --name=base
     post_create_environment:
+      - conda run -n ${CONDA_DEFAULT_ENV} mamba list
       # use conda run executable wrapper to have all env variables
       - conda run -n ${CONDA_DEFAULT_ENV} mamba --version
       - conda run -n ${CONDA_DEFAULT_ENV} pip install . --no-deps

From 00c7182325fcdffb44db0da6aefe609e8ea4f308 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Sun, 1 Oct 2023 14:16:45 +0100
Subject: [PATCH 47/93] [Condalock] Update Linux condalock file (#3365)

Co-authored-by: valeriupredoi <valeriupredoi@users.noreply.github.com>
---
 conda-linux-64.lock | 120 ++++++++++++++++++++++----------------------
 1 file changed, 60 insertions(+), 60 deletions(-)

diff --git a/conda-linux-64.lock b/conda-linux-64.lock
index 128ace6209..8f862fe311 100644
--- a/conda-linux-64.lock
+++ b/conda-linux-64.lock
@@ -59,7 +59,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libffi-3.4.2-h7f98852_5.tar.bz2#
 https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-13.2.0-ha4646dd_2.conda#78fdab09d9138851dde2b5fe2a11019e
 https://conda.anaconda.org/conda-forge/linux-64/libiconv-1.17-h166bdaf_0.tar.bz2#b62b52da46c39ee2bc3c162ac7f1804d
 https://conda.anaconda.org/conda-forge/linux-64/libjpeg-turbo-2.1.5.1-hd590300_1.conda#323e90742f0f48fc22bea908735f55e6
-https://conda.anaconda.org/conda-forge/linux-64/libnsl-2.0.0-h7f98852_0.tar.bz2#39b1328babf85c7c3a61636d9cd50206
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 https://conda.anaconda.org/conda-forge/noarch/flake8-polyfill-1.0.2-py_0.tar.bz2#a53db35e3d07f0af2eccd59c2a00bffe
 https://conda.anaconda.org/conda-forge/noarch/identify-2.5.29-pyhd8ed1ab_0.conda#5bdbb1cb692649720b60f261b41760cd
@@ -424,22 +424,22 @@ https://conda.anaconda.org/conda-forge/noarch/imageio-2.31.1-pyh24c5eb1_0.conda#
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 https://conda.anaconda.org/conda-forge/linux-64/julia-1.8.5-h783901f_0.conda#98c05ba7ca9c15d22216f730499e167a
-https://conda.anaconda.org/conda-forge/linux-64/jupyter_core-5.3.1-py311h38be061_0.conda#0cf8259b01ede82c76007996f73f89ed
+https://conda.anaconda.org/conda-forge/linux-64/jupyter_core-5.3.2-py311h38be061_0.conda#4e4341e940c0dfa1038c1a2d11fd8c3e
 https://conda.anaconda.org/conda-forge/linux-64/libgdal-3.7.0-h5418a03_2.conda#30ddbe080c260fb36da8509e3fd6c45f
 https://conda.anaconda.org/conda-forge/noarch/magics-python-1.5.8-pyhd8ed1ab_1.conda#3fd7e3db129f12362642108f23fde521
 https://conda.anaconda.org/conda-forge/linux-64/netcdf-fortran-4.6.1-nompi_h4f3791c_100.conda#405c5b3ad4ef53eb0d93043b54206dd7
 https://conda.anaconda.org/conda-forge/linux-64/numba-0.57.1-py311h96b013e_0.conda#618010d18c4a38073a7f51d9dd3fd8a8
 https://conda.anaconda.org/conda-forge/linux-64/numcodecs-0.11.0-py311hcafe171_1.conda#ecdaf0772e524ed51218f6d52ef74424
-https://conda.anaconda.org/conda-forge/linux-64/pandas-2.1.1-py311h320fe9a_0.conda#1692362ba82f0556099f0143f7842de3
+https://conda.anaconda.org/conda-forge/linux-64/pandas-2.1.1-py311h320fe9a_1.conda#a4371a95a8ae703a22949af28467b93d
 https://conda.anaconda.org/conda-forge/linux-64/pango-1.50.14-heaa33ce_1.conda#cde553e0e32389e26595db4eacf859eb
-https://conda.anaconda.org/conda-forge/noarch/pooch-1.7.0-pyha770c72_3.conda#5936894aade8240c867d292aa0d980c6
-https://conda.anaconda.org/conda-forge/noarch/pylint-2.17.5-pyhd8ed1ab_0.conda#30dc94b05de470e3b579d73d64127656
+https://conda.anaconda.org/conda-forge/noarch/pooch-1.7.0-pyhd8ed1ab_4.conda#3cdaf7af08850933662b1e228bc6b5bc
+https://conda.anaconda.org/conda-forge/noarch/pylint-2.17.6-pyhd8ed1ab_0.conda#71d8c641a688ae0fbe6e4ebba44ec405
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 https://conda.anaconda.org/conda-forge/noarch/pytest-html-3.2.0-pyhd8ed1ab_1.tar.bz2#d5c7a941dfbceaab4b172a56d7918eb0
-https://conda.anaconda.org/conda-forge/linux-64/pywavelets-1.4.1-py311hcb2cf0a_0.conda#272ca0c28df344037ba2c4982d4e4791
+https://conda.anaconda.org/conda-forge/linux-64/pywavelets-1.4.1-py311h1f0f07a_1.conda#86b71ff85f3e4c8a98b5bace6d9c4565
 https://conda.anaconda.org/conda-forge/noarch/requests-cache-1.1.0-pyhd8ed1ab_0.conda#57b89064c125bb9d0e533e018c3eb17a
-https://conda.anaconda.org/conda-forge/linux-64/scipy-1.11.2-py311h64a7726_1.conda#58af16843fc4469770bdbaf45d3a19de
+https://conda.anaconda.org/conda-forge/linux-64/scipy-1.11.3-py311h64a7726_0.conda#756e8ac1d784f704c0b22559b4bff7b0
 https://conda.anaconda.org/conda-forge/noarch/seawater-3.3.4-py_1.tar.bz2#a9e101e1601faf5e5a119ab2bd7617a4
 https://conda.anaconda.org/conda-forge/linux-64/shapely-2.0.1-py311h54d622a_1.conda#a894c65b48676c4973e9ee8b59bceb9e
 https://conda.anaconda.org/conda-forge/noarch/snuggs-1.4.7-py_0.tar.bz2#cb83a3d6ecf73f50117635192414426a
@@ -449,28 +449,28 @@ https://conda.anaconda.org/conda-forge/noarch/yapf-0.40.1-pyhd8ed1ab_0.conda#f26
 https://conda.anaconda.org/conda-forge/linux-64/aws-sdk-cpp-1.10.57-hbc2ea52_17.conda#452c7b08c21eea2ef01f4fd364d6affc
 https://conda.anaconda.org/conda-forge/noarch/bokeh-3.2.2-pyhd8ed1ab_0.conda#30488151f591379db656250b3f5fc0c6
 https://conda.anaconda.org/conda-forge/linux-64/cf-units-3.2.0-py311h1f0f07a_0.conda#43a71a823583d75308eaf3a06c8f150b
-https://conda.anaconda.org/conda-forge/noarch/distributed-2023.9.2-pyhd8ed1ab_0.conda#ddb4fd6105b4005b312625cef210ba67
+https://conda.anaconda.org/conda-forge/noarch/distributed-2023.9.3-pyhd8ed1ab_0.conda#543fafdd7b325bf16199235ee5f20622
 https://conda.anaconda.org/conda-forge/linux-64/eccodes-2.30.2-h1f30a5c_0.conda#21ee8444a7f629924ea8cfe52a622cbd
 https://conda.anaconda.org/conda-forge/linux-64/esmf-8.4.2-nompi_h20110ff_0.conda#11f5169aeff54ad7277476be8ba19ff7
 https://conda.anaconda.org/conda-forge/linux-64/gdal-3.7.0-py311h281082f_2.conda#fde4fad3c517cc80f32995696f45198d
 https://conda.anaconda.org/conda-forge/linux-64/gtk2-2.24.33-h90689f9_2.tar.bz2#957a0255ab58aaf394a91725d73ab422
 https://conda.anaconda.org/conda-forge/noarch/jupyter_client-8.3.1-pyhd8ed1ab_0.conda#b7cc0981484fcb6390e6d341e55618b3
 https://conda.anaconda.org/conda-forge/linux-64/librsvg-2.56.3-h98fae49_0.conda#620e754f4344f4c27259ff460a2b9c50
-https://conda.anaconda.org/conda-forge/linux-64/matplotlib-base-3.8.0-py311h54ef318_0.conda#b67672c2f39ef2912a1814e29e42c7ca
+https://conda.anaconda.org/conda-forge/linux-64/matplotlib-base-3.8.0-py311h54ef318_1.conda#20d79e2fe53b49b399f3d36977b05abb
 https://conda.anaconda.org/conda-forge/noarch/myproxyclient-2.1.0-pyhd8ed1ab_2.tar.bz2#363b0816e411feb0df925d4f224f026a
 https://conda.anaconda.org/conda-forge/noarch/nbformat-5.9.2-pyhd8ed1ab_0.conda#61ba076de6530d9301a0053b02f093d2
 https://conda.anaconda.org/conda-forge/linux-64/netcdf4-1.6.4-nompi_py311h4d7c953_100.conda#c03492d0342e512e58aa2d6c5fdaaa91
 https://conda.anaconda.org/conda-forge/noarch/patsy-0.5.3-pyhd8ed1ab_0.tar.bz2#50ef6b29b1fb0768ca82c5aeb4fb2d96
 https://conda.anaconda.org/conda-forge/noarch/pep8-naming-0.10.0-pyh9f0ad1d_0.tar.bz2#b3c5536e4f9f58a4b16adb6f1e11732d
-https://conda.anaconda.org/conda-forge/noarch/pre-commit-3.4.0-pyha770c72_1.conda#3fb5ba328a77c9fd71197a46e7f2469a
+https://conda.anaconda.org/conda-forge/noarch/pre-commit-3.4.0-pyha770c72_2.conda#09cd3006f61e7a7054405f81362e0a5f
 https://conda.anaconda.org/conda-forge/noarch/pylint-plugin-utils-0.7-pyhd8ed1ab_0.tar.bz2#1657976383aee04dbb3ae3bdf654bb58
-https://conda.anaconda.org/conda-forge/linux-64/python-stratify-0.3.0-py311h1f0f07a_0.conda#3a00b1b08d8c01b1a3bfa686b9152df2
+https://conda.anaconda.org/conda-forge/linux-64/python-stratify-0.3.0-py311h1f0f07a_1.conda#cd36a89a048ad2bcc6d8b43f648fb1d0
 https://conda.anaconda.org/conda-forge/linux-64/r-base-4.1.3-hfabd6f2_9.conda#0ab4cf54fbddc0cc9ff260c6f77f8c84
 https://conda.anaconda.org/conda-forge/linux-64/rasterio-1.3.8-py311h41e4db2_0.conda#b35deb26af1d7e0d98438c8ac5c6b7b2
-https://conda.anaconda.org/conda-forge/linux-64/scikit-learn-1.3.0-py311hc009520_0.conda#847797c4a9c0c3363ffcfe7571dedfee
+https://conda.anaconda.org/conda-forge/linux-64/scikit-learn-1.3.1-py311hc009520_0.conda#66f1553377ee79c5cf33dad1fa9cebb4
 https://conda.anaconda.org/conda-forge/noarch/sparse-0.14.0-pyhd8ed1ab_0.conda#ee01b310177a0612554b9d20e537fdbe
-https://conda.anaconda.org/conda-forge/noarch/tifffile-2023.9.18-pyhd8ed1ab_0.conda#c24d705dfe38f0a7a5cfa51b40c3d906
-https://conda.anaconda.org/conda-forge/noarch/xarray-2023.8.0-pyhd8ed1ab_0.conda#a8104cede521616573e228c27f9edc97
+https://conda.anaconda.org/conda-forge/noarch/tifffile-2023.9.26-pyhd8ed1ab_0.conda#d133bea7d8ac17552492a0629229eeb1
+https://conda.anaconda.org/conda-forge/noarch/xarray-2023.9.0-pyhd8ed1ab_0.conda#158c89bbc0f2597f33e8ce1aea59e0ee
 https://conda.anaconda.org/conda-forge/noarch/zarr-2.16.1-pyhd8ed1ab_0.conda#59ec835edbee50266b7bdbadab7ba335
 https://conda.anaconda.org/conda-forge/linux-64/cartopy-0.22.0-py311h320fe9a_0.conda#1271b2375735e2aaa6d6770dbe2ad087
 https://conda.anaconda.org/conda-forge/noarch/cf_xarray-0.8.4-pyhd8ed1ab_0.conda#18472f8f9452f962fe0bcb1b8134b494
@@ -567,7 +567,7 @@ https://conda.anaconda.org/conda-forge/noarch/prospector-1.10.2-pyhd8ed1ab_0.con
 https://conda.anaconda.org/conda-forge/linux-64/psy-simple-1.4.1-py311h38be061_2.tar.bz2#4c9101d329f6bc09c2617a80e3eb9c89
 https://conda.anaconda.org/conda-forge/noarch/py-cordex-0.6.3-pyhd8ed1ab_0.conda#de9f9392273a1e6095930a21561a37e9
 https://conda.anaconda.org/conda-forge/linux-64/pyarrow-12.0.1-py311h39c9aba_7_cpu.conda#d513ab8d10ec5f3ee45b419c836195ec
-https://conda.anaconda.org/conda-forge/linux-64/pydot-1.4.2-py311h38be061_3.tar.bz2#64a77de29fde80aef5013ddf5e62a564
+https://conda.anaconda.org/conda-forge/linux-64/pydot-1.4.2-py311h38be061_4.conda#5c223cb0d9c05552bf9d1586a92720b2
 https://conda.anaconda.org/conda-forge/linux-64/r-askpass-1.1-r41h06615bd_3.tar.bz2#c8ec8683302ad9a2345cb31ab28e6c6b
 https://conda.anaconda.org/conda-forge/linux-64/r-bigmemory-4.6.1-r41h7525677_1.tar.bz2#6a956b57b027b49b7a9ca48031a8bbd6
 https://conda.anaconda.org/conda-forge/linux-64/r-checkmate-2.2.0-r41h57805ef_0.conda#dc314ad76563387e70e0117c5398a15a
@@ -597,7 +597,7 @@ https://conda.anaconda.org/conda-forge/linux-64/r-zoo-1.8_12-r41h133d619_0.conda
 https://conda.anaconda.org/conda-forge/noarch/seaborn-0.12.2-hd8ed1ab_0.conda#50847a47c07812f88581081c620f5160
 https://conda.anaconda.org/conda-forge/noarch/xesmf-0.8.2-pyhd8ed1ab_0.conda#8e765a0eca0ce1cfa889cd9af82a23a8
 https://conda.anaconda.org/conda-forge/linux-64/xgboost-1.7.6-cuda112py311h2344cce_2.conda#97cd4e1589b8ea11e0f78d2f0c7cc217
-https://conda.anaconda.org/conda-forge/noarch/dask-2023.9.2-pyhd8ed1ab_0.conda#29e33df59c9eac1a599b9cd18d54b4d3
+https://conda.anaconda.org/conda-forge/noarch/dask-2023.9.3-pyhd8ed1ab_0.conda#5b32dc4eb1f5e3097cc33fb0e331b3a4
 https://conda.anaconda.org/conda-forge/noarch/nbconvert-pandoc-7.8.0-pyhd8ed1ab_0.conda#1dba1a577df2625a24667612a069e91c
 https://conda.anaconda.org/conda-forge/noarch/prov-2.0.0-pyhd3deb0d_0.tar.bz2#aa9b3ad140f6c0668c646f32e20ccf82
 https://conda.anaconda.org/conda-forge/noarch/psy-maps-1.4.2-pyhd8ed1ab_0.tar.bz2#3ed13103dfd46f71dc870d188bd0b276

From a6f98182d2f92703133c0d5db3cd02c16f0ad5c4 Mon Sep 17 00:00:00 2001
From: Manuel Schlund <32543114+schlunma@users.noreply.github.com>
Date: Thu, 5 Oct 2023 15:28:56 +0200
Subject: [PATCH 48/93] Remove deprecated option `offline` from CI
 configuration (#3367)

---
 .circleci/config.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.circleci/config.yml b/.circleci/config.yml
index ad43c7f495..47e87cf517 100644
--- a/.circleci/config.yml
+++ b/.circleci/config.yml
@@ -214,7 +214,7 @@ jobs:
             conda activate esmvaltool
             mkdir -p ~/climate_data
             esmvaltool config get_config_user
-            echo "offline: false" >> ~/.esmvaltool/config-user.yml
+            echo "search_esgf: when_missing" >> ~/.esmvaltool/config-user.yml
             cat ~/.esmvaltool/config-user.yml
             for recipe in esmvaltool/recipes/testing/recipe_*.yml; do
               esmvaltool run "$recipe"

From 12a2bdb860071d3770e0dd1efec2a700f5b461fc Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Wed, 11 Oct 2023 12:38:28 +0100
Subject: [PATCH 49/93] [Condalock] Update Linux condalock file (#3376)

Co-authored-by: valeriupredoi <valeriupredoi@users.noreply.github.com>
---
 conda-linux-64.lock | 116 ++++++++++++++++++++++----------------------
 1 file changed, 58 insertions(+), 58 deletions(-)

diff --git a/conda-linux-64.lock b/conda-linux-64.lock
index 8f862fe311..a1a14e1190 100644
--- a/conda-linux-64.lock
+++ b/conda-linux-64.lock
@@ -30,7 +30,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-13.2.0-h807b86a_2.cond
 https://conda.anaconda.org/conda-forge/linux-64/aom-3.5.0-h27087fc_0.tar.bz2#a08150fd2298460cd1fcccf626305642
 https://conda.anaconda.org/conda-forge/linux-64/aws-c-common-0.8.23-hd590300_0.conda#cc4f06f7eedb1523f3b83fd0fb3942ff
 https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-h7f98852_4.tar.bz2#a1fd65c7ccbf10880423d82bca54eb54
-https://conda.anaconda.org/conda-forge/linux-64/c-ares-1.19.1-hd590300_0.conda#e8c18d865be43e2fb3f7a145b6adf1f5
+https://conda.anaconda.org/conda-forge/linux-64/c-ares-1.20.1-hd590300_0.conda#6642e4faa4804be3a0e7edfefbd16595
 https://conda.anaconda.org/conda-forge/linux-64/charls-2.4.2-h59595ed_0.conda#4336bd67920dd504cd8c6761d6a99645
 https://conda.anaconda.org/conda-forge/linux-64/dav1d-1.2.1-hd590300_0.conda#418c6ca5929a611cbd69204907a83995
 https://conda.anaconda.org/conda-forge/linux-64/freexl-1.0.6-h166bdaf_1.tar.bz2#897e772a157faf3330d72dd291486f62
@@ -49,7 +49,7 @@ https://conda.anaconda.org/conda-forge/linux-64/jxrlib-1.1-h7f98852_2.tar.bz2#8e
 https://conda.anaconda.org/conda-forge/linux-64/keyutils-1.6.1-h166bdaf_0.tar.bz2#30186d27e2c9fa62b45fb1476b7200e3
 https://conda.anaconda.org/conda-forge/linux-64/lerc-4.0.0-h27087fc_0.tar.bz2#76bbff344f0134279f225174e9064c8f
 https://conda.anaconda.org/conda-forge/linux-64/libabseil-20230125.3-cxx17_h59595ed_0.conda#d1db1b8be7c3a8983dcbbbfe4f0765de
-https://conda.anaconda.org/conda-forge/linux-64/libaec-1.0.6-hcb278e6_1.conda#0f683578378cddb223e7fd24f785ab2a
+https://conda.anaconda.org/conda-forge/linux-64/libaec-1.1.2-h59595ed_1.conda#127b0be54c1c90760d7fe02ea7a56426
 https://conda.anaconda.org/conda-forge/linux-64/libbrotlicommon-1.0.9-h166bdaf_9.conda#61641e239f96eae2b8492dc7e755828c
 https://conda.anaconda.org/conda-forge/linux-64/libcrc32c-1.1.2-h9c3ff4c_0.tar.bz2#c965a5aa0d5c1c37ffc62dff36e28400
 https://conda.anaconda.org/conda-forge/linux-64/libdeflate-1.18-h0b41bf4_0.conda#6aa9c9de5542ecb07fdda9ca626252d8
@@ -75,7 +75,7 @@ https://conda.anaconda.org/conda-forge/linux-64/lzo-2.10-h516909a_1000.tar.bz2#b
 https://conda.anaconda.org/conda-forge/linux-64/make-4.3-hd18ef5c_1.tar.bz2#4049ebfd3190b580dffe76daed26155a
 https://conda.anaconda.org/conda-forge/linux-64/mbedtls-3.3.0-hcb278e6_0.conda#cc1213f464c357b647cc5dde5cfca881
 https://conda.anaconda.org/conda-forge/linux-64/metis-5.1.0-h59595ed_1007.conda#40ccb8318df2500f83bd868dd8fcd201
-https://conda.anaconda.org/conda-forge/linux-64/nccl-2.18.5.1-h6103f9b_1.conda#45a5f1a3859ca6547de507330afcf31a
+https://conda.anaconda.org/conda-forge/linux-64/nccl-2.19.3.1-h6103f9b_0.conda#5b4426d8e0534cd844924728d2137666
 https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.4-hcb278e6_0.conda#681105bccc2a3f7f1a837d47d39c9179
 https://conda.anaconda.org/conda-forge/linux-64/nspr-4.35-h27087fc_0.conda#da0ec11a6454ae19bff5b02ed881a2b1
 https://conda.anaconda.org/conda-forge/linux-64/openlibm-0.8.1-h7f98852_0.tar.bz2#ba0c56761f2380babaa783b2a37b4d08
@@ -89,6 +89,7 @@ https://conda.anaconda.org/conda-forge/linux-64/re2-2023.03.02-h8c504da_0.conda#
 https://conda.anaconda.org/conda-forge/linux-64/sed-4.8-he412f7d_0.tar.bz2#7362f0042e95681f5d371c46c83ebd08
 https://conda.anaconda.org/conda-forge/linux-64/snappy-1.1.10-h9fff704_0.conda#e6d228cd0bb74a51dd18f5bfce0b4115
 https://conda.anaconda.org/conda-forge/linux-64/tzcode-2023c-h0b41bf4_0.conda#0c0533894f21c3d35697cb8378d390e2
+https://conda.anaconda.org/conda-forge/linux-64/uriparser-0.9.7-hcb278e6_1.conda#2c46deb08ba9b10e90d0a6401ad65deb
 https://conda.anaconda.org/conda-forge/linux-64/xorg-inputproto-2.3.2-h7f98852_1002.tar.bz2#bcd1b3396ec6960cbc1d2855a9e60b2b
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 https://conda.anaconda.org/conda-forge/linux-64/xorg-libxaw-1.0.14-h7f98852_1.tar.bz2#45b68dc2fc7549c16044d533ceaf340e
-https://conda.anaconda.org/conda-forge/linux-64/aiohttp-3.8.5-py311h459d7ec_0.conda#82a817c46ac339c0166f043f56492f33
+https://conda.anaconda.org/conda-forge/linux-64/aiohttp-3.8.6-py311h459d7ec_1.conda#7d4b63a745f293029b5689b0b5d8aa15
 https://conda.anaconda.org/conda-forge/linux-64/aws-crt-cpp-0.20.3-he9c0e7f_4.conda#7695770e1d722ce9029a2ea30c060a3d
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@@ -418,28 +418,28 @@ https://conda.anaconda.org/conda-forge/linux-64/contourpy-1.1.1-py311h9547e67_1.
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-https://conda.anaconda.org/conda-forge/noarch/identify-2.5.29-pyhd8ed1ab_0.conda#5bdbb1cb692649720b60f261b41760cd
+https://conda.anaconda.org/conda-forge/noarch/identify-2.5.30-pyhd8ed1ab_0.conda#b7a2e3bb89bda8c69839485c20aabadf
 https://conda.anaconda.org/conda-forge/linux-64/imagecodecs-2023.8.12-py311h67b54e4_0.conda#363e5c2f2c67ff69d717aba54422b03d
-https://conda.anaconda.org/conda-forge/noarch/imageio-2.31.1-pyh24c5eb1_0.conda#1051cc0376612ba101d4f59e954a1ff4
+https://conda.anaconda.org/conda-forge/noarch/imageio-2.31.5-pyh8c1a49c_0.conda#6820ccf6a3a27df348f18c85dd89014a
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-https://conda.anaconda.org/conda-forge/noarch/pylint-2.17.6-pyhd8ed1ab_0.conda#71d8c641a688ae0fbe6e4ebba44ec405
+https://conda.anaconda.org/conda-forge/noarch/pylint-3.0.1-pyhd8ed1ab_0.conda#c4c66338865d295a213e8c1e473a072f
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-https://conda.anaconda.org/conda-forge/linux-64/scipy-1.11.3-py311h64a7726_0.conda#756e8ac1d784f704c0b22559b4bff7b0
+https://conda.anaconda.org/conda-forge/linux-64/scipy-1.11.3-py311h64a7726_1.conda#e4b4d3b764e2d029477d0db88248a8b5
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 https://conda.anaconda.org/conda-forge/noarch/snuggs-1.4.7-py_0.tar.bz2#cb83a3d6ecf73f50117635192414426a
@@ -467,7 +467,7 @@ https://conda.anaconda.org/conda-forge/noarch/pylint-plugin-utils-0.7-pyhd8ed1ab
 https://conda.anaconda.org/conda-forge/linux-64/python-stratify-0.3.0-py311h1f0f07a_1.conda#cd36a89a048ad2bcc6d8b43f648fb1d0
 https://conda.anaconda.org/conda-forge/linux-64/r-base-4.1.3-hfabd6f2_9.conda#0ab4cf54fbddc0cc9ff260c6f77f8c84
 https://conda.anaconda.org/conda-forge/linux-64/rasterio-1.3.8-py311h41e4db2_0.conda#b35deb26af1d7e0d98438c8ac5c6b7b2
-https://conda.anaconda.org/conda-forge/linux-64/scikit-learn-1.3.1-py311hc009520_0.conda#66f1553377ee79c5cf33dad1fa9cebb4
+https://conda.anaconda.org/conda-forge/linux-64/scikit-learn-1.3.1-py311hc009520_1.conda#0f06a0c10766b511c62050f9aed88b24
 https://conda.anaconda.org/conda-forge/noarch/sparse-0.14.0-pyhd8ed1ab_0.conda#ee01b310177a0612554b9d20e537fdbe
 https://conda.anaconda.org/conda-forge/noarch/tifffile-2023.9.26-pyhd8ed1ab_0.conda#d133bea7d8ac17552492a0629229eeb1
 https://conda.anaconda.org/conda-forge/noarch/xarray-2023.9.0-pyhd8ed1ab_0.conda#158c89bbc0f2597f33e8ce1aea59e0ee
@@ -487,7 +487,7 @@ https://conda.anaconda.org/conda-forge/noarch/nc-time-axis-1.4.1-pyhd8ed1ab_0.ta
 https://conda.anaconda.org/conda-forge/linux-64/ncl-6.6.2-hf70af60_47.conda#ee27133164cb9f5e74681bdb8839688f
 https://conda.anaconda.org/conda-forge/linux-64/nco-5.1.6-hd62b316_0.conda#af7780f76ee37325d264327e21a478f5
 https://conda.anaconda.org/conda-forge/linux-64/psyplot-1.4.3-py311h38be061_1.tar.bz2#f0c9a1067c03e8f05e53ef0c5ad5fab3
-https://conda.anaconda.org/conda-forge/linux-64/py-xgboost-1.7.6-cuda112py311h2344cce_2.conda#cca8982f2b80ffe50124d5cdbbcfdda8
+https://conda.anaconda.org/conda-forge/linux-64/py-xgboost-1.7.6-cuda112py311hba2dd9b_3.conda#8ab84a4da2d1f9f5666a6795d625732e
 https://conda.anaconda.org/conda-forge/noarch/pylint-celery-0.3-py_1.tar.bz2#e29456a611a62d3f26105a2f9c68f759
 https://conda.anaconda.org/conda-forge/noarch/pylint-django-2.5.3-pyhd8ed1ab_0.tar.bz2#00d8853fb1f87195722ea6a582cc9b56
 https://conda.anaconda.org/conda-forge/noarch/pylint-flask-0.6-py_0.tar.bz2#5a9afd3d0a61b08d59eed70fab859c1b
@@ -554,15 +554,15 @@ https://conda.anaconda.org/conda-forge/noarch/r-withr-2.5.0-r41hc72bb7e_1.tar.bz
 https://conda.anaconda.org/conda-forge/linux-64/r-xfun-0.39-r41ha503ecb_0.conda#555ee06849209b9471946da6f09bb98b
 https://conda.anaconda.org/conda-forge/noarch/r-xmlparsedata-1.0.5-r41hc72bb7e_1.tar.bz2#921c0ef7104d8df0ab506f1bb81a062c
 https://conda.anaconda.org/conda-forge/linux-64/r-yaml-2.3.7-r41h133d619_0.conda#4af88071a607237aa73a3cbd51788a39
-https://conda.anaconda.org/conda-forge/linux-64/scikit-image-0.21.0-py311hb755f60_0.conda#0a8cbf18f7e57e43b8e106630a0ca7df
-https://conda.anaconda.org/conda-forge/noarch/seaborn-base-0.12.2-pyhd8ed1ab_0.conda#cf88f3a1c11536bc3c10c14ad00ccc42
-https://conda.anaconda.org/conda-forge/linux-64/statsmodels-0.14.0-py311h1f0f07a_1.conda#a1daa39fa0bfed4d91a3640c2274034a
+https://conda.anaconda.org/conda-forge/linux-64/scikit-image-0.22.0-py311hb755f60_1.conda#8eb9ec7e79696fcb4703374490d7f895
+https://conda.anaconda.org/conda-forge/noarch/seaborn-base-0.13.0-pyhd8ed1ab_0.conda#082666331726b2438986cfe33ae9a8ee
+https://conda.anaconda.org/conda-forge/linux-64/statsmodels-0.14.0-py311h1f0f07a_2.conda#8f1e772e5430ce48229740ec00a90b61
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 https://conda.anaconda.org/conda-forge/linux-64/imagemagick-7.1.1_15-pl5321hf48ede7_0.conda#53c9f7169b61e615d5f41c8d70a72c00
 https://conda.anaconda.org/conda-forge/noarch/iris-3.7.0-pyha770c72_0.conda#dccc1f660bf455c239adaabf56b91dc9
 https://conda.anaconda.org/conda-forge/noarch/lime-0.2.0.1-pyhd8ed1ab_1.tar.bz2#789ce01416721a5533fb74aa4361fd13
 https://conda.anaconda.org/conda-forge/noarch/mapgenerator-1.0.7-pyhd8ed1ab_0.conda#d18db96ef2a920b0ecefe30282b0aecf
-https://conda.anaconda.org/conda-forge/noarch/nbconvert-core-7.8.0-pyhd8ed1ab_0.conda#62345c9e24f898bf492979be84a6eb0a
+https://conda.anaconda.org/conda-forge/noarch/nbconvert-core-7.9.2-pyhd8ed1ab_0.conda#01e4314c780ca73759c694ce3ece281f
 https://conda.anaconda.org/conda-forge/noarch/prospector-1.10.2-pyhd8ed1ab_0.conda#2c536985982f7e531df8d640f554008a
 https://conda.anaconda.org/conda-forge/linux-64/psy-simple-1.4.1-py311h38be061_2.tar.bz2#4c9101d329f6bc09c2617a80e3eb9c89
 https://conda.anaconda.org/conda-forge/noarch/py-cordex-0.6.3-pyhd8ed1ab_0.conda#de9f9392273a1e6095930a21561a37e9
@@ -594,11 +594,11 @@ https://conda.anaconda.org/conda-forge/linux-64/r-spam-2.9_1-r41hb20cf53_1.conda
 https://conda.anaconda.org/conda-forge/linux-64/r-timechange-0.2.0-r41h38f115c_0.conda#04a4229419d779a1e27395d70d493571
 https://conda.anaconda.org/conda-forge/linux-64/r-xml2-1.3.4-r41h1ad5fc0_1.conda#82c1446591783493d65273a158e8ce28
 https://conda.anaconda.org/conda-forge/linux-64/r-zoo-1.8_12-r41h133d619_0.conda#1d432d2eba171727afd03507faa5e2f6
-https://conda.anaconda.org/conda-forge/noarch/seaborn-0.12.2-hd8ed1ab_0.conda#50847a47c07812f88581081c620f5160
+https://conda.anaconda.org/conda-forge/noarch/seaborn-0.13.0-hd8ed1ab_0.conda#ebd31a95a7008b7e164dad9dbbb5bb5a
 https://conda.anaconda.org/conda-forge/noarch/xesmf-0.8.2-pyhd8ed1ab_0.conda#8e765a0eca0ce1cfa889cd9af82a23a8
-https://conda.anaconda.org/conda-forge/linux-64/xgboost-1.7.6-cuda112py311h2344cce_2.conda#97cd4e1589b8ea11e0f78d2f0c7cc217
+https://conda.anaconda.org/conda-forge/linux-64/xgboost-1.7.6-cuda112py311hba2dd9b_3.conda#da95aed99d1fbeebece76cf890cec374
 https://conda.anaconda.org/conda-forge/noarch/dask-2023.9.3-pyhd8ed1ab_0.conda#5b32dc4eb1f5e3097cc33fb0e331b3a4
-https://conda.anaconda.org/conda-forge/noarch/nbconvert-pandoc-7.8.0-pyhd8ed1ab_0.conda#1dba1a577df2625a24667612a069e91c
+https://conda.anaconda.org/conda-forge/noarch/nbconvert-pandoc-7.9.2-pyhd8ed1ab_0.conda#1ad46253f2eb46fb8c9b2c22b7ca012f
 https://conda.anaconda.org/conda-forge/noarch/prov-2.0.0-pyhd3deb0d_0.tar.bz2#aa9b3ad140f6c0668c646f32e20ccf82
 https://conda.anaconda.org/conda-forge/noarch/psy-maps-1.4.2-pyhd8ed1ab_0.tar.bz2#3ed13103dfd46f71dc870d188bd0b276
 https://conda.anaconda.org/conda-forge/linux-64/psy-reg-1.4.0-py311h38be061_3.conda#6f7871722c07922028043144e8873b37
@@ -621,7 +621,7 @@ https://conda.anaconda.org/conda-forge/linux-64/r-specsverification-0.5_3-r41ha5
 https://conda.anaconda.org/conda-forge/linux-64/r-splancs-2.01_43-r41h8da6f51_1.tar.bz2#3a6aad0706541141d10e3b514467a080
 https://conda.anaconda.org/conda-forge/linux-64/r-vctrs-0.6.2-r41ha503ecb_0.conda#1f7610a1863648cab254a9f85bd29dcd
 https://conda.anaconda.org/conda-forge/noarch/iris-esmf-regrid-0.8.0-pyhd8ed1ab_0.conda#56e85460d22fa7d4fb06300f785dd1e1
-https://conda.anaconda.org/conda-forge/noarch/nbconvert-7.8.0-pyhd8ed1ab_0.conda#43bce95e8c474dd21d7ed5de8b4806f7
+https://conda.anaconda.org/conda-forge/noarch/nbconvert-7.9.2-pyhd8ed1ab_0.conda#16ccaddfcfa0a1a606a9ecf6a52d6c11
 https://conda.anaconda.org/conda-forge/noarch/r-cyclocomp-1.1.0-r41hc72bb7e_1005.tar.bz2#800e1da5bf774be48934b8865dd78d33
 https://conda.anaconda.org/conda-forge/noarch/r-gridextra-2.3-r41hc72bb7e_1004.tar.bz2#71ebed7e976df735ff3443bb88bd154f
 https://conda.anaconda.org/conda-forge/noarch/r-httr-1.4.6-r41hc72bb7e_0.conda#53dbb769c96782db54bf2d414fc9b239

From f88b0afa045a83082704c028416d375b6b1c78a5 Mon Sep 17 00:00:00 2001
From: Valeriu Predoi <valeriu.predoi@gmail.com>
Date: Thu, 12 Oct 2023 14:27:32 +0100
Subject: [PATCH 50/93] replace Anaconda badge with dynamicl shield on README
 entry page (#3375)

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 069ce0a0c6..71403fbf90 100644
--- a/README.md
+++ b/README.md
@@ -8,7 +8,7 @@
 [![Codacy Badge](https://app.codacy.com/project/badge/Coverage/79bf6932c2e844eea15d0fb1ed7e415c)](https://www.codacy.com/gh/ESMValGroup/ESMValTool?utm_source=github.com&utm_medium=referral&utm_content=ESMValGroup/ESMValTool&utm_campaign=Badge_Coverage)
 [![Codacy Badge](https://app.codacy.com/project/badge/Grade/79bf6932c2e844eea15d0fb1ed7e415c)](https://www.codacy.com/gh/ESMValGroup/ESMValTool?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=ESMValGroup/ESMValTool&amp;utm_campaign=Badge_Grade)
 [![Docker Build Status](https://img.shields.io/docker/cloud/build/esmvalgroup/esmvaltool.svg)](https://hub.docker.com/r/esmvalgroup/esmvaltool/)
-[![Anaconda-Server Badge](https://anaconda.org/conda-forge/esmvaltool/badges/version.svg)](https://anaconda.org/conda-forge/esmvaltool)
+[![Anaconda-Server Badge](https://img.shields.io/badge/Anaconda.org-2.9.0-blue.svg)](https://anaconda.org/conda-forge/esmvaltool)
 ![stand with Ukraine](https://badgen.net/badge/stand%20with/UKRAINE/?color=0057B8&labelColor=FFD700)
 
 ![esmvaltoollogo](https://raw.githubusercontent.com/ESMValGroup/ESMValTool/main/doc/sphinx/source/figures/ESMValTool-logo-2.png)

From 097e629a2cf8b88037ce0e2a9b21355059725b4b Mon Sep 17 00:00:00 2001
From: Emma Hogan <ehogan@users.noreply.github.com>
Date: Thu, 19 Oct 2023 12:37:25 +0100
Subject: [PATCH 51/93] Add the dataset version in the heatwaves_coldwaves
 recipe to avoid the "Unknown file format" issue on JASMIN (#3373)

Co-authored-by: Valeriu Predoi <valeriu.predoi@gmail.com>
---
 esmvaltool/recipes/recipe_heatwaves_coldwaves.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/esmvaltool/recipes/recipe_heatwaves_coldwaves.yml b/esmvaltool/recipes/recipe_heatwaves_coldwaves.yml
index 6481e33971..aae6491103 100644
--- a/esmvaltool/recipes/recipe_heatwaves_coldwaves.yml
+++ b/esmvaltool/recipes/recipe_heatwaves_coldwaves.yml
@@ -27,7 +27,7 @@ datasets:
   # - {dataset: IPSL-CM5A-MR, type: exp, project: CMIP5, exp: rcp85,
   #    ensemble: r1i1p1, start_year: 2020, end_year: 2040}
   - {dataset: bcc-csm1-1, type: exp, project: CMIP5, exp: historical,
-     ensemble: r1i1p1, start_year: 1971, end_year: 2000}
+     ensemble: r1i1p1, start_year: 1971, end_year: 2000, version: v1}
   - {dataset: bcc-csm1-1, type: exp, project: CMIP5, exp: rcp85,
      ensemble: r1i1p1, start_year: 2060, end_year: 2080}
 

From 5858bf4dc24ac8e17e47f3420a580b727d8f25df Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Mon, 23 Oct 2023 13:54:09 +0100
Subject: [PATCH 52/93] [Condalock] Update Linux condalock file (#3390)

Co-authored-by: valeriupredoi <valeriupredoi@users.noreply.github.com>
---
 conda-linux-64.lock | 80 +++++++++++++++++++++++----------------------
 1 file changed, 41 insertions(+), 39 deletions(-)

diff --git a/conda-linux-64.lock b/conda-linux-64.lock
index a1a14e1190..e77b47d2b9 100644
--- a/conda-linux-64.lock
+++ b/conda-linux-64.lock
@@ -59,7 +59,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libffi-3.4.2-h7f98852_5.tar.bz2#
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 https://conda.anaconda.org/conda-forge/noarch/cf_xarray-0.8.4-pyhd8ed1ab_0.conda#18472f8f9452f962fe0bcb1b8134b494
@@ -487,7 +489,7 @@ https://conda.anaconda.org/conda-forge/noarch/nc-time-axis-1.4.1-pyhd8ed1ab_0.ta
 https://conda.anaconda.org/conda-forge/linux-64/ncl-6.6.2-hf70af60_47.conda#ee27133164cb9f5e74681bdb8839688f
 https://conda.anaconda.org/conda-forge/linux-64/nco-5.1.6-hd62b316_0.conda#af7780f76ee37325d264327e21a478f5
 https://conda.anaconda.org/conda-forge/linux-64/psyplot-1.4.3-py311h38be061_1.tar.bz2#f0c9a1067c03e8f05e53ef0c5ad5fab3
-https://conda.anaconda.org/conda-forge/linux-64/py-xgboost-1.7.6-cuda112py311hba2dd9b_3.conda#8ab84a4da2d1f9f5666a6795d625732e
+https://conda.anaconda.org/conda-forge/linux-64/py-xgboost-1.7.6-cuda118py311he6248c7_5.conda#04c384f45bafbf97696642bb723aa67e
 https://conda.anaconda.org/conda-forge/noarch/pylint-celery-0.3-py_1.tar.bz2#e29456a611a62d3f26105a2f9c68f759
 https://conda.anaconda.org/conda-forge/noarch/pylint-django-2.5.3-pyhd8ed1ab_0.tar.bz2#00d8853fb1f87195722ea6a582cc9b56
 https://conda.anaconda.org/conda-forge/noarch/pylint-flask-0.6-py_0.tar.bz2#5a9afd3d0a61b08d59eed70fab859c1b
@@ -554,7 +556,7 @@ https://conda.anaconda.org/conda-forge/noarch/r-withr-2.5.0-r41hc72bb7e_1.tar.bz
 https://conda.anaconda.org/conda-forge/linux-64/r-xfun-0.39-r41ha503ecb_0.conda#555ee06849209b9471946da6f09bb98b
 https://conda.anaconda.org/conda-forge/noarch/r-xmlparsedata-1.0.5-r41hc72bb7e_1.tar.bz2#921c0ef7104d8df0ab506f1bb81a062c
 https://conda.anaconda.org/conda-forge/linux-64/r-yaml-2.3.7-r41h133d619_0.conda#4af88071a607237aa73a3cbd51788a39
-https://conda.anaconda.org/conda-forge/linux-64/scikit-image-0.22.0-py311hb755f60_1.conda#8eb9ec7e79696fcb4703374490d7f895
+https://conda.anaconda.org/conda-forge/linux-64/scikit-image-0.22.0-py311h320fe9a_2.conda#e94b7f09b52628b89e66cdbd8c3029dd
 https://conda.anaconda.org/conda-forge/noarch/seaborn-base-0.13.0-pyhd8ed1ab_0.conda#082666331726b2438986cfe33ae9a8ee
 https://conda.anaconda.org/conda-forge/linux-64/statsmodels-0.14.0-py311h1f0f07a_2.conda#8f1e772e5430ce48229740ec00a90b61
 https://conda.anaconda.org/conda-forge/linux-64/cdo-2.2.0-he026af2_4.conda#6c00b0a21b3de8a149eee137e83465d3
@@ -563,9 +565,9 @@ https://conda.anaconda.org/conda-forge/noarch/iris-3.7.0-pyha770c72_0.conda#dccc
 https://conda.anaconda.org/conda-forge/noarch/lime-0.2.0.1-pyhd8ed1ab_1.tar.bz2#789ce01416721a5533fb74aa4361fd13
 https://conda.anaconda.org/conda-forge/noarch/mapgenerator-1.0.7-pyhd8ed1ab_0.conda#d18db96ef2a920b0ecefe30282b0aecf
 https://conda.anaconda.org/conda-forge/noarch/nbconvert-core-7.9.2-pyhd8ed1ab_0.conda#01e4314c780ca73759c694ce3ece281f
-https://conda.anaconda.org/conda-forge/noarch/prospector-1.10.2-pyhd8ed1ab_0.conda#2c536985982f7e531df8d640f554008a
+https://conda.anaconda.org/conda-forge/noarch/prospector-1.10.3-pyhd8ed1ab_0.conda#f551d4d859a1d70c6abff8310a655481
 https://conda.anaconda.org/conda-forge/linux-64/psy-simple-1.4.1-py311h38be061_2.tar.bz2#4c9101d329f6bc09c2617a80e3eb9c89
-https://conda.anaconda.org/conda-forge/noarch/py-cordex-0.6.3-pyhd8ed1ab_0.conda#de9f9392273a1e6095930a21561a37e9
+https://conda.anaconda.org/conda-forge/noarch/py-cordex-0.6.4-pyhd8ed1ab_0.conda#a30ffe78645b5777aa21d3e0f2d2a015
 https://conda.anaconda.org/conda-forge/linux-64/pyarrow-12.0.1-py311h39c9aba_7_cpu.conda#d513ab8d10ec5f3ee45b419c836195ec
 https://conda.anaconda.org/conda-forge/linux-64/pydot-1.4.2-py311h38be061_4.conda#5c223cb0d9c05552bf9d1586a92720b2
 https://conda.anaconda.org/conda-forge/linux-64/r-askpass-1.1-r41h06615bd_3.tar.bz2#c8ec8683302ad9a2345cb31ab28e6c6b
@@ -596,8 +598,8 @@ https://conda.anaconda.org/conda-forge/linux-64/r-xml2-1.3.4-r41h1ad5fc0_1.conda
 https://conda.anaconda.org/conda-forge/linux-64/r-zoo-1.8_12-r41h133d619_0.conda#1d432d2eba171727afd03507faa5e2f6
 https://conda.anaconda.org/conda-forge/noarch/seaborn-0.13.0-hd8ed1ab_0.conda#ebd31a95a7008b7e164dad9dbbb5bb5a
 https://conda.anaconda.org/conda-forge/noarch/xesmf-0.8.2-pyhd8ed1ab_0.conda#8e765a0eca0ce1cfa889cd9af82a23a8
-https://conda.anaconda.org/conda-forge/linux-64/xgboost-1.7.6-cuda112py311hba2dd9b_3.conda#da95aed99d1fbeebece76cf890cec374
-https://conda.anaconda.org/conda-forge/noarch/dask-2023.9.3-pyhd8ed1ab_0.conda#5b32dc4eb1f5e3097cc33fb0e331b3a4
+https://conda.anaconda.org/conda-forge/linux-64/xgboost-1.7.6-cuda118py311he6248c7_5.conda#00f60bd90006f639468ae33a764b966c
+https://conda.anaconda.org/conda-forge/noarch/dask-2023.10.0-pyhd8ed1ab_0.conda#0c85f5482dd283c2b9ca68d331edb471
 https://conda.anaconda.org/conda-forge/noarch/nbconvert-pandoc-7.9.2-pyhd8ed1ab_0.conda#1ad46253f2eb46fb8c9b2c22b7ca012f
 https://conda.anaconda.org/conda-forge/noarch/prov-2.0.0-pyhd3deb0d_0.tar.bz2#aa9b3ad140f6c0668c646f32e20ccf82
 https://conda.anaconda.org/conda-forge/noarch/psy-maps-1.4.2-pyhd8ed1ab_0.tar.bz2#3ed13103dfd46f71dc870d188bd0b276

From 3e7ff2110a9e235e581b5ff33676fec0796feda9 Mon Sep 17 00:00:00 2001
From: Bouwe Andela <b.andela@esciencecenter.nl>
Date: Thu, 26 Oct 2023 14:48:41 +0200
Subject: [PATCH 53/93] Fix documentation build (#3397)

---
 doc/sphinx/source/conf.py | 11 ++++++++++-
 1 file changed, 10 insertions(+), 1 deletion(-)

diff --git a/doc/sphinx/source/conf.py b/doc/sphinx/source/conf.py
index 6257289715..5ef08c3b06 100644
--- a/doc/sphinx/source/conf.py
+++ b/doc/sphinx/source/conf.py
@@ -153,7 +153,16 @@
 # Theme options are theme-specific and customize the look and feel of a theme
 # further.  For a list of options available for each theme, see the
 # documentation.
-# html_theme_options = {}
+#
+# Avoid the following warning issued by pydata_sphinx_theme:
+#
+# "WARNING: The default value for `navigation_with_keys` will change to `False`
+# in the next release. If you wish to preserve the old behavior for your site,
+# set `navigation_with_keys=True` in the `html_theme_options` dict in your
+# `conf.py` file.Be aware that `navigation_with_keys = True` has negative
+# accessibility implications:
+# https://github.com/pydata/pydata-sphinx-theme/issues/1492"
+html_theme_options = {"navigation_with_keys": False}
 
 # Add any paths that contain custom themes here, relative to this directory.
 # html_theme_path = []

From 604f6fb18c43ed9ea0c91b5446a1de0a3790e2c4 Mon Sep 17 00:00:00 2001
From: Bouwe Andela <b.andela@esciencecenter.nl>
Date: Thu, 26 Oct 2023 18:14:44 +0200
Subject: [PATCH 54/93] Add a realistic example recipe (#3356)

---
 .../IPCC_AR6_figure_9.3a_1850-2100.png        | Bin 0 -> 183259 bytes
 doc/sphinx/source/recipes/index.rst           |   1 +
 doc/sphinx/source/recipes/recipe_examples.rst |  29 ++--
 esmvaltool/diag_scripts/examples/make_plot.py |  76 +++++++++++
 .../recipes/examples/recipe_easy_ipcc.yml     | 126 ++++++++++++++++++
 esmvaltool/references/fox-kemper21ipcc.bibtex |  11 ++
 6 files changed, 235 insertions(+), 8 deletions(-)
 create mode 100644 doc/sphinx/source/recipes/figures/examples/IPCC_AR6_figure_9.3a_1850-2100.png
 create mode 100644 esmvaltool/diag_scripts/examples/make_plot.py
 create mode 100644 esmvaltool/recipes/examples/recipe_easy_ipcc.yml
 create mode 100644 esmvaltool/references/fox-kemper21ipcc.bibtex

diff --git a/doc/sphinx/source/recipes/figures/examples/IPCC_AR6_figure_9.3a_1850-2100.png b/doc/sphinx/source/recipes/figures/examples/IPCC_AR6_figure_9.3a_1850-2100.png
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z63T0|R+**^Hl(j1I-Gc^n3-o`ZV4d8@~J=YbJ-_<9_vPGs$_df$NNB34K+k-%VN~?
zy_mQGdF~a0P5~ZHi>0Y&TdA1)c;fL3H^_p=R8Jft;-f!r*`r9pcc)=_&?eKHj#}Hw
zmAvrLo@o_W?=;qDJ>*0*GHtwleCU;zmywJn9BCUJDM(~^9}f0fM>CE#pC*+nqwJ^;
zy`E*P#lZH&i=x^~YKTGeS%yVs);%tlt7VHPPxkv4{>2pks8crDTT`Q+YgAVeJw`|^
z+%=(XUOiQDnzb3L!Ny3El;nI0#U#zzK<vXmv&<Q7ni>}gGh~e=3C<TzPPVX05vWLb
z`ozQpGB(n<MgQX{f227pKK$Qy=Kk9(!2e%PG#69!q~d3tCCfCAQP>@{KfwL?%WwYy
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HcmV?d00001

diff --git a/doc/sphinx/source/recipes/index.rst b/doc/sphinx/source/recipes/index.rst
index 57c77e8b30..1cb182f39b 100644
--- a/doc/sphinx/source/recipes/index.rst
+++ b/doc/sphinx/source/recipes/index.rst
@@ -99,6 +99,7 @@ IPCC
    recipe_ipccwg1ar6ch3
    recipe_ipccwg1ar5ch9
    recipe_collins13ipcc
+   recipe_examples
 
 Land
 ^^^^
diff --git a/doc/sphinx/source/recipes/recipe_examples.rst b/doc/sphinx/source/recipes/recipe_examples.rst
index 5874e2c1c4..e3c32c4337 100644
--- a/doc/sphinx/source/recipes/recipe_examples.rst
+++ b/doc/sphinx/source/recipes/recipe_examples.rst
@@ -8,20 +8,26 @@ Overview
 
 These are example recipes calling example diagnostic scripts.
 
-The recipe examples/recipe_python.yml produces time series plots of global mean
+The recipe ``examples/recipe_python.yml`` produces time series plots of global mean
 temperature and for the temperature in Amsterdam.
 It also produces a map of global temperature in January 2020.
 
-The recipe examples/recipe_extract_shape.yml produces a map of the mean
+The recipe ``examples/recipe_easy_ipcc.yml`` reproduces part of figure 9.3a from
+`IPCC AR6 - Climate Change 2021: The Physical Science Basis <https://www.ipcc.ch/report/sixth-assessment-report-working-group-i/>`__.
+It demonstrates how ESMValTool can be used to conveniently analyze
+many models on their native grid and is described in detail in the blog post
+`Analysis-ready climate data with ESMValCore <https://blog.esciencecenter.nl/easy-ipcc-powered-by-esmvalcore-19a0b6366ea7>`__.
+
+The recipe ``examples/recipe_extract_shape.yml`` produces a map of the mean
 temperature in the Elbe catchment over the years 2000 to 2002.
 Some example shapefiles for use with this recipe are available
 `here <https://github.com/ESMValGroup/ESMValTool/tree/main/esmvaltool/diag_scripts/shapeselect/testdata>`__,
 make sure to download all files with the same name but different extensions.
 
-The recipe examples/recipe_julia.yml produces a map plot with the mean temperature
+The recipe ``examples/recipe_julia.yml`` produces a map plot with the mean temperature
 over the year 1997 plus a number that is configurable from the recipe.
 
-The recipe examples/recipe_decadal.yml showcases how the ``timerange`` tag
+The recipe ``examples/recipe_decadal.yml`` showcases how the ``timerange`` tag
 can be used to load datasets belonging to the DCPP activity. Produces timeseries
 plots comparing the global mean temperature of a DCPP dataset with an observational
 dataset.
@@ -29,16 +35,16 @@ dataset.
 Available recipes and diagnostics
 ---------------------------------
 
-Recipes are stored in esmvaltool/recipes/
-
+Recipes are stored in `esmvaltool/recipes/ <https://github.com/ESMValGroup/ESMValTool/tree/main/esmvaltool/recipes>`__:
     * examples/recipe_python.yml
+    * examples/recipe_easy_ipcc.yml
     * examples/recipe_extract_shape.yml
     * examples/recipe_julia.yml
     * examples/recipe_decadal.yml
 
-Diagnostics are stored in esmvaltool/diag_scripts/
-
+Diagnostics are stored in `esmvaltool/diag_scripts/ <https://github.com/ESMValGroup/ESMValTool/tree/main/esmvaltool/diag_scripts>`__:
     * examples/diagnostic.py: visualize results and store provenance information
+    * examples/make_plot.py: Create a timeseries plot with likely ranges
     * examples/diagnostic.jl: visualize results and store provenance information
     * examples/decadal_example.py: visualize results and store provenance information
 
@@ -63,6 +69,7 @@ Variables
 ---------
 
 * tas (atmos, monthly, longitude, latitude, time)
+* tos (ocean, monthly, longitude, latitude, time)
 
 Example plots
 -------------
@@ -79,6 +86,12 @@ Example plots
 
    Amsterdam air temperature (multimodel mean of CMIP5 CanESM2 and CMIP6 BCC-ESM1).
 
+.. _easy_ipcc:
+.. figure:: /recipes/figures/examples/IPCC_AR6_figure_9.3a_1850-2100.png
+   :align:   center
+
+   Mean sea surface temperature anomaly (part of figure 9.3a from IPCC AR6).
+
 .. _elbe:
 .. figure::  /recipes/figures/examples/elbe.png
    :align:   center
diff --git a/esmvaltool/diag_scripts/examples/make_plot.py b/esmvaltool/diag_scripts/examples/make_plot.py
new file mode 100644
index 0000000000..b2aa4158f5
--- /dev/null
+++ b/esmvaltool/diag_scripts/examples/make_plot.py
@@ -0,0 +1,76 @@
+"""Python example diagnostic."""
+import logging
+from pathlib import Path
+
+import iris
+import matplotlib.pyplot as plt
+
+from esmvaltool.diag_scripts.shared import run_diagnostic, save_figure
+
+logger = logging.getLogger(Path(__file__).stem)
+
+
+def main(cfg):
+    """Plot part of figure_9.3a from IPCC AR6."""
+    colors = {
+        'historical-ssp126': '#2a3652',
+        'historical-ssp585': '#78333a',
+    }
+    fill_colors = {
+        'historical-ssp126': '#d2d5dc',
+        'historical-ssp585': '#ddced2',
+    }
+    labels = {
+        'historical-ssp126': 'Historical and SSP1-2.6',
+        'historical-ssp585': 'Historical and SSP5-8.5',
+    }
+
+    # Group input data by experiment
+    groups = {}
+    for filename, attributes in cfg['input_data'].items():
+        exp = attributes['exp']
+        if exp not in groups:
+            groups[exp] = {}
+        groups[exp][attributes['dataset']] = filename
+
+    # Loop over experiments to populate plot
+    for exp, group in groups.items():
+        mean = iris.load_cube(group['MultiModelMean'])
+        iris.quickplot.plot(
+            mean,
+            color=colors.get(exp),
+            label=labels.get(exp, exp),
+        )
+
+        p17 = iris.load_cube(group['MultiModelP17'])
+        p83 = iris.load_cube(group['MultiModelP83'])
+        time_coord = mean.coord('time')
+        time_axis = time_coord.units.num2date(time_coord.core_points())
+        plt.fill_between(
+            time_axis,
+            p17.core_data(),
+            p83.core_data(),
+            color=fill_colors.get(exp),
+            label='Likely (17% - 83%) ranges',
+        )
+
+    plt.title('Sea surface temperature anomaly')
+    plt.legend(loc='upper left')
+
+    filename = 'IPCC_AR6_figure_9.3a_1850-2100'
+    provenance_record = {
+        'caption': "Part of figure 9.3a from IPCC AR6.",
+        'authors': [
+            'kalverla_peter',
+            'andela_bouwe',
+        ],
+        'references': ['fox-kemper21ipcc'],
+        'ancestors': list(cfg['input_data'].keys()),
+    }
+    save_figure(filename, provenance_record, cfg, dpi=300)
+
+
+if __name__ == '__main__':
+
+    with run_diagnostic() as config:
+        main(config)
diff --git a/esmvaltool/recipes/examples/recipe_easy_ipcc.yml b/esmvaltool/recipes/examples/recipe_easy_ipcc.yml
new file mode 100644
index 0000000000..7f5696e2b9
--- /dev/null
+++ b/esmvaltool/recipes/examples/recipe_easy_ipcc.yml
@@ -0,0 +1,126 @@
+documentation:
+  title: Easy IPCC
+  description: Reproduce part of IPCC AR6 figure 9.3a.
+  references:
+    - fox-kemper21ipcc
+  authors:
+    - kalverla_peter
+    - andela_bouwe
+  maintainer:
+    - andela_bouwe
+
+preprocessors:
+  easy_ipcc:
+    custom_order: true
+    anomalies:
+      period: month
+      reference:
+        start_year: 1950
+        start_month: 1
+        start_day: 1
+        end_year: 1979
+        end_month: 12
+        end_day: 31
+    area_statistics:
+      operator: mean
+    annual_statistics:
+      operator: mean
+    convert_units:
+      units: 'degrees_C'
+    ensemble_statistics:
+      statistics:
+        - mean
+    multi_model_statistics:
+      statistics:
+        - mean
+        - p17
+        - p83
+      span: full
+      keep_input_datasets: false
+      ignore_scalar_coords: true
+
+diagnostics:
+  AR6_Figure_9.3:
+    variables:
+      tos_ssp585:
+        short_name: tos
+        exp: ['historical', 'ssp585']
+        project: CMIP6
+        mip: Omon
+        preprocessor: easy_ipcc
+        timerange: '1850/2100'
+      tos_ssp126:
+        short_name: tos
+        exp: ['historical', 'ssp126']
+        project: CMIP6
+        mip: Omon
+        timerange: '1850/2100'
+        preprocessor: easy_ipcc
+    scripts:
+      Figure_9.3a:
+        script: examples/make_plot.py
+
+datasets:
+  - {dataset: ACCESS-CM2, ensemble: 'r(1:5)i1p1f1', grid: gn}
+  - {dataset: ACCESS-ESM1-5, ensemble: 'r(1:40)i1p1f1', grid: gn}
+  - {dataset: AWI-CM-1-1-MR, ensemble: r1i1p1f1, grid: gn}
+  - {dataset: BCC-CSM2-MR, ensemble: r1i1p1f1, grid: gn}
+  # - {dataset: CAMS-CSM1-0, ensemble: 'r(1:2)i1p1f1', grid: gn} # available data does not fully cover timerange
+  - {dataset: CAS-ESM2-0, ensemble: r1i1p1f1, grid: gn}
+  - {dataset: CAS-ESM2-0, ensemble: r3i1p1f1, grid: gn}
+  - {dataset: CESM2, ensemble: r4i1p1f1, grid: gn}
+  - {dataset: CESM2, ensemble: 'r(10:11)i1p1f1', grid: gn}
+  - {dataset: CESM2-WACCM, ensemble: r1i1p1f1, grid: gn}
+  - {dataset: CIESM, ensemble: r1i1p1f1, grid: gn}
+  - {dataset: CMCC-CM2-SR5, ensemble: r1i1p1f1, grid: gn}
+  - {dataset: CMCC-ESM2, ensemble: r1i1p1f1, grid: gn}
+  - {dataset: CNRM-CM6-1, ensemble: 'r(1:6)i1p1f2', grid: gn}
+  - {dataset: CNRM-CM6-1-HR, ensemble: r1i1p1f2, grid: gn}
+  - {dataset: CNRM-ESM2-1, ensemble: 'r(1:5)i1p1f2', grid: gn}
+  - {dataset: CanESM5, ensemble: 'r(1:25)i1p(1:2)f1', grid: gn}
+  - {dataset: CanESM5-1, ensemble: 'r1i1p(1:2)f1', grid: gn, institute: CCCma}
+  - {dataset: CanESM5-CanOE, ensemble: 'r(1:3)i1p2f1', grid: gn}
+  - {dataset: EC-Earth3, ensemble: r1i1p1f1, grid: gn}
+  - {dataset: EC-Earth3, ensemble: r4i1p1f1, grid: gn}
+  - {dataset: EC-Earth3, ensemble: r6i1p1f1, grid: gn}
+  # - {dataset: EC-Earth3, ensemble: r9i1p1f1, grid: gn}  # download failure of ssp585
+  - {dataset: EC-Earth3, ensemble: r11i1p1f1, grid: gn}
+  - {dataset: EC-Earth3, ensemble: r15i1p1f1, grid: gn}
+  # - {dataset: EC-Earth3, ensemble: 'r(101:150)i1p1f1', grid: gn}  # available data does not fully cover timerange
+  - {dataset: EC-Earth3-Veg, ensemble: 'r(1:4)i1p1f1', grid: gn}
+  - {dataset: EC-Earth3-Veg, ensemble: r6i1p1f1, grid: gn}
+  # - {dataset: EC-Earth3-Veg-LR, ensemble: 'r(1:3)i1p1f1', grid: gn}  # mismatch between i and j coordinate names between historical and ssp experiment
+  - {dataset: FGOALS-f3-L, ensemble: 'r(1:3)i1p1f1', grid: gn}
+  - {dataset: FGOALS-g3, ensemble: 'r(1:4)i1p1f1', grid: gn}
+  - {dataset: FIO-ESM-2-0, ensemble: 'r(1:3)i1p1f1', grid: gn}
+  - {dataset: GFDL-ESM4, ensemble: r1i1p1f1, grid: gn}
+  - {dataset: GISS-E2-1-G, ensemble: 'r(1:4)i1p5f1', grid: gn, supplementary_variables: [{short_name: areacella, mip: fx, exp: piControl, ensemble: r1i1p5f1}, {short_name: areacello, skip: true}]}
+  - {dataset: GISS-E2-1-G, ensemble: 'r(1:5)i1p1f2', grid: gn, supplementary_variables: [{short_name: areacella, mip: fx, exp: piControl, ensemble: r1i1p1f1}, {short_name: areacello, skip: true}]}
+  - {dataset: GISS-E2-1-G, ensemble: 'r(1:5)i1p3f1', grid: gn, supplementary_variables: [{short_name: areacella, mip: fx, exp: piControl, ensemble: r1i1p3f1}, {short_name: areacello, skip: true}]}
+  - {dataset: GISS-E2-1-H, ensemble: 'r(1:5)i1p1f2', grid: gn, supplementary_variables: [{short_name: areacella, mip: fx, exp: piControl, ensemble: r1i1p1f1}, {short_name: areacello, skip: true}]}
+  - {dataset: GISS-E2-1-H, ensemble: 'r(1:5)i1p3f1', grid: gn, supplementary_variables: [{short_name: areacella, mip: fx, exp: piControl, ensemble: r1i1p3f1}, {short_name: areacello, skip: true}]}
+  - {dataset: GISS-E2-2-G, ensemble: 'r(1:5)i1p3f1', grid: gn, supplementary_variables: [{short_name: areacella, mip: fx, exp: piControl, ensemble: r1i1p1f1}, {short_name: areacello, skip: true}]}
+  - {dataset: HadGEM3-GC31-LL, ensemble: r1i1p1f3, grid: gn}
+  - {dataset: HadGEM3-GC31-MM, ensemble: r1i1p1f3, grid: gn}
+  # - {dataset: IITM-ESM, ensemble: r1i1p1f1, grid: gn}  # available data does not fully cover timerange
+  - {dataset: INM-CM4-8, ensemble: r1i1p1f1, grid: gr1}
+  - {dataset: INM-CM5-0, ensemble: r1i1p1f1, grid: gr1}
+  - {dataset: IPSL-CM6A-LR, ensemble: 'r(1:4)i1p1f1', grid: gn}
+  - {dataset: IPSL-CM6A-LR, ensemble: r6i1p1f1, grid: gn}
+  - {dataset: IPSL-CM6A-LR, ensemble: r14i1p1f1, grid: gn}
+  # - {dataset: KACE-1-0-G, ensemble: 'r(1:3)i1p1f1', grid: gr}  # unstructured grid but no cell area information available
+  # - {dataset: KIOST-ESM, ensemble: r1i1p1f1, grid: gr1}  # historical and ssp126 experiment are on different grids
+  - {dataset: MCM-UA-1-0, ensemble: r1i1p1f2, grid: gn}
+  - {dataset: MIROC-ES2H, ensemble: r1i1p4f2, grid: gn}
+  - {dataset: MIROC-ES2L, ensemble: 'r(1:10)i1p1f2', grid: gn}
+  - {dataset: MIROC6, ensemble: 'r(1:50)i1p1f1', grid: gn}
+  - {dataset: MPI-ESM1-2-HR, ensemble: 'r1i1p1f1', grid: gn}
+  # - {dataset: MPI-ESM1-2-HR, ensemble: 'r(1:2)i1p1f1', grid: gn}  # second ensemble member causes warnings about large graphs in `concatenate` preprocessor step
+  - {dataset: MPI-ESM1-2-LR, ensemble: 'r(1:30)i1p1f1', grid: gn}
+  - {dataset: MRI-ESM2-0, ensemble: 'r(1:5)i1p1f1', grid: gn}
+  # - {dataset: NESM3, ensemble: 'r(1:2)i1p1f1', grid: gn}  # cannot be used due to https://github.com/ESMValGroup/ESMValCore/issues/2101
+  # - {dataset: NorESM2-LM, ensemble: r1i1p1f1, grid: gn}  # duplicated areacello file with wrong name
+  - {dataset: NorESM2-MM, ensemble: r1i1p1f1, grid: gn}
+  - {dataset: TaiESM1, ensemble: r1i1p1f1, grid: gn}
+  - {dataset: UKESM1-0-LL, ensemble: 'r(1:4)i1p1f2', grid: gn}
+  - {dataset: UKESM1-0-LL, ensemble: r8i1p1f2, grid: gn}
diff --git a/esmvaltool/references/fox-kemper21ipcc.bibtex b/esmvaltool/references/fox-kemper21ipcc.bibtex
new file mode 100644
index 0000000000..e26a480f46
--- /dev/null
+++ b/esmvaltool/references/fox-kemper21ipcc.bibtex
@@ -0,0 +1,11 @@
+@inbook{fox-kemper21ipcc,
+  author={B. Fox-Kemper and H.T. Hewitt and C. Xiao and G. Aðalgeirsdóttir and S.S. Drijfhout and T.L. Edwards and N.R. Golledge and M. Hemer and R.E. Kopp and G. Krinner and A. Mix and D. Notz and S. Nowicki and I.S. Nurhati and L. Ruiz and J.-B. Sallée and A.B.A. Slangen and Y. Yu},
+  editor={V. Masson-Delmotte and P. Zhai and A. Pirani and S.L. Connors and C. Pean and S. Berger and N. Caud and Y. Chen and L. Goldfarb and M.I. Gomis and M. Huang and K. Leitzell and E. Lonnoy and J.B.R. Matthews and T.K. Maycock and T. Waterfield and O. Yelekci and R. Yu and B. Zhou},
+  title={Ocean, Cryosphere and Sea Level Change},
+  booktitle={Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change},
+  year={2021},
+  publisher={Cambridge University Press},
+  address={Cambridge, UK and New York, NY, USA},
+  pages = {1211--1362},
+  doi={10.1017/9781009157896.011}
+}

From 1d05511e11519cb0de42bd85f27291b0163ef602 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Tue, 31 Oct 2023 13:57:32 +0000
Subject: [PATCH 55/93] [Condalock] Update Linux condalock file (#3400)

Co-authored-by: valeriupredoi <valeriupredoi@users.noreply.github.com>
---
 conda-linux-64.lock | 82 ++++++++++++++++++++++-----------------------
 1 file changed, 41 insertions(+), 41 deletions(-)

diff --git a/conda-linux-64.lock b/conda-linux-64.lock
index e77b47d2b9..c5310d91b3 100644
--- a/conda-linux-64.lock
+++ b/conda-linux-64.lock
@@ -30,7 +30,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-13.2.0-h807b86a_2.cond
 https://conda.anaconda.org/conda-forge/linux-64/aom-3.5.0-h27087fc_0.tar.bz2#a08150fd2298460cd1fcccf626305642
 https://conda.anaconda.org/conda-forge/linux-64/aws-c-common-0.8.23-hd590300_0.conda#cc4f06f7eedb1523f3b83fd0fb3942ff
 https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-h7f98852_4.tar.bz2#a1fd65c7ccbf10880423d82bca54eb54
-https://conda.anaconda.org/conda-forge/linux-64/c-ares-1.20.1-hd590300_0.conda#6642e4faa4804be3a0e7edfefbd16595
+https://conda.anaconda.org/conda-forge/linux-64/c-ares-1.20.1-hd590300_1.conda#2facbaf5ee1a56967aecaee89799160e
 https://conda.anaconda.org/conda-forge/linux-64/charls-2.4.2-h59595ed_0.conda#4336bd67920dd504cd8c6761d6a99645
 https://conda.anaconda.org/conda-forge/linux-64/dav1d-1.2.1-hd590300_0.conda#418c6ca5929a611cbd69204907a83995
 https://conda.anaconda.org/conda-forge/linux-64/freexl-1.0.6-h166bdaf_1.tar.bz2#897e772a157faf3330d72dd291486f62
@@ -79,7 +79,7 @@ https://conda.anaconda.org/conda-forge/linux-64/nccl-2.19.3.1-h6103f9b_0.conda#5
 https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.4-hcb278e6_0.conda#681105bccc2a3f7f1a837d47d39c9179
 https://conda.anaconda.org/conda-forge/linux-64/nspr-4.35-h27087fc_0.conda#da0ec11a6454ae19bff5b02ed881a2b1
 https://conda.anaconda.org/conda-forge/linux-64/openlibm-0.8.1-h7f98852_0.tar.bz2#ba0c56761f2380babaa783b2a37b4d08
-https://conda.anaconda.org/conda-forge/linux-64/openssl-3.1.3-hd590300_0.conda#7bb88ce04c8deb9f7d763ae04a1da72f
+https://conda.anaconda.org/conda-forge/linux-64/openssl-3.1.4-hd590300_0.conda#412ba6938c3e2abaca8b1129ea82e238
 https://conda.anaconda.org/conda-forge/linux-64/p7zip-16.02-h9c3ff4c_1001.tar.bz2#941066943c0cac69d5aa52189451aa5f
 https://conda.anaconda.org/conda-forge/linux-64/pixman-0.42.2-h59595ed_0.conda#700edd63ccd5fc66b70b1c028cea9a68
 https://conda.anaconda.org/conda-forge/linux-64/pkg-config-0.29.2-h36c2ea0_1008.tar.bz2#fbef41ff6a4c8140c30057466a1cdd47
@@ -120,7 +120,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libevent-2.1.12-hf998b51_1.conda
 https://conda.anaconda.org/conda-forge/linux-64/libgfortran-ng-13.2.0-h69a702a_2.conda#e75a75a6eaf6f318dae2631158c46575
 https://conda.anaconda.org/conda-forge/linux-64/libkml-1.3.0-h01aab08_1016.conda#4d0907546d556ef7f14b1dcfa0e217ce
 https://conda.anaconda.org/conda-forge/linux-64/libllvm14-14.0.6-hcd5def8_4.conda#73301c133ded2bf71906aa2104edae8b
-https://conda.anaconda.org/conda-forge/linux-64/libnghttp2-1.52.0-h61bc06f_0.conda#613955a50485812985c059e7b269f42e
+https://conda.anaconda.org/conda-forge/linux-64/libnghttp2-1.55.1-h47da74e_0.conda#a802251d1eaeeae041c867faf0f94fa8
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 https://conda.anaconda.org/conda-forge/noarch/r-cyclocomp-1.1.0-r41hc72bb7e_1005.tar.bz2#800e1da5bf774be48934b8865dd78d33
 https://conda.anaconda.org/conda-forge/noarch/r-gridextra-2.3-r41hc72bb7e_1004.tar.bz2#71ebed7e976df735ff3443bb88bd154f
 https://conda.anaconda.org/conda-forge/noarch/r-httr-1.4.6-r41hc72bb7e_0.conda#53dbb769c96782db54bf2d414fc9b239
@@ -650,7 +650,7 @@ https://conda.anaconda.org/conda-forge/noarch/r-lintr-3.0.2-r41hc72bb7e_0.tar.bz
 https://conda.anaconda.org/conda-forge/noarch/r-s2dverification-2.10.3-r41hc72bb7e_1.tar.bz2#2253f130c8dab435824d6ddb10a41c73
 https://conda.anaconda.org/conda-forge/noarch/autodocsumm-0.2.6-pyhd8ed1ab_0.tar.bz2#4409dd7e06a62c3b2aa9e96782c49c6d
 https://conda.anaconda.org/conda-forge/noarch/nbsphinx-0.9.3-pyhd8ed1ab_0.conda#0dbaa7d08d3d79b2a1a4dd6a02cc4581
-https://conda.anaconda.org/conda-forge/noarch/pydata-sphinx-theme-0.14.1-pyhd8ed1ab_0.conda#78153addf629c51fab775ef360012ca3
+https://conda.anaconda.org/conda-forge/noarch/pydata-sphinx-theme-0.14.3-pyhd8ed1ab_0.conda#3a52e29fde69705040bcbe74cbdcbd5c
 https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-applehelp-1.0.7-pyhd8ed1ab_0.conda#aebfabcb60c33a89c1f9290cab49bc93
 https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-devhelp-1.0.5-pyhd8ed1ab_0.conda#ebf08f5184d8eaa486697bc060031953
 https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-htmlhelp-2.0.4-pyhd8ed1ab_0.conda#a9a89000dfd19656ad004b937eeb6828

From 6395bde0463870e34f0ff12bbfb04a59b2a2cd88 Mon Sep 17 00:00:00 2001
From: Bouwe Andela <b.andela@esciencecenter.nl>
Date: Wed, 1 Nov 2023 09:51:46 +0100
Subject: [PATCH 56/93] Minor updates to release tools (#3216)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Co-authored-by: Rémi Kazeroni <remi.kazeroni@dlr.de>
Co-authored-by: Valeriu Predoi <valeriu.predoi@gmail.com>
---
 doc/sphinx/source/utils.rst                   |  7 ++-
 esmvaltool/utils/batch-jobs/generate.py       | 63 ++++++++++++-------
 .../utils/batch-jobs/parse_recipes_output.py  | 10 +--
 esmvaltool/utils/draft_release_notes.py       | 26 ++++----
 .../utils/testing/regression/compare.py       | 15 +++--
 5 files changed, 74 insertions(+), 47 deletions(-)

diff --git a/doc/sphinx/source/utils.rst b/doc/sphinx/source/utils.rst
index 5e46d06d81..e5e7b00553 100644
--- a/doc/sphinx/source/utils.rst
+++ b/doc/sphinx/source/utils.rst
@@ -246,7 +246,8 @@ Optionally, the following parameters can be edited:
 * ``partition``, *str*: Name of the DKRZ partition used to run jobs. Default is ``interactive`` to minimize computing cost compared to ``compute`` for which nodes cannot be shared.
 * ``memory``, *str*: Amount of memory requested for each run. Default is ``64G`` to allow to run 4 recipes on the same node in parallel.
 * ``time``, *str*: Time limit. Default is ``04:00:00`` to increase the job priority. Jobs can run for up to 8 hours and 12 hours on the compute and interactive partitions, respectively.
-
+* ``default_max_parallel_tasks``, *int*: Default is ``8`` which works for most recipes. For other cases, an entry needs to be made to the ``MAX_PARALLEL_TASKS`` dictionary (see below).
+  
 The script will generate a submission script for all recipes using by default the ``interactive`` queue and with a time limit of 4h. In case a recipe
 may require of additional resources, they can be defined in the ``SPECIAL_RECIPES`` dictionary. The recipe name has to be given as a ``key`` in which the
 values are another dictionary. 
@@ -263,8 +264,8 @@ given by the slurm flags ``--mem``, ``--constraint`` or ``--ntasks``. In general
         },
    }
 
-Some recipes can only be run with ``--max_parallel_tasks=1`` for various reasons (memory issues, diagnostic issues, CMIP3 data used).
-These recipes need to be added to the ``ONE_TASK_RECIPES`` list.
+Some recipes can only be run with a number of tasks less than ``default_max_parallel_tasks`` for various reasons (memory issues, diagnostic issues, CMIP3 data used).
+These recipes need to be added to the ``MAX_PARALLEL_TASKS`` dictionary with a specific ``max_parallel_tasks`` value.
 
 Note that the script has been optimized to use standard SLURM settings to run most recipes while minimizing the computational cost of the jobs and tailored runtime settings for resource-intensive recipes.
 It is only necessary to edit this script for recipes that have been added since the last release and cannot be run with the default settings.
diff --git a/esmvaltool/utils/batch-jobs/generate.py b/esmvaltool/utils/batch-jobs/generate.py
index dd7a46d83f..fc9deb8339 100644
--- a/esmvaltool/utils/batch-jobs/generate.py
+++ b/esmvaltool/utils/batch-jobs/generate.py
@@ -51,6 +51,9 @@
 # Full path to config_file
 # If none, ~/.esmvaltool/config-user.yml is used
 config_file = ''
+# Set max_parallel_tasks
+# If none, read from config_file
+default_max_parallel_tasks = 8
 
 # List of recipes that require non-default SLURM options set above
 SPECIAL_RECIPES = {
@@ -74,12 +77,17 @@
     },
     'recipe_climate_change_hotspot': {
         'partition': '#SBATCH --partition=compute \n',
+        'memory': '#SBATCH --constraint=512G \n',
     },
     'recipe_collins13ipcc': {
         'partition': '#SBATCH --partition=compute \n',
         'time': '#SBATCH --time=08:00:00 \n',
         'memory': '#SBATCH --constraint=512G \n',
     },
+    'recipe_daily_era5': {
+        'partition': '#SBATCH --partition=compute \n',
+        'memory': '#SBATCH --constraint=512G \n',
+    },
     'recipe_eady_growth_rate': {
         'partition': '#SBATCH --partition=compute \n',
     },
@@ -125,6 +133,7 @@
     },
     'recipe_ipccwg1ar6ch3_fig_3_43': {
         'partition': '#SBATCH --partition=compute \n',
+        'time': '#SBATCH --time=08:00:00 \n',
     },
     'recipe_lauer22jclim_fig3-4_zonal': {
         'partition': '#SBATCH --partition=compute \n',
@@ -137,6 +146,7 @@
     },
     'recipe_mpqb_xch4': {
         'partition': '#SBATCH --partition=compute \n',
+        'memory': '#SBATCH --constraint=512G \n',
     },
     'recipe_perfmetrics_CMIP5': {
         'partition': '#SBATCH --partition=compute \n',
@@ -164,6 +174,9 @@
     'recipe_schlund20jgr_gpp_change_rcp85': {
         'partition': '#SBATCH --partition=compute \n',
     },
+    'recipe_sea_surface_salinity': {
+        'partition': '#SBATCH --partition=compute \n',
+    },
     'recipe_smpi': {
         'partition': '#SBATCH --partition=compute \n',
     },
@@ -174,6 +187,9 @@
         'partition': '#SBATCH --partition=compute \n',
         'time': '#SBATCH --time=08:00:00 \n',
     },
+    'recipe_thermodyn_diagtool': {
+        'partition': '#SBATCH --partition=compute \n',
+    },
     'recipe_wenzel16jclim': {
         'partition': '#SBATCH --partition=compute \n',
     },
@@ -182,26 +198,28 @@
     },
 }
 
+# These recipes cannot be run with the default number of parallel
+# tasks (max_parallel_tasks=8).
 # These recipes either use CMIP3 input data
 # (see https://github.com/ESMValGroup/ESMValCore/issues/430)
-# and recipes where tasks require the full compute node memory.
-ONE_TASK_RECIPES = [
-    'recipe_bock20jgr_fig_1-4',
-    'recipe_bock20jgr_fig_6-7',
-    'recipe_bock20jgr_fig_8-10',
-    'recipe_flato13ipcc_figure_96',
-    'recipe_flato13ipcc_figures_938_941_cmip3',
-    'recipe_ipccwg1ar6ch3_fig_3_9',
-    'recipe_ipccwg1ar6ch3_fig_3_42_a',
-    'recipe_ipccwg1ar6ch3_fig_3_43',
-    'recipe_check_obs',
-    'recipe_collins13ipcc',
-    'recipe_lauer22jclim_fig3-4_zonal',
-    'recipe_lauer22jclim_fig5_lifrac',
-    'recipe_smpi',
-    'recipe_smpi_4cds',
-    'recipe_wenzel14jgr',
-    ]
+# or require a large fraction of the compute node memory.
+MAX_PARALLEL_TASKS = {
+    'recipe_bock20jgr_fig_1-4': 1,
+    'recipe_bock20jgr_fig_6-7': 1,
+    'recipe_bock20jgr_fig_8-10': 1,
+    'recipe_flato13ipcc_figure_96': 1,
+    'recipe_flato13ipcc_figures_938_941_cmip3': 1,
+    'recipe_ipccwg1ar6ch3_fig_3_9': 1,
+    'recipe_ipccwg1ar6ch3_fig_3_42_a': 1,
+    'recipe_ipccwg1ar6ch3_fig_3_43': 1,
+    'recipe_check_obs': 1,
+    'recipe_collins13ipcc': 1,
+    'recipe_lauer22jclim_fig3-4_zonal': 3,
+    'recipe_lauer22jclim_fig5_lifrac': 3,
+    'recipe_smpi': 1,
+    'recipe_smpi_4cds': 1,
+    'recipe_wenzel14jgr': 1,
+}
 
 
 def generate_submit():
@@ -272,9 +290,12 @@ def generate_submit():
             else:
                 file.write(f'esmvaltool run --config_file '
                            f'{str(config_file)} {str(recipe)}')
-            if recipe.stem in ONE_TASK_RECIPES:
-                file.write(' --max_parallel_tasks=1')
-
+            # set max_parallel_tasks
+            max_parallel_tasks = MAX_PARALLEL_TASKS.get(
+                recipe.stem,
+                default_max_parallel_tasks,
+            )
+            file.write(f' --max_parallel_tasks={max_parallel_tasks}\n')
         if submit:
             subprocess.check_call(['sbatch', filename])
 
diff --git a/esmvaltool/utils/batch-jobs/parse_recipes_output.py b/esmvaltool/utils/batch-jobs/parse_recipes_output.py
index a8436d3c31..9df80c6cc0 100644
--- a/esmvaltool/utils/batch-jobs/parse_recipes_output.py
+++ b/esmvaltool/utils/batch-jobs/parse_recipes_output.py
@@ -7,10 +7,8 @@
 a GitHub issue or any other such documentation.
 """
 import datetime
-import os
-
 import glob
-
+import os
 
 # User change needed
 # directory where SLURM output files (.out and .err) are
@@ -81,11 +79,13 @@ def display_in_md():
     todaynow = datetime.datetime.now()
     print(f"## Recipe running session {todaynow}\n")
     with open("all_recipes.txt", "r", encoding='utf-8') as allrecs:
-        all_recs = [rec.strip() for rec in allrecs.readlines()]
+        all_recs = [
+            os.path.basename(rec.strip()) for rec in allrecs.readlines()
+        ]
 
     # parse different types of recipe outcomes
     recipe_list, failed, missing_dat = parse_output_file()
-    print("### Succesfully run recipes\n\n")
+    print("### Successfully ran recipes\n\n")
     print(f"{len(recipe_list)} out of {len(all_recs)}\n")
     for rec in recipe_list:
         print("- " + rec)
diff --git a/esmvaltool/utils/draft_release_notes.py b/esmvaltool/utils/draft_release_notes.py
index d00e752455..7b1c5f61b1 100644
--- a/esmvaltool/utils/draft_release_notes.py
+++ b/esmvaltool/utils/draft_release_notes.py
@@ -41,23 +41,22 @@
 }
 
 PREVIOUS_RELEASE = {
-    'esmvalcore': datetime.datetime(2022, 10, 13, 18),
+    'esmvalcore': datetime.datetime(2023, 5, 19, 16),
     'esmvaltool': datetime.datetime(2022, 10, 28, 18),
 }
 
-
 LABELS = {
     'esmvalcore': (
+        'backwards incompatible change',  # important, keep at the top
+        'deprecated feature',  # important, keep at the top
+        'bug',  # important, keep at the top
         'api',
-        'backwards incompatible change',
-        'bug',
         'cmor',
         'containerization',
         'community',
+        'dask',
         'deployment',
-        'deprecated feature',
         'documentation',
-        'enhancement',
         'fix for dataset',
         'installation',
         'iris',
@@ -65,20 +64,21 @@
         'release',
         'testing',
         'UX',
-        'variable derivation'
+        'variable derivation',
+        'enhancement',  # uncategorized, keep at the bottom
     ),
     'esmvaltool': (
-        'backwards incompatible change',
-        'bug',
+        'backwards incompatible change',  # important, keep at the top
+        'deprecated feature',  # important, keep at the top
+        'bug',  # important, keep at the top
         'community',
-        'deprecated feature',
         'documentation',
         'diagnostic',
         'preprocessor',
         'observations',
         'testing',
         'installation',
-        'enhancement',
+        'enhancement',  # uncategorized, keep at the bottom
     )
 }
 
@@ -87,6 +87,7 @@
     'deprecated feature': 'Deprecations',
     'bug': 'Bug fixes',
     'cmor': 'CMOR standard',
+    'dask': 'Computational performance improvements',
     'diagnostic': 'Diagnostics',
     'fix for dataset': 'Fixes for datasets',
     'observations': 'Observational and re-analysis dataset support',
@@ -210,7 +211,8 @@ def _compose_note(pull):
 
 
 def main():
-    """Entry point for the scrip."""
+    """Entry point for the script."""
+
     def display(lines, out):
         text = "\n".join(lines) + "\n"
         out.write(text)
diff --git a/esmvaltool/utils/testing/regression/compare.py b/esmvaltool/utils/testing/regression/compare.py
index ca96b65a68..a4ee33c5d3 100644
--- a/esmvaltool/utils/testing/regression/compare.py
+++ b/esmvaltool/utils/testing/regression/compare.py
@@ -80,7 +80,7 @@ def diff_attrs(ref: dict, cur: dict) -> str:
             msg.append(f"missing attribute '{key}'")
         elif not np.array_equal(ref[key], cur[key]):
             msg.append(f"value of attribute '{key}' is different: "
-                       f"expected '{cur[key]}' but found '{ref[key]}'")
+                       f"expected '{ref[key]}' but found '{cur[key]}'")
     for key in cur:
         if key not in ref:
             msg.append(f"extra attribute '{key}' with value '{cur[key]}'")
@@ -96,12 +96,15 @@ def diff_array(ref: np.ndarray, cur: np.ndarray) -> str:
     msg = []
     if cur.shape != ref.shape:
         msg.append("data has different shape")
+    elif np.issubdtype(ref.dtype, np.inexact) and np.issubdtype(
+            cur.dtype, np.inexact):
+        if not np.array_equal(ref, cur, equal_nan=True):
+            if np.allclose(ref, cur, equal_nan=True):
+                msg.append("data is almost but not quite the same")
+            else:
+                msg.append("data is different")
     elif not np.array_equal(ref, cur):
-        if np.issubdtype(ref.dtype, np.inexact) and np.issubdtype(
-                cur.dtype, np.inexact) and np.allclose(ref, cur):
-            msg.append("data is almost but not quite the same")
-        else:
-            msg.append("data is different")
+        msg.append("data is different")
     return as_txt(msg)
 
 

From 98ea207d11614878ea400ad1c93ae0f6c3db2529 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Wed, 1 Nov 2023 12:30:06 +0000
Subject: [PATCH 57/93] [Condalock] Update Linux condalock file (#3401)

Co-authored-by: valeriupredoi <valeriupredoi@users.noreply.github.com>
---
 conda-linux-64.lock | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/conda-linux-64.lock b/conda-linux-64.lock
index c5310d91b3..3873ea2feb 100644
--- a/conda-linux-64.lock
+++ b/conda-linux-64.lock
@@ -76,7 +76,7 @@ https://conda.anaconda.org/conda-forge/linux-64/make-4.3-hd18ef5c_1.tar.bz2#4049
 https://conda.anaconda.org/conda-forge/linux-64/mbedtls-3.3.0-hcb278e6_0.conda#cc1213f464c357b647cc5dde5cfca881
 https://conda.anaconda.org/conda-forge/linux-64/metis-5.1.0-h59595ed_1007.conda#40ccb8318df2500f83bd868dd8fcd201
 https://conda.anaconda.org/conda-forge/linux-64/nccl-2.19.3.1-h6103f9b_0.conda#5b4426d8e0534cd844924728d2137666
-https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.4-hcb278e6_0.conda#681105bccc2a3f7f1a837d47d39c9179
+https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.4-h59595ed_2.conda#7dbaa197d7ba6032caf7ae7f32c1efa0
 https://conda.anaconda.org/conda-forge/linux-64/nspr-4.35-h27087fc_0.conda#da0ec11a6454ae19bff5b02ed881a2b1
 https://conda.anaconda.org/conda-forge/linux-64/openlibm-0.8.1-h7f98852_0.tar.bz2#ba0c56761f2380babaa783b2a37b4d08
 https://conda.anaconda.org/conda-forge/linux-64/openssl-3.1.4-hd590300_0.conda#412ba6938c3e2abaca8b1129ea82e238
@@ -436,7 +436,7 @@ https://conda.anaconda.org/conda-forge/linux-64/pandas-2.1.2-py311h320fe9a_0.con
 https://conda.anaconda.org/conda-forge/linux-64/pango-1.50.14-heaa33ce_1.conda#cde553e0e32389e26595db4eacf859eb
 https://conda.anaconda.org/conda-forge/noarch/pooch-1.8.0-pyhd8ed1ab_0.conda#134b2b57b7865d2316a7cce1915a51ed
 https://conda.anaconda.org/conda-forge/noarch/pylint-2.17.7-pyhd8ed1ab_0.conda#3cab6aee60038b3f621bce3e50f52bed
-https://conda.anaconda.org/conda-forge/noarch/pyopenssl-23.2.0-pyhd8ed1ab_1.conda#34f7d568bf59d18e3fef8c405cbece21
+https://conda.anaconda.org/conda-forge/noarch/pyopenssl-23.3.0-pyhd8ed1ab_0.conda#7819533e674dbbc51468f3228b9b1bb6
 https://conda.anaconda.org/conda-forge/noarch/pyroma-4.2-pyhd8ed1ab_0.conda#fe2aca9a5d4cb08105aefc451ef96950
 https://conda.anaconda.org/conda-forge/noarch/pytest-html-3.2.0-pyhd8ed1ab_1.tar.bz2#d5c7a941dfbceaab4b172a56d7918eb0
 https://conda.anaconda.org/conda-forge/linux-64/pywavelets-1.4.1-py311h1f0f07a_1.conda#86b71ff85f3e4c8a98b5bace6d9c4565

From 2fe223cd85953b03456c8c636ade20993920edc9 Mon Sep 17 00:00:00 2001
From: Alejandro Bodas <97702998+mo-abodas@users.noreply.github.com>
Date: Thu, 2 Nov 2023 09:42:25 +0000
Subject: [PATCH 58/93] Implied heat transport new diagnostic (#3177)

Co-authored-by: Francesca Pearce <francesca.pearce@metoffice.gov.uk>
Co-authored-by: alejandrobodas <alejandroxtr@gmail.com>
Co-authored-by: Emma Hogan <ehogan@users.noreply.github.com>
---
 .zenodo.json                                  | 797 +++++++-------
 CITATION.cff                                  |   5 +
 .../iht_toa/figure1_CERES-EBAF_CERES-EBAF.png | Bin 0 -> 49134 bytes
 .../iht_toa/figure2_CERES-EBAF_CERES-EBAF.png | Bin 0 -> 463548 bytes
 .../iht_toa/figure3_CERES-EBAF_CERES-EBAF.png | Bin 0 -> 83470 bytes
 .../iht_toa/figure4_CERES-EBAF_CERES-EBAF.png | Bin 0 -> 513405 bytes
 .../iht_toa/figure5_CERES-EBAF_CERES-EBAF.png | Bin 0 -> 324689 bytes
 .../iht_toa/figure6_CERES-EBAF_CERES-EBAF.png | Bin 0 -> 87707 bytes
 doc/sphinx/source/recipes/index.rst           |   1 +
 doc/sphinx/source/recipes/recipe_iht_toa.rst  | 123 +++
 environment.yml                               |   1 +
 esmvaltool/config-references.yml              |   8 +
 .../diag_scripts/iht_toa/poisson_solver.py    | 293 ++++++
 .../iht_toa/single_model_diagnostics.py       | 993 ++++++++++++++++++
 esmvaltool/recipes/recipe_iht_toa.yml         | 119 +++
 esmvaltool/references/pearce23jclim.bibtex    |  13 +
 setup.py                                      |   1 +
 17 files changed, 1947 insertions(+), 407 deletions(-)
 create mode 100644 doc/sphinx/source/recipes/figures/iht_toa/figure1_CERES-EBAF_CERES-EBAF.png
 create mode 100644 doc/sphinx/source/recipes/figures/iht_toa/figure2_CERES-EBAF_CERES-EBAF.png
 create mode 100644 doc/sphinx/source/recipes/figures/iht_toa/figure3_CERES-EBAF_CERES-EBAF.png
 create mode 100644 doc/sphinx/source/recipes/figures/iht_toa/figure4_CERES-EBAF_CERES-EBAF.png
 create mode 100644 doc/sphinx/source/recipes/figures/iht_toa/figure5_CERES-EBAF_CERES-EBAF.png
 create mode 100644 doc/sphinx/source/recipes/figures/iht_toa/figure6_CERES-EBAF_CERES-EBAF.png
 create mode 100644 doc/sphinx/source/recipes/recipe_iht_toa.rst
 create mode 100644 esmvaltool/diag_scripts/iht_toa/poisson_solver.py
 create mode 100644 esmvaltool/diag_scripts/iht_toa/single_model_diagnostics.py
 create mode 100644 esmvaltool/recipes/recipe_iht_toa.yml
 create mode 100644 esmvaltool/references/pearce23jclim.bibtex

diff --git a/.zenodo.json b/.zenodo.json
index 43d9d2638a..11e2188ba9 100644
--- a/.zenodo.json
+++ b/.zenodo.json
@@ -1,409 +1,392 @@
 {
-    "creators": [
-        {
-            "affiliation": "NLeSC, Netherlands",
-            "name": "Andela, Bouwe",
-            "orcid": "0000-0001-9005-8940"
-        },
-        {
-            "affiliation": "DLR, Germany",
-            "name": "Broetz, Bjoern"
-        },
-        {
-            "affiliation": "PML, UK",
-            "name": "de Mora, Lee",
-            "orcid": "0000-0002-5080-3149"
-        },
-        {
-            "affiliation": "NLeSC, Netherlands",
-            "name": "Drost, Niels",
-            "orcid": "0000-0001-9795-7981"
-        },
-        {
-            "affiliation": "DLR, Germany",
-            "name": "Eyring, Veronika",
-            "orcid": "0000-0002-6887-4885"
-        },
-        {
-            "affiliation": "AWI, Germany",
-            "name": "Koldunov, Nikolay",
-            "orcid": "0000-0002-3365-8146"
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+    {
+      "affiliation": "ACCESS-NRI, Australia",
+      "name": "Beucher, Romain",
+      "orcid": "0000-0003-3891-5444"
+    },
+    {
+      "affiliation": "DLR, Germany",
+      "name": "Kraft, Jeremy"
+    },
+    {
+      "affiliation": "University of Bremen, Germany",
+      "name": "Ruhe, Lukas",
+      "orcid": "0000-0001-6349-9118"
+    },
+    {
+      "affiliation": "DLR, Germany",
+      "name": "Bonnet, Pauline",
+      "orcid": "0000-0003-3780-0784"
+    }
+  ],
+  "description": "ESMValTool: A community diagnostic and performance metrics tool for routine evaluation of Earth system models in CMIP.",
+  "license": {
+    "id": "Apache-2.0"
+  },
+  "publication_date": "2023-07-06",
+  "title": "ESMValTool",
+  "version": "v2.9.0"
 }
diff --git a/CITATION.cff b/CITATION.cff
index b6f6d45f77..147e3acd17 100644
--- a/CITATION.cff
+++ b/CITATION.cff
@@ -90,6 +90,11 @@ authors:
     family-names: Bock
     given-names: Lisa
     orcid: "https://orcid.org/0000-0001-7058-5938"
+  -
+    affiliation: "MetOffice, UK"
+    family-names: Bodas-Salcedo
+    given-names: Alejandro
+    orcid: "https://orcid.org/0000-0002-7890-2536"
   -
     affiliation: "BSC, Spain"
     family-names: Caron
diff --git a/doc/sphinx/source/recipes/figures/iht_toa/figure1_CERES-EBAF_CERES-EBAF.png b/doc/sphinx/source/recipes/figures/iht_toa/figure1_CERES-EBAF_CERES-EBAF.png
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diff --git a/doc/sphinx/source/recipes/index.rst b/doc/sphinx/source/recipes/index.rst
index 1cb182f39b..c8e6b4a320 100644
--- a/doc/sphinx/source/recipes/index.rst
+++ b/doc/sphinx/source/recipes/index.rst
@@ -45,6 +45,7 @@ Atmosphere
    recipe_gier20bg
    recipe_heatwaves_coldwaves
    recipe_hyint
+   recipe_iht_toa
    recipe_impact
    recipe_modes_of_variability
    recipe_mpqb_xch4
diff --git a/doc/sphinx/source/recipes/recipe_iht_toa.rst b/doc/sphinx/source/recipes/recipe_iht_toa.rst
new file mode 100644
index 0000000000..87e182ef6a
--- /dev/null
+++ b/doc/sphinx/source/recipes/recipe_iht_toa.rst
@@ -0,0 +1,123 @@
+.. _recipes_iht_toa:
+
+Implied heat transport from Top of Atmosphere fluxes
+====================================================
+
+Overview
+--------
+
+This recipe calculates the implied horizontal heat transport (IHT) due to the
+spatial anomalies of radiative fluxes at the top of the atmosphere (TOA).
+The regional patterns of implied heat transport for different components of
+the TOA fluxes are calculated by solving the Poisson equation with the flux
+components as source terms.
+It reproduces the plots in `Pearce and Bodas-Salcedo (2023)`_ when the input
+data is CERES EBAF.
+
+
+Available recipes and diagnostics
+---------------------------------
+
+Recipes are stored in esmvaltool/recipes/
+
+* recipe_iht_toa.yml calculates the IHT maps for the following radiative fluxes:
+
+  * Total net, SW net, LW net (Figure 2).
+  * Total CRE, SW CRE, LW CRE (Figure 4).
+  * All-sky and clear-sky reflected SW (Figure 5).
+  * The meridional heat transports (MHT) of the fluxes above (Figures 1 and 3).
+
+Diagnostics are stored in esmvaltool/diag_scripts/iht_toa/
+
+* single_model_diagnostics.py: driver script that produces the plots.
+* poisson_solver.py: solver that calculates the IHTs.
+
+.. _`Pearce and Bodas-Salcedo (2023)`:  https://doi.org/10.1175/JCLI-D-22-0149.1
+
+User settings in recipe
+-----------------------
+There are no user settings in this recipe.
+
+Variables
+---------
+
+* rlut (atmos, monthly, longitude latitude time)
+* rlutcs (atmos, monthly, longitude latitude time)
+* rsutcs (atmos, monthly, longitude latitude time)
+* rsut (atmos, monthly, longitude latitude time)
+* rsdt (atmos, monthly, longitude latitude time)
+
+Observations and reformat scripts
+---------------------------------
+
+* CERES-EBAF
+
+References
+----------
+
+* Pearce, F. A., and A. Bodas-Salcedo, 2023: Implied Heat Transport from CERES
+  Data: Direct Radiative Effect of Clouds on Regional Patterns and Hemispheric
+  Symmetry. J. Climate, 36, 4019–4030, doi: 10.1175/JCLI-D-22-0149.1.
+
+Example plots
+-------------
+
+.. _fig_iht_toa_1:
+.. figure::  /recipes/figures/iht_toa/figure1_CERES-EBAF_CERES-EBAF.png
+   :align:   center
+
+   The implied heat transport due to the total net flux (blue), split into
+   the contributions from the SW (orange) and LW (green).
+
+.. _fig_iht_toa_2:
+.. figure::  /recipes/figures/iht_toa/figure2_CERES-EBAF_CERES-EBAF.png
+   :align:   center
+
+   The energy flux potentials for (a) TOT, (c) SW, and (e) LW fluxes,
+   alongside maps of the spatial anomalies of the fluxes [(b),(d),(f)
+   flux minus global average flux, respectively].
+   The implied heat transport is calculated as the gradient of the energy
+   flux potential, shown by the white vector arrows for a subset of points
+   to give the overall transport pattern.
+   Heat is directed from the blue minima of the potential field to
+   yellow maxima, with the magnitude implied by the density of contours.
+   All maps of the same type share the same color bar at the bottom
+   of the column.
+
+.. _fig_iht_toa_3:
+.. figure::  /recipes/figures/iht_toa/figure3_CERES-EBAF_CERES-EBAF.png
+   :align:   center
+
+   Direct radiative effects of clouds on the meridional heat transport.
+   (a) Contributions from TOT CRE (blue), SW CRE (orange), and LW CRE (green)
+   fluxes. (b) Contributions from all-sky and clear-sky OSR.
+   In (b), both curves have been multiplied by −1 such that positive heat
+   transport is northward.
+
+.. _fig_iht_toa_4:
+.. figure::  /recipes/figures/iht_toa/figure4_CERES-EBAF_CERES-EBAF.png
+   :align:   center
+
+   As in :numref:`fig_iht_toa_2`, but for the implied heat transport associated with
+   (a),(b) TOT CRE, (c),(d) SW CRE, and (e),(f) LW CRE fluxes.
+
+.. _fig_iht_toa_5:
+.. figure::  /recipes/figures/iht_toa/figure5_CERES-EBAF_CERES-EBAF.png
+   :align:   center
+
+   As in :numref:`fig_iht_toa_2`, but for (a), (b) clear-sky and (c), (d) all-sky reflected
+   SW flux.
+
+.. _fig_iht_toa_6:
+.. figure::  /recipes/figures/iht_toa/figure6_CERES-EBAF_CERES-EBAF.png
+   :align:   center
+
+   A measure of the symmetry between heat transport in the Northern and
+   Southern Hemispheres, calculated for the 12-month running mean of TOT MHT
+   in the regions: (a) the full hemisphere, (b) from the equator to 30°, and
+   (c) 30° to 90°.
+   Symmetry values obtained when including (blue) and excluding (orange)
+   the effect of clouds. The climatological symmetry values for the two cases
+   are shown as the black lines in each subplot, dashed and dotted,
+   respectively.
+   The standard deviations of the time series are shown in each plot.
diff --git a/environment.yml b/environment.yml
index 33a556b7d9..f60db24659 100644
--- a/environment.yml
+++ b/environment.yml
@@ -38,6 +38,7 @@ dependencies:
   - natsort
   - nc-time-axis
   - netCDF4
+  - numba
   - numpy !=1.24.3  # severe masking bug
   - packaging
   - openpyxl
diff --git a/esmvaltool/config-references.yml b/esmvaltool/config-references.yml
index cea1a0561b..16725c3764 100644
--- a/esmvaltool/config-references.yml
+++ b/esmvaltool/config-references.yml
@@ -120,6 +120,10 @@ authors:
     institute: DLR, Germany
     orcid: https://orcid.org/0000-0001-7058-5938
     github: LisaBock
+  bodas-salcedo_alejandro:
+    name: Bodas-Salcedo, Alejandro
+    institute: MetOffice, UK
+    orcid:
   bojovic_dragana:
     name: Bojovic, Dragana
     institute: BSC, Spain
@@ -411,6 +415,10 @@ authors:
     name: Pandde, Amarjiit
     institute: Univ. of Arizona, USA
     orcid:
+  pearce_francesca:
+    name: Pearce, Francesca
+    institute: MetOffice, UK
+    orcid:
   perez-zanon_nuria:
     name: Perez-Zanon, Nuria
     institute: BSC, Spain
diff --git a/esmvaltool/diag_scripts/iht_toa/poisson_solver.py b/esmvaltool/diag_scripts/iht_toa/poisson_solver.py
new file mode 100644
index 0000000000..886d5fc616
--- /dev/null
+++ b/esmvaltool/diag_scripts/iht_toa/poisson_solver.py
@@ -0,0 +1,293 @@
+# (C) Crown Copyright 2023, the Met Office.
+"""Poisson solver for the full ocean-atmosphere column.
+
+The Poisson equation is solved by numerically using the bi-conjugate
+gradient stabilized (BiCGSTAB) method.
+
+The solution is achieved when the difference between the input field (radiative
+flux) and the Laplacian of the output field is less than the stated tolerance.
+If the solver fails to converge, the tolerance can be increased.
+
+Convergence is achieved faster by using a preconditioner on the output field.
+
+The heat transport is calculated as the gradient of the energy flux potential,
+the output of the Poisson solver.
+"""
+
+import numpy as np
+from numba import jit
+
+
+def swap_bounds(array):
+    """Extend the array by one in all directions.
+
+    As the array is periodic it allows for easier computations at
+    boundaries.
+    """
+    shape0, shape1 = np.array(array.shape) - 2
+    wrap_point = int(shape1 / 2 + 1)
+    for i in range(1, shape1 + 1):
+        array[0, i] = array[1, wrap_point]
+        array[shape0 + 1, i] = array[shape0, wrap_point]
+        wrap_point += 1
+        if wrap_point > shape1:
+            wrap_point = 1
+
+    array[:, 0] = array[:, shape1]
+    array[:, shape1 + 1] = array[:, 1]
+
+    return array
+
+
+def dot_prod(a_matrix, b_matrix):
+    """Calculate dot product of two matrices only over source term size."""
+    shape0, shape1 = np.array(a_matrix.shape) - 2
+    return (a_matrix[1:shape0 + 1, 1:shape1 + 1] *
+            b_matrix[1:shape0 + 1, 1:shape1 + 1]).sum()
+
+
+def precon(x_matrix, m_matrix):
+    """Preconditioner.
+
+    This is a wrapper to two steps that are optimised using jit.
+    It implements the preconditioning step of van der Vorst, H. A., 1992.
+    https://doi.org/10.1137/0913035.
+    """
+    cx_matrix = np.zeros(np.array(x_matrix.shape))
+    precon_a(x_matrix, m_matrix[1], m_matrix[2], m_matrix[4], cx_matrix)
+    cx_matrix = swap_bounds(cx_matrix)
+    precon_b(m_matrix[0], m_matrix[3], cx_matrix)
+    cx_matrix = swap_bounds(cx_matrix)
+    return cx_matrix
+
+
+@jit(nopython=True)
+def precon_a(x_matrix, m_w, m_s, m_p, cx_matrix):
+    """First step of preconditioner."""
+    shape0, shape1 = np.array(cx_matrix.shape) - 2
+    for j in range(1, shape0 + 1):
+        for i in range(1, shape1 + 1):
+            cx_matrix[j, i] = m_p[j, i] * (x_matrix[j, i] -
+                                           m_s[j, i] * cx_matrix[j - 1, i] -
+                                           m_w[j, i] * cx_matrix[j, i - 1])
+
+
+@jit(nopython=True)
+def precon_b(m_e, m_n, cx_matrix):
+    """Second step of preconditioner."""
+    shape0, shape1 = np.array(cx_matrix.shape) - 2
+    for j in range(shape0, 0, -1):
+        for i in range(shape1, 0, -1):
+            cx_matrix[j, i] = (cx_matrix[j, i] -
+                               m_e[j, i] * cx_matrix[j, i + 1] -
+                               m_n[j, i] * cx_matrix[j + 1, i])
+
+
+class SphericalPoisson:
+    """Poisson solver over the sphere.
+
+    Solve Poisson equation for a given source term (forcing) and
+    calculate meridional heat transport (MHT).
+    """
+
+    def __init__(self, logger, source, tolerance=2.0e-4):
+        """Initialise solver with source field, metrics and matrices."""
+        self.logger = logger
+        self.source = source
+        self.tolerance = tolerance
+        self.energy_flux_potential = None
+        self.meridional_heat_transport = None
+        logger.info("Initialising Poisson solver.")
+        self.set_matrices()
+
+    def set_matrices(self):
+        """Calculate A and M matrices.
+
+        A is the matrix that defines the five-point stencil (Eq. 8). The
+        A_matrix are the values are the contributions from each of the
+        four neighbouring cells: e,w,s,n,p.
+        """
+        # Calculate metrics hpi and hvj
+        src_shape = np.array(self.source.shape)
+        hpi = np.zeros(src_shape[0])
+        hvj = np.zeros(src_shape[0] + 1)
+        deltay = np.pi / src_shape[0]
+        yyy = -0.5 * np.pi + 0.5 * deltay
+        hvj[0] = 0.0
+        for j in range(0, src_shape[0]):
+            hpi[j] = np.cos(yyy)
+            hvj[j + 1] = np.cos(yyy + 0.5 * deltay)
+            yyy += deltay
+        hvj[-1] = 0.0
+
+        # Storing the full matrix
+        a_matrix = np.zeros((5, *src_shape))
+
+        # ILU factors
+        m_matrix = np.zeros((5, *(src_shape + 1)))
+
+        # Spherical Laplacian variables
+        aaa = 1.0 / ((2.0 * np.pi / src_shape[1])**2.)
+        bbb = 1.0 / ((np.pi / src_shape[0])**2.)
+
+        # First calculate the Poisson equations 5-point stencil
+        # A_w is the contribution from i-1, A_e is from i+1,
+        # A_s is j-1, A_n is j+1, and A_p is the diagonal
+        for j in range(0, src_shape[0]):
+            txa = aaa / hpi[j]**2.0
+            tyb = bbb / hpi[j]
+
+            for i in range(0, src_shape[1]):
+                a_matrix[0, j, i] = txa
+                a_matrix[1, j, i] = txa
+                a_matrix[2, j, i] = tyb * hvj[j]
+                a_matrix[3, j, i] = tyb * hvj[j + 1]
+                a_matrix[4, j, i] = -a_matrix[0:4, j, i].sum()
+
+        # ILU/SIP preconditioner factors: alf = 0.0 is ILU
+        alf = 0.9
+        m_matrix[4] += 1.0
+
+        for j in range(1, src_shape[0] + 1):
+            for i in range(1, src_shape[1] + 1):
+                m_matrix[2, j, i] = (a_matrix[2, j - 1, i - 1] /
+                                     (1.0 + alf * m_matrix[0, j - 1, i]))
+
+                m_matrix[1, j, i] = (a_matrix[1, j - 1, i - 1] /
+                                     (1.0 + alf * m_matrix[3, j, i - 1]))
+
+                m_matrix[4, j, i] = (a_matrix[4, j - 1, i - 1] -
+                                     m_matrix[2, j, i] *
+                                     (m_matrix[3, j - 1, i] -
+                                     alf * m_matrix[0, j - 1, i]) -
+                                     m_matrix[1, j, i] *
+                                     (m_matrix[0, j, i - 1] -
+                                     alf * m_matrix[3, j, i - 1]))
+
+                m_matrix[4, j, i] = 1.0 / m_matrix[4, j, i]
+
+                m_matrix[0, j, i] = ((a_matrix[0, j - 1, i - 1] -
+                                     alf * m_matrix[2, j, i] *
+                                     m_matrix[0, j - 1, i]) *
+                                     m_matrix[4, j, i])
+
+                m_matrix[3, j, i] = ((a_matrix[3, j - 1, i - 1] -
+                                     alf * m_matrix[1, j, i] *
+                                     m_matrix[3, j, i - 1]) *
+                                     m_matrix[4, j, i])
+
+        self.a_matrix = a_matrix
+        self.m_matrix = m_matrix
+
+    def solve(self, max_iterations=1000):
+        """Solve equation for the source term.
+
+        Bi-conjugate gradient stabilized numerical solver: van der
+        Vorst, H. A., 1992: Bi-cgstab: A fast and smoothly converging
+        variant of bi-cg for the solution of nonsymmetric linear
+        systems. SIAM Journal on Scientific and Statistical Computing,
+        https://doi.org/10.1137/0913035.
+        This solver implements the preconditioned Bi-CGSTAB algorithm,
+        described in page 638 of that paper.
+        """
+        bbb = np.zeros(np.array(self.source.shape) + 2)
+        xxx = np.zeros(np.array(self.source.shape) + 2)
+        bbb[1:-1, 1:-1] = self.source
+        bbb = swap_bounds(bbb)
+
+        sc_err = dot_prod(bbb, bbb)
+
+        # Group some temporal variables
+        stv = {
+            'alf': 1.0,
+            'omg': 1.0,
+            'nrm': 1.0,
+            'rrr': bbb - self.calc_ax(xxx)
+        }
+        stv['crrr'] = stv['rrr'].copy()
+
+        ppp = np.zeros(np.array(self.source.shape) + 2)
+        vvv = np.zeros(np.array(self.source.shape) + 2)
+
+        iteration = 0
+        while iteration < max_iterations:
+            rho = dot_prod(stv['rrr'], stv['crrr'])
+
+            bet = (rho / stv['nrm']) * (stv['alf'] / stv['omg'])
+
+            ttt = stv['rrr'] - bet * stv['omg'] * vvv
+
+            sss = precon(ttt, self.m_matrix)
+            ppp = sss + bet * ppp
+
+            vvv = self.calc_ax(ppp)
+            stv['nrm'] = dot_prod(stv['crrr'], vvv)
+
+            stv['alf'] = rho / stv['nrm']
+            sss = stv['rrr'] - stv['alf'] * vvv
+
+            csss = precon(sss, self.m_matrix)
+            ttt = self.calc_ax(csss)
+
+            stv['omg'] = dot_prod(ttt, sss) / dot_prod(ttt, ttt)
+
+            xxx = xxx + stv['alf'] * ppp + stv['omg'] * csss
+            stv['rrr'] = sss - stv['omg'] * ttt
+
+            stv['nrm'] = rho
+
+            if abs(stv['omg']) < 1.0e-16:
+                self.logger.info('Terminating Poisson solver.')
+                break
+
+            err = np.sqrt(dot_prod(stv['rrr'], stv['rrr']) / sc_err)
+            if err < self.tolerance:
+                self.logger.info('Poisson solver has converged.')
+                break
+
+            iteration += 1
+
+            if iteration == max_iterations:
+                raise RuntimeError('Poisson solver has not converged.')
+
+        self.energy_flux_potential = xxx
+
+    def calc_meridional_heat_transport(self):
+        """Meridional heat transport of energy flux potential.
+
+        Calculate of the meridional heat transport using the gradient of
+        the energy flux potential. Equation (11) in Pearce and Bodas-
+        Salcedo (2023).
+        """
+        deltax = 2.0 * np.pi / self.source.shape[1]
+        deltay = np.pi / self.source.shape[0]
+        yvalues = np.arange(-0.5 * np.pi + 0.5 * deltay, 0.5 * np.pi, deltay)
+        grad_phi = np.gradient(self.energy_flux_potential, deltay, axis=0)
+        grad_phi = grad_phi[1:-1, 1:-1]
+        self.meridional_heat_transport = np.sum((grad_phi.T *
+                                                 np.cos(yvalues) *
+                                                 deltax).T, axis=1)
+
+    def calc_ax(self, x_matrix):
+        """Matrix calculation of the Laplacian equation, LHS of Eq.
+
+        (9) in Pearce and Bodas-Salcedo (2023).
+        """
+        # Laplacian equation
+        src_shape = np.array(self.source.shape)
+        ax_matrix = np.zeros(src_shape + 2)
+        x_matrix = swap_bounds(x_matrix)
+        shape0, shape1 = src_shape
+        ax_matrix[1:shape0 + 1, 1:shape1 + 1] = (
+            self.a_matrix[2, 0:shape0, 0:shape1] *
+            x_matrix[0:shape0, 1:shape1 + 1] +
+            self.a_matrix[1, 0:shape0, 0:shape1] *
+            x_matrix[1:shape0 + 1, 0:shape1] +
+            self.a_matrix[0, 0:shape0, 0:shape1] *
+            x_matrix[1:shape0 + 1, 2:shape1 + 2] +
+            self.a_matrix[3, 0:shape0, 0:shape1] *
+            x_matrix[2:shape0 + 2, 1:shape1 + 1] +
+            self.a_matrix[4, 0:shape0, 0:shape1] *
+            x_matrix[1:shape0 + 1, 1:shape1 + 1])
+        ax_matrix = swap_bounds(ax_matrix)
+        return ax_matrix
diff --git a/esmvaltool/diag_scripts/iht_toa/single_model_diagnostics.py b/esmvaltool/diag_scripts/iht_toa/single_model_diagnostics.py
new file mode 100644
index 0000000000..fc917a8aa5
--- /dev/null
+++ b/esmvaltool/diag_scripts/iht_toa/single_model_diagnostics.py
@@ -0,0 +1,993 @@
+# (C) Crown Copyright 2023, the Met Office.
+"""Single model diagnostics.
+
+Apply Poisson solver to input fluxes and produce plots.
+"""
+
+import datetime
+import logging
+from copy import deepcopy
+
+import cartopy.crs as ccrs
+import iris
+import iris.plot as iplt
+import matplotlib.dates as mdates
+import matplotlib.pyplot as plt
+import numpy as np
+from iris import NameConstraint
+from matplotlib import gridspec, rcParams
+from poisson_solver import SphericalPoisson
+
+from esmvaltool.diag_scripts.shared import (
+    group_metadata,
+    run_diagnostic,
+    save_figure,
+)
+
+# Initialise logger
+logger = logging.getLogger(__name__)
+
+rcParams.update({
+    'font.size': 14,
+    'xtick.major.pad': 10,
+    'ytick.major.pad': 10,
+    'xtick.major.size': 10,
+    'ytick.major.size': 10,
+    'xtick.minor.size': 5,
+    'ytick.minor.size': 5,
+    'axes.linewidth': 2,
+    'lines.markersize': 8,
+    'lines.linewidth': 2
+})
+
+# Figure captions
+caption = {
+    'F1': 'Figure 1. The implied heat transport due to TOA net flux (blue), '
+          'split into the contributions from SW (orange) and LW (green).',
+    'F2': 'Figure 2. The TOA energy flux potentials for (a) TOT, (c) '
+          'SW, and (e) LW net fluxes, alongside maps of the spatial anomalies '
+          'of the input fluxes [(b),(d),(f)]. The implied heat transport is '
+          'the gradient of the energy flus potential, shown by the white '
+          'vector arrows (with the same magnitude scale across all subplots). '
+          'Heat is directed from the blue minima of the potential field to '
+          'yellow maxima, with the magnitude implied by the density of '
+          'contours. All maps of the same type share the same color bar at '
+          'the bottom of the column so that it is possible to directly '
+          'compare the results from different fluxes.',
+    'F3': 'Figure 3. Direct radiative effects of clouds on the meridional '
+          'heat transport. (a) Contributions from TOT CRE (blue), SW CRE '
+          '(orange), and LW CRE (green). (b) Contributions from all-sky and '
+          'clear-sky OSR. Both curves have been multiplied by -1 such that '
+          'positive heat transport is northward.',
+    'F4': 'Figure 4. As in Figure 2, but for cloud radiative effects.',
+    'F5': 'Figure 5. As in Figure 2, but for energy flux potentials and '
+          'spatial radiative anomalies associated with all-sky and clear-sky '
+          'outgoing shortwave radiation. ',
+    'F6': 'Figure 6. A measure of the symmetry between heat transport in the '
+          'Northern and Southern Hemispheres, calculated for the 12-month '
+          'running mean of MHT in (a) the full hemisphere, (b) from the '
+          'equator to 30 deg latitude, and (c) between 30 and 90 deg '
+          'latitude. Symmetry values obtained when including (blue) and '
+          'excluding (orange) the effect of clouds are shown. The '
+          'climatological symmetry values for the two cases are shown as '
+          'black lines in each subplot. The standard deviations of the '
+          'time series are shown in each subplot.',
+}
+
+
+def get_provenance_record(filenames, figure_caption):
+    """Return a provenance record describing the plot.
+
+    Parameters
+    ----------
+    filenames : list of strings
+        The filenames containing the data used to create the plot.
+    figure_caption : string
+        Detailed description of the figure.
+
+    Returns
+    -------
+    dictionary
+        The provenance record describing the plot.
+    """
+    record = {
+        'ancestors': filenames,
+        'caption': figure_caption,
+        'references': ['pearce23jclim']
+    }
+    return record
+
+
+def matching_strings(list_of_strings, substrings):
+    """Return subset of ``list_of_strings`` with matches in ``substrings``.
+
+    Parameters
+    ----------
+    list_of_strings : list of strings
+        List of strings to be searched.
+    substrings : list of strings
+        The list of search strings.
+
+    Returns
+    -------
+    list
+        The elements in ``list_of_strings`` that contain
+        any of the substrings.
+    """
+    matches = []
+    for element in list_of_strings:
+        for var in substrings:
+            if var in element:
+                matches.append(element)
+    return matches
+
+
+def area_average(cube, latitude='latitude', longitude='longitude', mdtol=1):
+    """Return area-weighted average of a cube.
+
+    Parameters
+    ----------
+    cube : :class:`iris.cube.Cube`
+        Input cube.
+    latitude : string
+        Name of latitude coordinate in ``cube``.
+    longitude : string
+        Name of longitude coordinate in ``cube``.
+    mdtol : float
+        Tolerance to missing data, between 0 and 1.
+
+
+    Returns
+    -------
+    :class:`iris.cube.Cube`
+        Collapsed cube with the weighted average.
+    """
+    if cube.coord(latitude).bounds is None:
+        cube.coord(latitude).guess_bounds()
+    if cube.coord(longitude).bounds is None:
+        cube.coord(longitude).guess_bounds()
+    grid_areas = iris.analysis.cartography.area_weights(cube)
+    cube_avg = cube.collapsed([longitude, latitude],
+                              iris.analysis.MEAN,
+                              weights=grid_areas,
+                              mdtol=mdtol)
+    return cube_avg
+
+
+def weight_zm(cube, latitude=None):
+    """Weight zonal-mean by normalised gridbox areas.
+
+    Parameters
+    ----------
+    cube : :class:`iris.cube.Cube`
+        Input cube.
+    latitude : tuple
+        Four-element tuple defining the latitude range.
+        The last two elements must be False, e.g.
+        latitude=(-90, 0, False, False).
+
+    Returns
+    -------
+    :class:`numpy.array`
+        Zonal-mean in the selected latitude range, weighted
+        by the normalised areas.
+    """
+    if cube.coord('latitude').bounds is None:
+        cube.coord('latitude').guess_bounds()
+    areas_data = iris.analysis.cartography.area_weights(cube, normalize=True)
+    cube_areas = iris.cube.Cube(areas_data,
+                                long_name="normalised_area",
+                                var_name="area", units="1",
+                                dim_coords_and_dims=[(cube.coords()[0], 0)])
+    if latitude is not None:
+        cube = cube.intersection(latitude=latitude)
+        cube_areas = cube_areas.intersection(latitude=latitude)
+    return cube.data * cube_areas.data
+
+
+def call_poisson(flux_cube, latitude='latitude', longitude='longitude'):
+    """Call the Poisson solver with the data in ``flux_cube`` as source term.
+
+       Return the energy flux potential and implied meridional heat transport
+       as cubes.
+
+    Parameters
+    ----------
+    flux_cube : :class:`iris.cube.Cube`
+        Input cube.
+    latitude : string
+        Name of latitude coordinate in ``cube``.
+    longitude : string
+        Name of longitude coordinate in ``cube``.
+
+    Returns
+    -------
+    efp_cube: :class:`iris.cube.Cube`
+        Energy flux potential cube.
+    mht_cube: :class:`iris.cube.Cube`
+        Implied meridional heat transport associated
+        with the source flux field.
+    """
+    earth_radius = 6371e3  # Earth's radius in m
+    if flux_cube.coord(latitude).bounds is None:
+        flux_cube.coord(latitude).guess_bounds()
+    if flux_cube.coord(longitude).bounds is None:
+        flux_cube.coord(longitude).guess_bounds()
+
+    # Remove average of flux field to account for storage term
+    grid_areas = iris.analysis.cartography.area_weights(flux_cube)
+    data_mean = flux_cube.collapsed(["longitude", "latitude"],
+                                    iris.analysis.MEAN,
+                                    weights=grid_areas).data
+    data = flux_cube.data - data_mean
+
+    logger.info("Calling spherical_poisson")
+    sphpo = SphericalPoisson(logger,
+                             source=data * (earth_radius**2.0),
+                             tolerance=2.0e-4)
+    sphpo.solve()
+    sphpo.calc_meridional_heat_transport()
+    logger.info("Ending spherical_poisson")
+
+    # Energy flux potential
+    efp_cube = iris.cube.Cube(sphpo.energy_flux_potential[1:-1, 1:-1],
+                              long_name=f"energy_flux_potential"
+                                        f"_of_{flux_cube.var_name}",
+                              var_name=f"{flux_cube.var_name}_efp",
+                              units='J s-1',
+                              dim_coords_and_dims=[(flux_cube.coords()[0], 0),
+                                                   (flux_cube.coords()[1], 1)])
+
+    # MHT data cube
+    collapsed_longitude = iris.coords.AuxCoord(180.0,
+                                               bounds=(0.0, 360.0),
+                                               long_name='longitude',
+                                               standard_name='longitude',
+                                               units='degrees')
+    dim_coords_and_dims = [(flux_cube.coord('latitude'), 0)]
+    aux_coords_and_dims = [(flux_cube.coord('time'), None),
+                           (collapsed_longitude, None)]
+    mht_cube = iris.cube.Cube(sphpo.meridional_heat_transport,
+                              long_name=f"meridional_heat_transport_of"
+                                        f"_{flux_cube.var_name}",
+                              var_name=f"{flux_cube.var_name}_mht",
+                              units='W',
+                              dim_coords_and_dims=dim_coords_and_dims,
+                              aux_coords_and_dims=aux_coords_and_dims)
+    return efp_cube, mht_cube
+
+
+def symmetry_metric(cube):
+    """Calculate symmetry metrics for a zonal-mean cube.
+
+    It returns the symmetry metric S, as defined in Pearce and
+    Bodas-Salcedo, JClim, 2023, for 3 regions: entire hemisphere,
+    tropics (0 to 30 deg latitude) and extratropics
+    (30 to 90 degrees latitude). Perfectly symmetrical latitude
+    bands give S=0.
+
+    Parameters
+    ----------
+    cube : :class:`iris.cube.Cube`
+        Input cube.
+
+    Returns
+    -------
+    hemisphere: float
+        Metric for the whole hemisphere.
+    tropics: float
+        Metric for the tropics.
+    extra_tropics: float
+        Metric for the extra-tropics.
+    """
+    hemisphere = np.abs(
+        weight_zm(cube, latitude=(0, 90, False, False))[::-1] +
+        weight_zm(cube, latitude=(-90, 0, False, False))).sum()
+    tropics = np.abs(
+        weight_zm(cube, latitude=(0, 30, False, False))[::-1] +
+        weight_zm(cube, latitude=(-30, 0, False, False))).sum()
+    extra_tropics = np.abs(
+        weight_zm(cube, latitude=(30, 90, False, False))[::-1] +
+        weight_zm(cube, latitude=(-90, -30, False, False))).sum()
+    return hemisphere, tropics, extra_tropics
+
+
+def format_plot(axes, label, title):
+    """Format plots in quiver panel.
+
+    Parameters
+    ----------
+    axes : :class:`matplotlib.axes.Axes`
+        Input axes.
+    label : string
+        Top-left plot label.
+    title : string
+        Plot title.
+    """
+    axes.set_xticks(np.arange(-180, 190, 60))
+    axes.set_xticklabels(['180', '120W', '60W', '0', '60E', '120E', '180'])
+    axes.set_yticks(np.arange(-90, 100, 30))
+    axes.set_yticklabels(['90S', '60S', '30S', 'Eq', '30N', '60N', '90N'])
+    axes.annotate(label, xy=(0, 1.05), xycoords='axes fraction', color='k')
+    axes.set_title(title)
+
+
+class ImpliedHeatTransport:
+    """Class that solves implied heat transport for an input dataset.
+
+    These are the physical meanings of the main acronyms
+    used in the variable names:
+       FLX: radiative flux
+       EFP: energy flux potential
+       MHT: meridional heat transport
+    """
+
+    def __init__(self, flx_files):
+        """Calculate all the diagnostics for all fluxes in ``flx_files``.
+
+        Parameters
+        ----------
+        flx_files : list
+            List of files with input data.
+        """
+        self.flx_files = flx_files
+
+        # Create cube lists for the different datasets
+        self.flx_clim = iris.cube.CubeList()
+        self.mht_clim = iris.cube.CubeList()
+        self.efp_clim = iris.cube.CubeList()
+        self.mht_rolling_mean = iris.cube.CubeList()
+        self.symmetry_metric = iris.cube.CubeList()
+
+        # Calculate 12-month rolling means for time series.
+        self.flx_rolling_mean = iris.cube.CubeList()
+        for flx_file in flx_files:
+            flx = iris.load_cube(flx_file)
+            if len(flx.shape) == 3:
+                self.flx_rolling_mean.append(
+                    flx.rolling_window('time', iris.analysis.MEAN, 12))
+            else:
+                self.flx_clim.append(flx)
+
+        # Compute derived fluxes
+        self.derived_fluxes()
+
+        # Calculate Energy Flux Potential and Meridional Heat Transport
+        # for each flux component
+        self.compute_efp_and_mht()
+
+        # Times series of MHT symmetry metric
+        self.mht_symmetry_metrics()
+
+        self.print()
+
+    def compute_efp_and_mht(self):
+        """Calculate Energy Flux Potential and meridional heat transport.
+
+        Loop over input data and calculate EFP and MHT of the
+        climatologies of radiative fluxes and the 12-month
+        rolling means of radiative fluxes.
+        """
+        # Loop over climatologies
+        for flx in self.flx_clim:
+            efp, mht = call_poisson(flx)
+            self.efp_clim.append(efp)
+            self.mht_clim.append(mht)
+        # Loop over rolling means
+        for flx_rm in self.flx_rolling_mean:
+            mht_series = iris.cube.CubeList()
+            for flx in flx_rm.slices_over('time'):
+                efp, mht = call_poisson(flx)
+                mht_series.append(mht)
+            # Append MHT rolling mean after merging time series.
+            self.mht_rolling_mean.append(mht_series.merge_cube())
+
+    def derived_fluxes(self):
+        """Calculate derived radiative fluxes.
+
+        rlnt_clim: climatology of net LW TOA
+        rtntcs_clim: climatology of clear-sky net TOA
+        rtntcs_rolling_mean: 12-month rolling mean of rtntcs
+        """
+        # Derived TOA climatologies: rlnt_clim, rtntcs_clim
+        rlnt_clim = -1.0 * self.flx_clim.extract_cube(
+            NameConstraint(var_name="rlut"))
+        rlnt_clim.var_name = "rlnt"
+        rlnt_clim.long_name = "radiative_flux_of_rlnt"
+        self.flx_clim.append(rlnt_clim)
+        rtntcs_clim = (self.flx_clim.extract_cube(
+                       NameConstraint(var_name="rsdt")) -
+                       self.flx_clim.extract_cube(
+                       NameConstraint(var_name="rsutcs")) -
+                       self.flx_clim.extract_cube(
+                       NameConstraint(var_name="rlutcs")))
+        rtntcs_clim.var_name = "rtntcs"
+        rtntcs_clim.long_name = "radiative_flux_of_rtntcs"
+        self.flx_clim.append(rtntcs_clim)
+        # Annual rolling means clear-sky net total TOA
+        rtntcs_rolling_mean = (self.flx_rolling_mean.extract_cube(
+                               NameConstraint(var_name="rsdt")) -
+                               self.flx_rolling_mean.extract_cube(
+                               NameConstraint(var_name="rsutcs")) -
+                               self.flx_rolling_mean.extract_cube(
+                               NameConstraint(var_name="rlutcs")))
+        rtntcs_rolling_mean.var_name = "rtntcs"
+        rtntcs_rolling_mean.long_name = "radiative_flux_of_rtntcs"
+        self.flx_rolling_mean.append(rtntcs_rolling_mean)
+
+    def print(self):
+        """Print variable names of all cubes in an IHT object."""
+        logger.info("=== implied_heat_transport object ===")
+        logger.info(self.mht_clim)
+        info_message = "Long name: %s; Variable: %s."
+        for climatology in self.mht_clim:
+            logger.info(info_message,
+                        climatology.long_name,
+                        climatology.var_name)
+
+        logger.info(self.efp_clim)
+        for climatology in self.efp_clim:
+            logger.info(info_message,
+                        climatology.long_name,
+                        climatology.var_name)
+
+        logger.info(self.flx_clim)
+        for climatology in self.flx_clim:
+            logger.info(info_message,
+                        climatology.long_name,
+                        climatology.var_name)
+
+        logger.info(self.mht_rolling_mean)
+        for rolling_mean in self.mht_rolling_mean:
+            logger.info(info_message,
+                        rolling_mean.long_name,
+                        rolling_mean.var_name)
+
+        logger.info(self.symmetry_metric)
+        for metric in self.symmetry_metric:
+            logger.info(info_message,
+                        metric.long_name,
+                        metric.var_name)
+
+        logger.info(self.flx_files)
+
+    def mht_symmetry_metrics(self):
+        """Calculate symmetry metrics.
+
+        Produce 12-month rolling means for all monthly time series
+        of MHT.
+        """
+        petaunit = 1.0e15
+        for mht_series in self.mht_rolling_mean:
+            time_coord = mht_series.coord('time')
+            ntime = time_coord.shape[0]
+            hemisphere = np.zeros(ntime)
+            tropics = np.zeros(ntime)
+            extra_tropics = np.zeros(ntime)
+            for i in np.arange(ntime):
+                hemisphere[i], tropics[i], extra_tropics[i] = (
+                    symmetry_metric(mht_series[i]))
+            # Create the cubes for each metric
+            long_name = f"symmetry_hemisphere_of_{mht_series.long_name}"
+            var_name = f"s_hem_{mht_series.var_name}"
+            cube_h = iris.cube.Cube(hemisphere / petaunit,
+                                    long_name=long_name,
+                                    var_name=var_name,
+                                    units="PW",
+                                    dim_coords_and_dims=[(time_coord, 0)])
+            long_name = f"symmetry_tropics_of_{mht_series.long_name}"
+            var_name = f"s_tro_{mht_series.var_name}"
+            cube_t = iris.cube.Cube(tropics / petaunit,
+                                    long_name=long_name,
+                                    var_name=var_name,
+                                    units="PW",
+                                    dim_coords_and_dims=[(time_coord, 0)])
+            long_name = f"symmetry_extratropics_of_{mht_series.long_name}"
+            var_name = f"s_ext_{mht_series.var_name}"
+            cube_e = iris.cube.Cube(extra_tropics / petaunit,
+                                    long_name=long_name,
+                                    var_name=var_name,
+                                    units="PW",
+                                    dim_coords_and_dims=[(time_coord, 0)])
+            self.symmetry_metric.append(cube_h)
+            self.symmetry_metric.append(cube_t)
+            self.symmetry_metric.append(cube_e)
+
+    def mht_plot(self, var_names, legend_label, ylim=(-10, 10)):
+        """Produce a single multi-line plot of MHT components.
+
+        MHT is presented in PW. Up to three variables are on each plot.
+
+        Parameters
+        ----------
+        var_names : list
+            Variable names to plot, e.g. ["rtnt_mht", "rsnt_mht"].
+        legend_label : list
+            List of labels for each line.
+        ylim : tuple
+            y axis limits.
+        """
+        plt.figure()
+        for i, vname in enumerate(var_names):
+            mht = self.mht_clim.extract_cube(NameConstraint(var_name=vname))
+            mht.convert_units('PW')
+            plt.plot(mht.coord('latitude').points,
+                     mht.data,
+                     label=legend_label[i])
+        plt.hlines(0, -90, 90, color='k', linestyles=':')
+        plt.vlines(0, -10, 10, color='k', linestyles=':')
+        plt.xlim(-90, 90)
+        plt.ylim(ylim[0], ylim[1])
+        plt.xticks(np.arange(-90, 120, 30))
+        plt.xlabel('Latitude')
+        plt.ylabel('MHT (PW)')
+        plt.legend()
+        plt.tight_layout()
+
+    def cre_mht_plot(self, left, right, ylim=(-1.5, 1.5)):
+        """Produce two multiline plots of MHT components.
+
+        Parameters
+        ----------
+        left : dictionary
+            Dictionary with variable names and labels for
+            the LHS plot, e.g.
+            {'vname': ['netcre_mht', 'swcre_mht', 'lwcre_mht'],
+            'legend': ['Net CRE', 'SW CRE', 'LW CRE']}
+        right : dictionary
+            As ``left`` but for the RHS plot
+        ylim : tuple
+            y axis limits.
+        """
+        plt.figure(figsize=(11, 5))
+        ax1 = plt.subplot(121)
+        for i, vname in enumerate(left['vname']):
+            mht = self.mht_clim.extract_cube(NameConstraint(var_name=vname))
+            mht.convert_units('PW')
+            ax1.plot(mht.coord('latitude').points,
+                     mht.data,
+                     label=left['legend'][i])
+        ax1.axhline(0, color='k', ls=':')
+        ax1.axvline(0, color='k', ls=':')
+        ax1.set_xlim(-90, 90)
+        ax1.set_xticks(np.arange(-90, 120, 30))
+        ax1.set_xlabel('Latitude')
+        ax1.set_ylim(ylim[0], ylim[1])
+        ax1.set_ylabel('MHT (PW)')
+        ax1.annotate('(a)',
+                     xy=(0.01, 0.95),
+                     xycoords='axes fraction',
+                     color='k')
+        plt.legend()
+
+        ax2 = plt.subplot(122)
+        col = ['C3', 'C7']
+        for i, vname in enumerate(right['vname']):
+            mht = self.mht_clim.extract_cube(NameConstraint(var_name=vname))
+            mht.convert_units('PW')
+            ax2.plot(mht.coord('latitude').points,
+                     -mht.data,
+                     label=right['legend'][i],
+                     color=col[i])
+        ax2.axhline(0, color='k', ls=':')
+        ax2.axvline(0, color='k', ls=':')
+        ax2.set_xlim(-90, 90)
+        ax2.set_xticks(np.arange(-90, 120, 30))
+        ax2.set_xlabel('Latitude')
+        ax2.set_ylim(ylim[0], ylim[1])
+        ax2.set_ylabel('MHT (PW)')
+        ax2.annotate('(b)',
+                     xy=(0.01, 0.95),
+                     xycoords='axes fraction',
+                     color='k')
+        plt.legend(loc='lower right')
+        plt.tight_layout()
+
+    def quiver_start(self, ntot, step):
+        """Calculate start point for quiver plot.
+
+        Parameters
+        ----------
+        ntot : int
+            Total number of points of the full vector.
+        step : int
+            Sampling step.
+        """
+        start = (ntot - 2 - ((ntot - 2) // step) * step) // 2
+        return start
+
+    def quiver_maps_data(self, vnames, change_sign):
+        """Obtain data for one row of plots.
+
+        Parameters
+        ----------
+        vnames : list
+            Two-element list with the names of the EFP and
+            flux variables.
+        change_sign : list
+            Two-element list of booleans to indicate if
+            the variable has to be plotted with the sign changed.
+        """
+        efp = self.efp_clim.extract_cube(NameConstraint(var_name=vnames[0]))
+        flx = self.flx_clim.extract_cube(NameConstraint(var_name=vnames[1]))
+        # The choice of origin for efp is arbitrary,
+        # we choose the unweighted mean.
+        efp = efp - efp.collapsed(efp.coords(), iris.analysis.MEAN)
+        flx = flx - area_average(flx)
+        if change_sign[0]:
+            efp = -efp
+        if change_sign[1]:
+            flx = -flx
+        efp.convert_units("PW")
+        v_component, u_component = np.gradient(efp.data)
+        u_component = u_component[1:-1, 1:-1]
+        v_component = v_component[1:-1, 1:-1]
+        return {'efp': efp, 'flx': flx, 'uuu': u_component, 'vvv': v_component}
+
+    def quiver_subplot(self, dargs):
+        """Produce panel with maps of EFPs and fluxes.
+
+        Plot figures with energy flux potential and gradient in the left-hand
+        column and the corresponding source term in the right-hand column.
+
+        Parameters
+        ----------
+        dargs : dictionary
+            Dictionary with variable names and plot configuration
+            data.
+        """
+        mshgrd = np.meshgrid(self.flx_clim[0].coord('longitude').points,
+                             self.flx_clim[0].coord('latitude').points)
+        nrows = len(dargs['var_name'])
+        # Calculate sampling for vector plot
+        dxy = [mshgrd[0].shape[1] // 20, mshgrd[0].shape[0] // 10]
+        startx = self.quiver_start(mshgrd[0].shape[1], dxy[0])
+        starty = self.quiver_start(mshgrd[0].shape[0], dxy[1])
+
+        # Set grid layout depending on number of rows.
+        # Place figures every grid_step rows in the grid.
+        grid_step = 7
+        if nrows == 3:
+            plt.figure(figsize=(10, 10))
+            grds = gridspec.GridSpec(22, 2)
+            grds.update(wspace=0.25, hspace=1.5)
+        elif nrows == 2:
+            plt.figure(figsize=(10, 6.5))
+            grds = gridspec.GridSpec(15, 2)
+            grds.update(wspace=0.25, hspace=1.5)
+        elif nrows == 1:
+            plt.figure(figsize=(12, 4))
+            grds = gridspec.GridSpec(8, 2)
+            grds.update(wspace=0.25, hspace=1.5)
+
+        cbs = []
+        for i in range(nrows):
+            data = self.quiver_maps_data(dargs['var_name'][i],
+                                         dargs['change_sign'][i])
+            plt.subplot(grds[i * grid_step:(i * grid_step) + grid_step, 0],
+                        projection=ccrs.PlateCarree(central_longitude=0))
+            cbs.append(
+                iplt.contourf(data['efp'],
+                              levels=np.linspace(dargs['vmin'], dargs['vmax'],
+                                                 dargs['nlevs'])))
+            plt.gca().coastlines()
+            if i == 0:
+                qqq = plt.quiver(mshgrd[0][starty::dxy[1], startx::dxy[0]],
+                                 mshgrd[1][starty::dxy[1], startx::dxy[0]],
+                                 data['uuu'][starty::dxy[1], startx::dxy[0]],
+                                 data['vvv'][starty::dxy[1], startx::dxy[0]],
+                                 pivot='mid',
+                                 color='w',
+                                 width=0.005)
+            else:
+                plt.quiver(mshgrd[0][starty::dxy[1], startx::dxy[0]],
+                           mshgrd[1][starty::dxy[1], startx::dxy[0]],
+                           data['uuu'][starty::dxy[1], startx::dxy[0]],
+                           data['vvv'][starty::dxy[1], startx::dxy[0]],
+                           pivot='mid',
+                           scale=qqq.scale,
+                           color='w')
+            format_plot(plt.gca(), dargs['label'][i][0], dargs['title'][i][0])
+
+            plt.subplot(grds[i * grid_step:(i * grid_step) + grid_step, 1],
+                        projection=ccrs.PlateCarree(central_longitude=0))
+            cbs.append(
+                iplt.contourf(data['flx'],
+                              levels=np.linspace(dargs['wmin'], dargs['wmax'],
+                                                 dargs['nwlevs']),
+                              cmap='RdBu_r'))
+            plt.gca().coastlines()
+            format_plot(plt.gca(), dargs['label'][i][1], dargs['title'][i][1])
+
+        plt.subplot(grds[-1, 0])
+        plt.colorbar(cbs[0],
+                     cax=plt.gca(),
+                     orientation='horizontal',
+                     label='Energy flux potential (PW)')
+        plt.subplot(grds[-1, 1])
+        plt.colorbar(cbs[1],
+                     cax=plt.gca(),
+                     orientation='horizontal',
+                     label=r'Flux (Wm$^{-2}$)',
+                     ticks=np.linspace(dargs['wmin'], dargs['wmax'],
+                                       dargs['nwlevs'])[1::dargs['wlevstep']])
+
+        if nrows == 3:
+            plt.subplots_adjust(left=0.1, right=0.94, top=1.0, bottom=0.11)
+        elif nrows == 2:
+            plt.subplots_adjust(left=0.11, right=0.9, top=1.0, bottom=0.13)
+        elif nrows == 1:
+            plt.subplots_adjust(left=0.11, right=0.9, top=1.0, bottom=0.20)
+
+    def plot_symmetry_time_series(self):
+        """Produce Figure 6.
+
+        All-sky and clear-sky time series of the symmetry metrics for
+        three regions: globe, tropics and extra-tropics.
+        """
+        var_list = [["s_hem_rtnt_mht", "s_hem_rtntcs_mht"],
+                    ["s_tro_rtnt_mht", "s_tro_rtntcs_mht"],
+                    ["s_ext_rtnt_mht", "s_ext_rtntcs_mht"]]
+        col = ['C0', 'C1']
+        label = [
+            r'Global: 0$^\mathrm{o}$ - 90$^\mathrm{o}$',
+            r'Tropics: 0$^\mathrm{o}$ - 30$^\mathrm{o}$',
+            r'Extratropics: 30$^\mathrm{o}$ - 90$^\mathrm{o}$'
+        ]
+        legend_label = ["TOA net all-sky", "TOA net clear-sky"]
+
+        plt.figure(figsize=(6, 12))
+        for count, (var_name_1, var_name_2) in enumerate(var_list):
+            yy0 = self.symmetry_metric.extract_cube(
+                NameConstraint(var_name=var_name_1))
+            yy1 = self.symmetry_metric.extract_cube(
+                NameConstraint(var_name=var_name_2))
+            axx = plt.subplot(3, 1, count + 1)
+            dtx = [
+                datetime.datetime.strptime(str(cell[0]), '%Y-%m-%d %H:%M:%S')
+                for cell in yy0.coord('time').cells()
+            ]
+            plt.plot(dtx, yy0.data, lw=4, linestyle='-', label=legend_label[0])
+            plt.plot(dtx, yy1.data, lw=4, linestyle='-', label=legend_label[1])
+            axx.annotate(rf'$\sigma$: {np.std(yy0.data):5.3f}', (0.05, 0.55),
+                         xycoords='axes fraction',
+                         color=col[0])
+            axx.annotate(rf'$\sigma$: {np.std(yy1.data):5.3f}', (0.05, 0.45),
+                         xycoords='axes fraction',
+                         color=col[1])
+            axx.set_ylim(0, 0.8)
+            axx.set_ylabel(r'$S$ (PW)')
+            axx.xaxis.set_major_locator(mdates.YearLocator(3, month=1, day=1))
+            axx.xaxis.set_major_formatter(mdates.DateFormatter('%Y'))
+            axx.xaxis.set_minor_locator(mdates.YearLocator())
+            axx.set_title(label[count])
+            if count == 0:
+                plt.legend(loc=5)
+        plt.tight_layout()
+
+
+def efp_maps(iht, model, experiment, config):
+    """Produce Figures 2, 4, and 5.
+
+    Parameters
+    ----------
+    iht : :class: ImpliedHeatTransport
+        Object with the recipe datasets.
+    model : string
+        Model name.
+    experiment : string
+        Experiment name.
+    config : dict
+        The ESMValTool configuration.
+    """
+    # Figure 2
+    iht.quiver_subplot(
+        {
+            'var_name': [['rtnt_efp', 'rtnt'], ['rsnt_efp', 'rsnt'],
+                         ['rlnt_efp', 'rlnt']],
+            'title': [['$P_{TOA}^{TOT}$', r'$\Delta F_{TOA}^{TOT}$'],
+                      ['$P_{TOA}^{SW}$', r'$\Delta F_{TOA}^{SW}$'],
+                      ['$P_{TOA}^{LW}$', r'$\Delta F_{TOA}^{LW}$']],
+            'label': [['(a)', '(b)'], ['(c)', '(d)'], ['(e)', '(f)']],
+            'change_sign': [[False, False], [False, False], [False, False]],
+            'wmin':
+            -180,
+            'wmax':
+            180,
+            'nwlevs':
+            19,
+            'wlevstep':
+            4,
+            'vmin':
+            -1.2,
+            'vmax':
+            1.2,
+            'nlevs':
+            11
+        })
+    flx_files = matching_strings(iht.flx_files, ['rtnt/',
+                                                 'rsut/',
+                                                 'rlut/'])
+    provenance_record = get_provenance_record(flx_files, caption['F2'])
+    figname = f"figure2_{model}_{experiment}"
+    save_figure(figname, provenance_record, config)
+    # Figure 4
+    iht.quiver_subplot(
+        {
+            'var_name': [['netcre_efp', 'netcre'], ['swcre_efp', 'swcre'],
+                         ['lwcre_efp', 'lwcre']],
+            'title': [['$P_{TOA}^{TOTCRE}$', r'$\Delta CRE_{TOA}^{TOT}$'],
+                      ['$P_{TOA}^{SWCRE}$', r'$\Delta CRE_{TOA}^{SW}$'],
+                      ['$P_{TOA}^{LWCRE}$', r'$\Delta CRE_{TOA}^{LW}$']],
+            'label': [['(a)', '(b)'], ['(c)', '(d)'], ['(e)', '(f)']],
+            'change_sign': [[False, False], [False, False], [False, False]],
+            'wmin':
+            -60,
+            'wmax':
+            60,
+            'nwlevs':
+            13,
+            'wlevstep':
+            2,
+            'vmin':
+            -0.3,
+            'vmax':
+            0.3,
+            'nlevs':
+            11
+        })
+    flx_files = matching_strings(iht.flx_files, ['netcre/',
+                                                 'swcre/',
+                                                 'lwcre/'])
+    provenance_record = get_provenance_record(flx_files, caption['F4'])
+    figname = f"figure4_{model}_{experiment}"
+    save_figure(figname, provenance_record, config)
+    # Figure 5
+    iht.quiver_subplot(
+        {
+            'var_name': [['rsutcs_efp', 'rsutcs'], ['rsut_efp', 'rsut']],
+            'title': [['$P_{TOA}^{SWup, clr}$',
+                       r'$\Delta F_{TOA}^{SWup, clr}$'],
+                      ['$P_{TOA}^{SWup, all}$',
+                       r'$\Delta F_{TOA}^{SWup, all}$']],
+            'label': [['(a)', '(b)'], ['(c)', '(d)']],
+            'change_sign': [[True, True], [True, True]],
+            'wmin': -100,
+            'wmax': 100,
+            'nwlevs': 21,
+            'wlevstep': 3,
+            'vmin': -0.35,
+            'vmax': 0.35,
+            'nlevs': 11
+        })
+    flx_files = matching_strings(iht.flx_files, ['rsut/', 'rsutcs/'])
+    provenance_record = get_provenance_record(flx_files, caption['F5'])
+    figname = f"figure5_{model}_{experiment}"
+    save_figure(figname, provenance_record, config)
+
+
+def mht_plots(iht, model, experiment, config):
+    """Produce Figures 1 and 3.
+
+    Parameters
+    ----------
+    iht : :class: ImpliedHeatTransport
+        Object with the recipe datasets.
+    model : string
+        Model name.
+    experiment : string
+        Experiment name.
+    config : dict
+        The ESMValTool configuration.
+    """
+    # Figure 1
+    iht.mht_plot(["rtnt_mht", "rsnt_mht", "rlnt_mht"], ['Net', 'SW', 'LW'])
+    flx_files = matching_strings(iht.flx_files, ['rtnt/', 'rsut/', 'rlut/'])
+    provenance_record = get_provenance_record(flx_files, caption['F1'])
+    figname = f"figure1_{model}_{experiment}"
+    save_figure(figname, provenance_record, config)
+    # Figure 3
+    iht.cre_mht_plot(
+        {
+            'vname': ['netcre_mht', 'swcre_mht', 'lwcre_mht'],
+            'legend': ['Net CRE', 'SW CRE', 'LW CRE']
+        }, {
+            'vname': ['rsut_mht', 'rsutcs_mht'],
+            'legend': ['-1 x OSR (all-sky)', '-1 x OSR (clear-sky)']
+        })
+    flx_files = matching_strings(iht.flx_files, ['netcre/', 'swcre/', 'lwcre/',
+                                                 'rsut/', 'rsutcs/'])
+    provenance_record = get_provenance_record(flx_files, caption['F3'])
+    figname = f"figure3_{model}_{experiment}"
+    save_figure(figname, provenance_record, config)
+
+
+def symmetry_plots(iht, model, experiment, config):
+    """Produce Figure 6.
+
+    Parameters
+    ----------
+    iht : :class: ImpliedHeatTransport
+        Object with the recipe datasets.
+    model : string
+        Model name.
+    experiment : string
+        Experiment name.
+    config : dict
+        The ESMValTool configuration.
+    """
+    iht.plot_symmetry_time_series()
+    flx_files = matching_strings(iht.flx_files, ['rtnt_monthly',
+                                                 'rsutcs_monthly',
+                                                 'rlutcs_monthly',
+                                                 'rsdt_monthly'])
+    provenance_record = get_provenance_record(flx_files, caption['F6'])
+    figname = f"figure6_{model}_{experiment}"
+    save_figure(figname, provenance_record, config)
+
+
+def plot_single_model_diagnostics(iht_dict, config):
+    """Produce plots for a single model and experiment.
+
+    Parameters
+    ----------
+    iht_dict : dict
+        iht_dict is a two-level dictionary: iht_dict[model][experiment]
+    config : dict
+        The ESMValTool configuration.
+    """
+    for model, iht_model in iht_dict.items():
+        logger.info("Plotting model: %s", model)
+        for experiment, iht_experiment in iht_model.items():
+            logger.info("Plotting experiment: %s", experiment)
+            mht_plots(iht_experiment, model, experiment, config)
+            efp_maps(iht_experiment, model, experiment, config)
+            symmetry_plots(iht_experiment, model, experiment, config)
+
+
+def main(config):
+    """Produce all the recipe's plots.
+
+    Produce Figures 1 to 6 of Pearce and Bodas-Salcedo (2023) for each
+    model and dataset combination.
+
+    Parameters
+    ----------
+    config : dict
+        The ESMValTool configuration.
+    """
+    input_data = deepcopy(list(config['input_data'].values()))
+    input_data = group_metadata(input_data, 'dataset', sort='variable_group')
+
+    # Arrange input flux files in a 2-level dictionary [model_name][dataset]
+    flux_files = {}
+    for model_name, datasets in input_data.items():
+        flux_files[model_name] = {}
+        for dataset in datasets:
+            if dataset['dataset'] in flux_files[model_name]:
+                flux_files[model_name][dataset['dataset']].append(
+                    dataset['filename'])
+            else:
+                flux_files[model_name][dataset['dataset']] = [
+                    dataset['filename']
+                ]
+
+    # Create dictionary of implied_heat_transport objects.
+    # It's a 2-level dictionary like flux_files.
+    # This is where all the calculations are done.
+    iht = {}
+    for model_name, datasets in flux_files.items():
+        logger.info("Model %s", model_name)
+        iht[model_name] = {}
+        for dataset_name, files in datasets.items():
+            logger.info("Dataset %s", dataset_name)
+            iht[model_name][dataset_name] = ImpliedHeatTransport(files)
+
+    # Produce plots
+    plot_single_model_diagnostics(iht, config)
+
+
+if __name__ == '__main__':
+
+    with run_diagnostic() as configuration:
+        main(configuration)
diff --git a/esmvaltool/recipes/recipe_iht_toa.yml b/esmvaltool/recipes/recipe_iht_toa.yml
new file mode 100644
index 0000000000..19e05f5ac2
--- /dev/null
+++ b/esmvaltool/recipes/recipe_iht_toa.yml
@@ -0,0 +1,119 @@
+# ESMValTool
+# recipe_transport.yml
+---
+documentation:
+  title: Implied heat transport
+
+  description: |
+    Horizontal implied heat transport of the entire column derived from
+    TOA radiative fluxes.
+
+#    The 'single_model' script  produces Figures 1 to 6 in Pearce and
+#    Bodas-Salcedo (2023) for each of the datasets chosen.
+
+  authors:
+    - pearce_francesca
+    - bodas-salcedo_alejandro
+
+  maintainer:
+    - bodas-salcedo_alejandro
+
+  references:
+    - pearce23jclim
+
+datasets:
+  # The CERES-EBAF observations reproduce the results of Pearce and
+  # Bodas-Salcedo (2023), but it can be applied to model data.
+  - {dataset: CERES-EBAF, project: obs4MIPs, tier: 1, start_year: 2001, end_year: 2010}
+  # - {dataset: HadGEM3-GC31-LL, project: CMIP6, exp: amip, ensemble: r1i1p1f3, grid: gn, mip: Amon, start_year: 1990, end_year: 2005}
+
+preprocessors:
+  # It is recommended to use a low resolution grid as the
+  # calculations are computationally expensive
+  common_grid:
+    regrid:
+      target_grid: 5.0x5.0
+      scheme: area_weighted
+
+  climate_mean_global:
+    regrid:
+      target_grid: 5.0x5.0
+      scheme: area_weighted
+    climate_statistics:
+      operator: mean
+
+diagnostics:
+
+  implied_heat_transport:
+    title: TOA implied heat transports
+    description: Energy flux potential and implied heat transports for TOA radiative fluxes.
+    themes:
+      - phys
+    realms:
+      - atmos
+    variables:
+      rtnt:
+        derive: true
+        short_name: rtnt
+        mip: Amon
+        preprocessor: climate_mean_global
+      rtnt_monthly:
+        derive: true
+        short_name: rtnt
+        mip: Amon
+        preprocessor: common_grid
+      rsnt:
+        derive: true
+        short_name: rsnt
+        mip: Amon
+        preprocessor: climate_mean_global
+      rlut:
+        short_name: rlut
+        mip: Amon
+        preprocessor: climate_mean_global
+      rlutcs:
+        short_name: rlutcs
+        mip: Amon
+        preprocessor: climate_mean_global
+      rlutcs_monthly:
+        short_name: rlutcs
+        mip: Amon
+        preprocessor: common_grid
+      rsutcs:
+        short_name: rsutcs
+        mip: Amon
+        preprocessor: climate_mean_global
+      rsutcs_monthly:
+        short_name: rsutcs
+        mip: Amon
+        preprocessor: common_grid
+      rsut:
+        short_name: rsut
+        mip: Amon
+        preprocessor: climate_mean_global
+      rsdt:
+        short_name: rsdt
+        mip: Amon
+        preprocessor: climate_mean_global
+      rsdt_monthly:
+        short_name: rsdt
+        mip: Amon
+        preprocessor: common_grid
+      netcre:
+        derive: true
+        short_name: netcre
+        mip: Amon
+        preprocessor: climate_mean_global
+      swcre:
+        derive: true
+        short_name: swcre
+        mip: Amon
+        preprocessor: climate_mean_global
+      lwcre:
+        derive: true
+        short_name: lwcre
+        mip: Amon
+        preprocessor: climate_mean_global
+    scripts:
+      single_model:
+        script: iht_toa/single_model_diagnostics.py
diff --git a/esmvaltool/references/pearce23jclim.bibtex b/esmvaltool/references/pearce23jclim.bibtex
new file mode 100644
index 0000000000..ebfac532ad
--- /dev/null
+++ b/esmvaltool/references/pearce23jclim.bibtex
@@ -0,0 +1,13 @@
+@article{pearce23jclim,
+	doi = {10.1175/JCLI-D-22-0149.1},
+	url = {https://doi.org/10.1175/JCLI-D-22-0149.1},
+	year = 2023,
+	month = {jun},
+	publisher = {American Meteorological Society},
+	volume = {36},
+	number = {9},
+	pages = {1--30},
+	author = {Francesca Pearce and Alejandro Bodas-Salcedo},
+	title = {Implied heat transport from {CERES} data: direct radiative effect of clouds on regional patterns and hemispheric symmetry},
+	journal = {Journal of Climate}
+}
diff --git a/setup.py b/setup.py
index 940cc5224f..bd584b7b3b 100755
--- a/setup.py
+++ b/setup.py
@@ -44,6 +44,7 @@
         'natsort',
         'nc-time-axis',
         'netCDF4',
+        'numba',
         'numpy!=1.24.3',  # severe masking bug
         'packaging',
         'openpyxl',

From 72174d39c8b320832f9fcfef64f270c3697335e9 Mon Sep 17 00:00:00 2001
From: Klaus Zimmermann <klaus.zimmermann@smhi.se>
Date: Thu, 2 Nov 2023 17:17:55 +0100
Subject: [PATCH 59/93] Use ESMValCore v2.10.0 release candidates (#3404)

Co-authored-by: Valeriu Predoi <valeriu.predoi@gmail.com>
---
 .github/workflows/test-development.yml                |  1 +
 .github/workflows/test.yml                            |  1 +
 environment.yml                                       |  4 ++--
 environment_osx.yml                                   |  4 ++--
 .../data/formatters/datasets/esacci_watervapour.py    |  4 ++--
 esmvaltool/utils/draft_release_notes.py               |  7 +++++--
 esmvaltool/utils/recipe_filler.py                     | 11 +----------
 tests/integration/test_recipe_filler.py               |  6 ------
 8 files changed, 14 insertions(+), 24 deletions(-)

diff --git a/.github/workflows/test-development.yml b/.github/workflows/test-development.yml
index dfede54280..cab6489548 100644
--- a/.github/workflows/test-development.yml
+++ b/.github/workflows/test-development.yml
@@ -12,6 +12,7 @@ on:
   push:
     branches:
       - main
+      - fix_recipe_filler_bkwds_incompatibility
   schedule:
     - cron: '0 0 * * *'
 
diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
index 4e2698454f..9eec648279 100644
--- a/.github/workflows/test.yml
+++ b/.github/workflows/test.yml
@@ -6,6 +6,7 @@ on:
   push:
     branches:
       - main
+      - fix_recipe_filler_bkwds_incompatibility
   schedule:
     - cron: '0 0 * * *'
 
diff --git a/environment.yml b/environment.yml
index f60db24659..fb2e5adb14 100644
--- a/environment.yml
+++ b/environment.yml
@@ -4,7 +4,7 @@ channels:
   # The release candidate channel should only be activated
   # during the rc phase right before the next release of the
   # ESMValCore.
-  # - conda-forge/label/esmvalcore_rc
+  - conda-forge/label/esmvalcore_rc
   - conda-forge
   - nodefaults
 
@@ -24,7 +24,7 @@ dependencies:
   - ecmwf-api-client
   - eofs
   - esmpy
-  - esmvalcore 2.9.*
+  - esmvalcore =2.10.0rc1
   - fiona
   - fire
   - gdal
diff --git a/environment_osx.yml b/environment_osx.yml
index fac9409617..0734dee2c6 100644
--- a/environment_osx.yml
+++ b/environment_osx.yml
@@ -4,7 +4,7 @@ channels:
   # The release candidate channel should only be activated
   # during the rc phase right before the next release of the
   # ESMValCore.
-  # - conda-forge/label/esmvalcore_rc
+  - conda-forge/label/esmvalcore_rc
   - conda-forge
   - nodefaults
 
@@ -24,7 +24,7 @@ dependencies:
   - ecmwf-api-client
   - eofs
   - esmpy
-  - esmvalcore 2.9.*
+  - esmvalcore =2.10.0rc1
   - fiona
   - fire
   - gdal
diff --git a/esmvaltool/cmorizers/data/formatters/datasets/esacci_watervapour.py b/esmvaltool/cmorizers/data/formatters/datasets/esacci_watervapour.py
index c5ec55bb16..0985e5d6e6 100644
--- a/esmvaltool/cmorizers/data/formatters/datasets/esacci_watervapour.py
+++ b/esmvaltool/cmorizers/data/formatters/datasets/esacci_watervapour.py
@@ -23,7 +23,7 @@
 import os
 
 import iris
-from esmvalcore.cmor.check import _get_time_bounds
+from esmvalcore.cmor.fixes import get_time_bounds
 from esmvalcore.preprocessor import concatenate
 
 from ...utilities import (
@@ -83,7 +83,7 @@ def cmorization(in_dir, out_dir, cfg, cfg_user, start_date, end_date):
             yearly_cube = concatenate(monthly_cubes)
             # Fix monthly time bounds
             time = yearly_cube.coord('time')
-            time.bounds = _get_time_bounds(time, 'mon')
+            time.bounds = get_time_bounds(time, 'mon')
             save_variable(yearly_cube,
                           var,
                           out_dir,
diff --git a/esmvaltool/utils/draft_release_notes.py b/esmvaltool/utils/draft_release_notes.py
index 7b1c5f61b1..13bcb4324c 100644
--- a/esmvaltool/utils/draft_release_notes.py
+++ b/esmvaltool/utils/draft_release_notes.py
@@ -10,6 +10,7 @@
 """
 import datetime
 from pathlib import Path
+from zoneinfo import ZoneInfo
 
 import dateutil
 import esmvalcore
@@ -41,8 +42,10 @@
 }
 
 PREVIOUS_RELEASE = {
-    'esmvalcore': datetime.datetime(2023, 5, 19, 16),
-    'esmvaltool': datetime.datetime(2022, 10, 28, 18),
+    'esmvalcore':
+    datetime.datetime(2023, 7, 4, 11, tzinfo=ZoneInfo("CET")),
+    'esmvaltool':
+    datetime.datetime(2022, 10, 28, 18, tzinfo=ZoneInfo("CET")),
 }
 
 LABELS = {
diff --git a/esmvaltool/utils/recipe_filler.py b/esmvaltool/utils/recipe_filler.py
index 90001674b1..91033a12c8 100755
--- a/esmvaltool/utils/recipe_filler.py
+++ b/esmvaltool/utils/recipe_filler.py
@@ -63,15 +63,6 @@
 CFG = {}
 
 
-# standard libs from esmvalcore ported here to avoid private func import
-def load_config_developer(cfg_file=None):
-    """Load the config developer file and initialize CMOR tables."""
-    cfg_developer = read_config_developer_file(cfg_file)
-    for key, value in cfg_developer.items():
-        CFG[key] = value
-    read_cmor_tables(CFG)
-
-
 def _purge_file_handlers(cfg: dict) -> None:
     """Remove handlers with filename set.
 
@@ -258,7 +249,7 @@ def read_config_user_file(config_file, folder_name, options=None):
     cfg['run_dir'] = os.path.join(cfg['output_dir'], 'run')
 
     # Read developer configuration file
-    load_config_developer(cfg['config_developer_file'])
+    read_cmor_tables(cfg['config_developer_file'])
 
     return cfg
 
diff --git a/tests/integration/test_recipe_filler.py b/tests/integration/test_recipe_filler.py
index a0f3f85333..b78ac8c5f8 100644
--- a/tests/integration/test_recipe_filler.py
+++ b/tests/integration/test_recipe_filler.py
@@ -8,14 +8,8 @@
 import pytest
 import yaml
 
-import esmvaltool.utils.recipe_filler as recipe_filler
-from esmvalcore.cmor.table import read_cmor_tables
 from esmvaltool.utils.recipe_filler import run
 
-# Initialize with standard config developer file
-std_config = recipe_filler.read_config_developer_file()
-# Initialize CMOR tables
-read_cmor_tables(std_config)
 
 # Load test configuration
 with open(os.path.join(os.path.dirname(__file__),

From 072f0bf6e5ab475155d4757fd6334efbaa508540 Mon Sep 17 00:00:00 2001
From: Bouwe Andela <b.andela@esciencecenter.nl>
Date: Thu, 2 Nov 2023 18:19:52 +0100
Subject: [PATCH 60/93] Update obs4MIPs GPCP-V2.3 dataset name in
 recipe_bock20jgr_fig_1-4.yml (#3389)

---
 .../bock20jgr/recipe_bock20jgr_fig_1-4.yml    | 25 ++++++++-----------
 1 file changed, 10 insertions(+), 15 deletions(-)

diff --git a/esmvaltool/recipes/bock20jgr/recipe_bock20jgr_fig_1-4.yml b/esmvaltool/recipes/bock20jgr/recipe_bock20jgr_fig_1-4.yml
index aaca95d116..1ae9066ec3 100644
--- a/esmvaltool/recipes/bock20jgr/recipe_bock20jgr_fig_1-4.yml
+++ b/esmvaltool/recipes/bock20jgr/recipe_bock20jgr_fig_1-4.yml
@@ -400,11 +400,10 @@ diagnostics:
     variables:
       pr:
         <<: *var_cmip6_bias
-        reference_dataset: GPCP-SG
+        reference_dataset: GPCP-V2.3
         additional_datasets: *cmip6_tas
     additional_datasets:
-      - {dataset: GPCP-SG, project: obs4MIPs, level: L3, version: v2.3,
-         tier: 1}
+      - {dataset: GPCP-V2.3, project: obs4MIPs, tier: 1}
     scripts:
       model_bias:
         <<: *model_bias_settings
@@ -416,15 +415,14 @@ diagnostics:
     variables:
       pr:
         <<: *var_cmip6_bias
-        reference_dataset: GPCP-SG
+        reference_dataset: GPCP-V2.3
         project: CMIP5
         ensemble: r1i1p1
         start_year: 1985
         end_year: 2004
         additional_datasets: *cmip5_tas
     additional_datasets:
-      - {dataset: GPCP-SG, project: obs4MIPs, level: L3, version: v2.3,
-         tier: 1}
+      - {dataset: GPCP-V2.3, project: obs4MIPs, tier: 1}
     scripts:
       model_bias:
         <<: *model_bias_settings
@@ -436,7 +434,7 @@ diagnostics:
     variables:
       pr:
         <<: *var_cmip6_bias
-        reference_dataset: GPCP-SG
+        reference_dataset: GPCP-V2.3
         mip: A1
         project: CMIP3
         modeling_realm: atm
@@ -447,8 +445,7 @@ diagnostics:
         end_year: 1999
         additional_datasets: *cmip3_tas
     additional_datasets:
-      - {dataset: GPCP-SG, project: obs4MIPs, level: L3, version: v2.3,
-         tier: 1, mip: Amon}
+      - {dataset: GPCP-V2.3, project: obs4MIPs, tier: 1, mip: Amon}
     scripts:
       model_bias:
         <<: *model_bias_settings
@@ -460,11 +457,10 @@ diagnostics:
     variables:
       pr:
         <<: *var_cmip6_bias
-        reference_dataset: GPCP-SG
+        reference_dataset: GPCP-V2.3
         additional_datasets: *cmip6_highresmip_low
     additional_datasets:
-      - {dataset: GPCP-SG, project: obs4MIPs, level: L3, version: v2.3,
-         tier: 1}
+      - {dataset: GPCP-V2.3, project: obs4MIPs, tier: 1}
     scripts:
       model_bias:
         <<: *model_bias_settings
@@ -476,11 +472,10 @@ diagnostics:
     variables:
       pr:
         <<: *var_cmip6_bias
-        reference_dataset: GPCP-SG
+        reference_dataset: GPCP-V2.3
         additional_datasets: *cmip6_highresmip_high
     additional_datasets:
-      - {dataset: GPCP-SG, project: obs4MIPs, level: L3, version: v2.3,
-         tier: 1}
+      - {dataset: GPCP-V2.3, project: obs4MIPs, tier: 1}
     scripts:
       model_bias:
         <<: *model_bias_settings

From 29b20e7d3fbee07c7f5008e57ee918f07ef5afba Mon Sep 17 00:00:00 2001
From: FranziskaWinterstein
 <119339136+FranziskaWinterstein@users.noreply.github.com>
Date: Fri, 3 Nov 2023 10:46:19 +0100
Subject: [PATCH 61/93] Download and formatting of NOAA marine boundary layer
 data for CH4 (NOAA-MBL-CH4) (#3301)

Co-authored-by: Birgit Hassler <33543691+hb326@users.noreply.github.com>
Co-authored-by: Valeriu Predoi <valeriu.predoi@gmail.com>
Co-authored-by: Klaus Zimmermann <klaus.zimmermann@smhi.se>
---
 doc/sphinx/source/input.rst                   |   2 +
 .../data/cmor_config/NOAA-MBL-CH4.yml         |  18 ++
 esmvaltool/cmorizers/data/datasets.yml        |   8 +
 .../data/downloaders/datasets/noaa_mbl_ch4.py |  38 +++++
 .../data/formatters/datasets/noaa_mbl_ch4.py  | 159 ++++++++++++++++++
 .../recipes/examples/recipe_check_obs.yml     |   8 +
 esmvaltool/references/noaa-mbl-ch4.bibtex     |   9 +
 7 files changed, 242 insertions(+)
 create mode 100644 esmvaltool/cmorizers/data/cmor_config/NOAA-MBL-CH4.yml
 create mode 100644 esmvaltool/cmorizers/data/downloaders/datasets/noaa_mbl_ch4.py
 create mode 100644 esmvaltool/cmorizers/data/formatters/datasets/noaa_mbl_ch4.py
 create mode 100644 esmvaltool/references/noaa-mbl-ch4.bibtex

diff --git a/doc/sphinx/source/input.rst b/doc/sphinx/source/input.rst
index fa6b9b00e4..626bc82133 100644
--- a/doc/sphinx/source/input.rst
+++ b/doc/sphinx/source/input.rst
@@ -387,6 +387,8 @@ A list of the datasets for which a CMORizers is available is provided in the fol
 +------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+
 | NOAA-CIRES-20CR-V3           | clt, clwvi, hus, prw, rlut, rlutcs, rsut, rsutcs (Amon)                                              |   2  | Python          |
 +------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+
+| NOAA-MBL-CH4                 | ch4s (Amon)                                                                                          |   2  | Python          |
++------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+
 | NOAAGlobalTemp               | tasa (Amon)                                                                                          |   2  | Python          |
 +------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+
 | NSIDC-0116-[nh|sh]           | usi, vsi (day)                                                                                       |   3  | Python          |
diff --git a/esmvaltool/cmorizers/data/cmor_config/NOAA-MBL-CH4.yml b/esmvaltool/cmorizers/data/cmor_config/NOAA-MBL-CH4.yml
new file mode 100644
index 0000000000..23e84a657d
--- /dev/null
+++ b/esmvaltool/cmorizers/data/cmor_config/NOAA-MBL-CH4.yml
@@ -0,0 +1,18 @@
+---
+# Common global attributes for Cmorizer output
+attributes:
+  dataset_id: NOAA-MBL-CH4
+  version: '1.0'
+  tier: 2
+  modeling_realm: atmos
+  project_id: OBS6
+  source: 'https://gml.noaa.gov/webdata/ccgg/trends/ch4/ch4_mm_gl.csv'
+  reference: 'noaa-mbl-ch4'
+
+# Variables to cmorize
+variables:
+  ch4s:
+    filename: ch4_mm_gl.csv
+    mip: Amon
+    raw_name: ch4
+    raw_units: 'nmol mol-1'
diff --git a/esmvaltool/cmorizers/data/datasets.yml b/esmvaltool/cmorizers/data/datasets.yml
index 57fa7076ba..555d7bf512 100644
--- a/esmvaltool/cmorizers/data/datasets.yml
+++ b/esmvaltool/cmorizers/data/datasets.yml
@@ -1028,6 +1028,14 @@ datasets:
       Download the following files:
       [SOURCE]/gridded/NOAAGlobalTemp_v5.0.0_gridded_s188001_e202205_c20220608T133245.nc
 
+  NOAA-MBL-CH4:
+    tier: 2
+    source: https://gml.noaa.gov/webdata/ccgg/trends/ch4/ch4_mm_gl.csv
+    last_access: 2023-07-17
+    info: |
+      Download the following file:
+      https://gml.noaa.gov/webdata/ccgg/trends/ch4/ch4_mm_gl.csv
+
   NSIDC-0116-sh:
     tier: 3
     source: https://nsidc.org/data/NSIDC-0116
diff --git a/esmvaltool/cmorizers/data/downloaders/datasets/noaa_mbl_ch4.py b/esmvaltool/cmorizers/data/downloaders/datasets/noaa_mbl_ch4.py
new file mode 100644
index 0000000000..3cbf701c97
--- /dev/null
+++ b/esmvaltool/cmorizers/data/downloaders/datasets/noaa_mbl_ch4.py
@@ -0,0 +1,38 @@
+"""Script to download NOAA-MBL-CH4."""
+import logging
+
+from esmvaltool.cmorizers.data.downloaders.wget import WGetDownloader
+
+logger = logging.getLogger(__name__)
+
+
+def download_dataset(config, dataset, dataset_info, start_date, end_date,
+                     overwrite):
+    """Download dataset.
+
+    Parameters
+    ----------
+    config : dict
+        ESMValTool's user configuration
+    dataset : str
+        Name of the dataset
+    dataset_info : dict
+         Dataset information from the datasets.yml file
+    start_date : datetime
+        Start of the interval to download
+    end_date : datetime
+        End of the interval to download
+    overwrite : bool
+        Overwrite already downloaded files
+    """
+    downloader = WGetDownloader(
+        config=config,
+        dataset=dataset,
+        dataset_info=dataset_info,
+        overwrite=overwrite,
+    )
+
+    downloader.download_file(
+        "https://gml.noaa.gov/webdata/ccgg/trends/ch4/ch4_mm_gl.csv",
+        wget_options=[],
+    )
diff --git a/esmvaltool/cmorizers/data/formatters/datasets/noaa_mbl_ch4.py b/esmvaltool/cmorizers/data/formatters/datasets/noaa_mbl_ch4.py
new file mode 100644
index 0000000000..30011229de
--- /dev/null
+++ b/esmvaltool/cmorizers/data/formatters/datasets/noaa_mbl_ch4.py
@@ -0,0 +1,159 @@
+"""ESMValTool CMORizer for NOAA-MBL-CH4 data.
+
+Tier
+    Tier 2: other freely-available dataset.
+
+Source
+    https://gml.noaa.gov/ccgg/trends_ch4/
+
+Last access
+    20230717
+
+Download and processing instructions
+    Download the file:
+    wget https://gml.noaa.gov/webdata/ccgg/trends/ch4/ch4_mm_gl.csv
+"""
+
+import logging
+import warnings
+from pathlib import Path
+
+from datetime import datetime
+import iris
+import pandas as pd
+from cf_units import Unit
+import numpy as np
+
+from esmvaltool.cmorizers.data import utilities as utils
+
+logger = logging.getLogger(__name__)
+
+LAT_COORD = iris.coords.DimCoord([0.],
+                                 bounds=[[-90.0, 90.0]],
+                                 var_name='lat',
+                                 standard_name='latitude',
+                                 long_name='latitude',
+                                 units='degrees')
+LON_COORD = iris.coords.DimCoord([180.0],
+                                 bounds=[[0., 360.]],
+                                 var_name='lon',
+                                 standard_name='longitude',
+                                 long_name='longitude',
+                                 units='degrees')
+
+
+def _fix_var_metadata(var_info, cmor_info, cube):
+    """Fix variable metadata."""
+    if 'raw_units' in var_info:
+        cube.units = var_info['raw_units']
+
+    cube.convert_units(cmor_info.units)
+
+    utils.fix_var_metadata(cube, cmor_info)
+    return cube
+
+
+def _get_time_coord(year, month):
+    """Get time coordinate."""
+    point = datetime(year=year, month=month, day=15)
+    bound_low = datetime(year=year, month=month, day=1)
+    if month == 12:
+        month_bound_up = 1
+        year_bound_up = year + 1
+    else:
+        month_bound_up = month + 1
+        year_bound_up = year
+    bound_up = datetime(year=year_bound_up, month=month_bound_up, day=1)
+    time_units = Unit('days since 1950-01-01 00:00:00', calendar='standard')
+    time_coord = iris.coords.DimCoord(
+        time_units.date2num(point),
+        bounds=time_units.date2num([bound_low, bound_up]),
+        var_name='time',
+        standard_name='time',
+        long_name='time',
+        units=time_units,
+    )
+    return time_coord
+
+
+def _get_cube(row, column_name):
+    """Create :class:`iris.cube.Cube` from :class:`pandas.Series`."""
+    time_coord = _get_time_coord(int(row['year']), int(row['month']))
+    lat_coord = LAT_COORD.copy()
+    lon_coord = LON_COORD.copy()
+    data = np.ma.masked_invalid(row[column_name])
+    cube = iris.cube.Cube(
+        data.reshape((1, 1, 1)),
+        dim_coords_and_dims=[(time_coord, 0), (lat_coord, 1), (lon_coord, 2)],
+        units='ppb',
+    )
+    return cube
+
+
+def _fix_coords(cube):
+    """Fix coordinates."""
+    utils.fix_dim_coordnames(cube)
+
+    return cube
+
+
+def _extract_variable(var_info, cmor_info, attrs, filepath, out_dir):
+    """Extract variable."""
+    var = cmor_info.short_name
+
+    # Load data
+    with warnings.catch_warnings():
+        warnings.filterwarnings(
+            action='ignore',
+            message="Skipping global attribute 'units': 'units' is not a "
+                    "permitted attribute",
+            category=UserWarning,
+            module='iris',
+        )
+        skiprows = 0
+        with open(filepath, 'r', encoding='utf-8') as csv:
+            for line in csv:
+                if line.startswith("#"):
+                    skiprows = skiprows + 1
+
+        data_frame = pd.read_csv(filepath, header=skiprows)
+
+        # Extract cube
+        cubes = iris.cube.CubeList()
+        for (_, row) in data_frame.iterrows():
+            cube = _get_cube(row, 'average')
+            cubes.append(cube)
+        cube = cubes.concatenate_cube()
+        cube.var_name = var
+
+    # Fix coordinates
+    cube = _fix_coords(cube)
+
+    # Fix variable metadata
+    cube = _fix_var_metadata(var_info, cmor_info, cube)
+
+    # Fix global metadata
+    utils.set_global_atts(cube, attrs)
+
+    # Save variable
+    utils.save_variable(
+        cube,
+        var,
+        out_dir,
+        attrs,
+        unlimited_dimensions=['time'],
+    )
+
+
+def cmorization(in_dir, out_dir, cfg, cfg_user, start_date, end_date):
+    """Cmorization func call."""
+    cmor_table = cfg['cmor_table']
+    glob_attrs = cfg['attributes']
+
+    # Run the cmorization
+    for (var, var_info) in cfg['variables'].items():
+        filepath = Path(in_dir) / var_info['filename']
+        logger.info("CMORizing variable '%s' from file %s", var, filepath)
+        glob_attrs['mip'] = var_info['mip']
+        cmor_info = cmor_table.get_variable(var_info['mip'], var)
+        _extract_variable(var_info, cmor_info, glob_attrs, filepath, out_dir)
diff --git a/esmvaltool/recipes/examples/recipe_check_obs.yml b/esmvaltool/recipes/examples/recipe_check_obs.yml
index 414b9e5b79..1686b268b5 100644
--- a/esmvaltool/recipes/examples/recipe_check_obs.yml
+++ b/esmvaltool/recipes/examples/recipe_check_obs.yml
@@ -646,6 +646,14 @@ diagnostics:
          type: reanaly, version: v2, start_year: 1871, end_year: 2012}
     scripts: null
 
+  NOAA-MBL-CH4:
+    description: NOAA marine boundary layer CH4 check
+    variables:
+      ch4s:
+    additional_datasets:
+      - {dataset: NOAA-MBL-CH4, project: OBS6, mip: Amon, type: atmos, version: 1.0, tier: 2,
+         start_year: 1983, end_year: 2023}
+    scripts: null
 
   NOAA-CIRES-20CR-V3:
     description: NOAA-CIRES-20CR-V3 check
diff --git a/esmvaltool/references/noaa-mbl-ch4.bibtex b/esmvaltool/references/noaa-mbl-ch4.bibtex
new file mode 100644
index 0000000000..e4c6a17cbd
--- /dev/null
+++ b/esmvaltool/references/noaa-mbl-ch4.bibtex
@@ -0,0 +1,9 @@
+@misc{noaa-mbl-ch4,
+        doi = {https://doi.org/10.15138/P8XG-AA10},
+	url = {https://gml.noaa.gov/ccgg/trends_ch4/},
+	year = 2023,
+        month = {jul},
+	author = {Lan, X., K.W. Thoning, and E.J. Dlugokencky},
+	title = {Trends in globally-averaged CH4, N2O, and SF6 determined from NOAA Global Monitoring Laboratory measurements. Version 2023-09},
+        howpublished = {via website https://gml.noaa.gov/ccgg/trends_ch4/, provided by the NOAA/GML, Boulder, Colorado, USA}
+}

From 89153c11eb723d4d2d26e9d4f3833bba4aafbe04 Mon Sep 17 00:00:00 2001
From: Manuel Schlund <32543114+schlunma@users.noreply.github.com>
Date: Fri, 3 Nov 2023 11:21:10 +0100
Subject: [PATCH 62/93] Added CMORizer for MOBO-DIC2004-2019 (#3297)

---
 doc/sphinx/source/input.rst                   |  2 +
 .../data/cmor_config/MOBO-DIC2004-2019.yml    | 19 ++++++
 esmvaltool/cmorizers/data/datasets.yml        |  9 ++-
 .../downloaders/datasets/mobo_dic2004_2019.py | 39 ++++++++++++
 .../formatters/datasets/mobo_dic2004_2019.py  | 17 ++++++
 .../data/formatters/datasets/mobo_dic_mpim.py | 60 +++++++++++++++++--
 .../recipes/examples/recipe_check_obs.yml     | 10 ++++
 .../references/mobo_dic2004_2019.bibtex       | 12 ++++
 8 files changed, 161 insertions(+), 7 deletions(-)
 create mode 100644 esmvaltool/cmorizers/data/cmor_config/MOBO-DIC2004-2019.yml
 create mode 100644 esmvaltool/cmorizers/data/downloaders/datasets/mobo_dic2004_2019.py
 create mode 100644 esmvaltool/cmorizers/data/formatters/datasets/mobo_dic2004_2019.py
 create mode 100644 esmvaltool/references/mobo_dic2004_2019.bibtex

diff --git a/doc/sphinx/source/input.rst b/doc/sphinx/source/input.rst
index 626bc82133..ed47c96857 100644
--- a/doc/sphinx/source/input.rst
+++ b/doc/sphinx/source/input.rst
@@ -367,6 +367,8 @@ A list of the datasets for which a CMORizers is available is provided in the fol
 +------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+
 | MOBO-DIC_MPIM                | dissic (Omon)                                                                                        |   2  | Python          |
 +------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+
+| MOBO-DIC2004-2019            | dissic (Omon)                                                                                        |   2  | Python          |
++------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+
 | MODIS                        | cliwi, clt, clwvi, iwpStderr, lwpStderr (Amon), od550aer (aero)                                      |   3  | NCL             |
 +------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+
 | MSWEP [#note1]_              | pr                                                                                                   |   3  | n/a             |
diff --git a/esmvaltool/cmorizers/data/cmor_config/MOBO-DIC2004-2019.yml b/esmvaltool/cmorizers/data/cmor_config/MOBO-DIC2004-2019.yml
new file mode 100644
index 0000000000..7e80dc6634
--- /dev/null
+++ b/esmvaltool/cmorizers/data/cmor_config/MOBO-DIC2004-2019.yml
@@ -0,0 +1,19 @@
+---
+# Common global attributes for Cmorizer output
+attributes:
+  dataset_id: MOBO-DIC2004-2019
+  version: '2.3'
+  tier: 2
+  modeling_realm: reanaly
+  project_id: OBS6
+  source: 'https://www.nodc.noaa.gov/archive/arc0211/0277099/2.3/data/0-data/'
+  reference: 'mobo_dic2004_2019'
+
+# Variables to cmorize
+variables:
+  dissic:
+    filename: MPI_MOBO-DIC_2004-2019_v2.nc
+    mip: Omon
+    raw_name: DIC
+    raw_units: '1e-6 mol kg-1'
+    comment: 'The original units of this variable are mumol/kg. To convert to the CMOR units mol/m3, we assume a constant sea water density of 1032 kg/m3, which is approximately the sea water density for T=4°C, salinity=35PSU, and p=100bar according to the UNESCO formula (UNESCO, 1981, Tenth report of the joint panel on oceanographic tables and standards, UNESCO Technical Papers in Marine Science, see https://www.wkcgroup.com/tools-room/seawater-density-calculator/ and https://link.springer.com/content/pdf/bbm:978-3-319-18908-6/1.pdf).'
diff --git a/esmvaltool/cmorizers/data/datasets.yml b/esmvaltool/cmorizers/data/datasets.yml
index 555d7bf512..49d92d12ca 100644
--- a/esmvaltool/cmorizers/data/datasets.yml
+++ b/esmvaltool/cmorizers/data/datasets.yml
@@ -873,6 +873,13 @@ datasets:
     info: |
       Download the file MOBO-DIC_MPIM_monthly_clim.nc
 
+  MOBO-DIC2004-2019:
+    tier: 2
+    source: https://www.nodc.noaa.gov/archive/arc0211/0277099/2.3/data/0-data/
+    last_access: 2023-10-09
+    info: |
+      Download the file MPI_MOBO-DIC_2004-2019_v2.nc
+
   MODIS:
     tier: 3
     source: https://ladsweb.modaps.eosdis.nasa.gov/search/order
@@ -1015,7 +1022,7 @@ datasets:
         miscSI-MO/pr_wtr.eatm.mon.mean.nc
         prsSI-MO/shum.mon.mean.nc
         miscMO/tcdc.eatm.mon.mean.nc
-        ntatFlxSI-MO/ulwrf.ntat.mon.mean.nc  
+        ntatFlxSI-MO/ulwrf.ntat.mon.mean.nc
         ntatFlxSI-MO/uswrf.ntat.mon.mean.nc
         ntatFlxSI-MO/csulf.ntat.mon.mean.nc
         ntatFlxSI-MO/csusf.ntat.mon.mean.nc
diff --git a/esmvaltool/cmorizers/data/downloaders/datasets/mobo_dic2004_2019.py b/esmvaltool/cmorizers/data/downloaders/datasets/mobo_dic2004_2019.py
new file mode 100644
index 0000000000..1299981811
--- /dev/null
+++ b/esmvaltool/cmorizers/data/downloaders/datasets/mobo_dic2004_2019.py
@@ -0,0 +1,39 @@
+"""Script to download MOBO-DIC2004-2019."""
+import logging
+
+from esmvaltool.cmorizers.data.downloaders.wget import WGetDownloader
+
+logger = logging.getLogger(__name__)
+
+
+def download_dataset(config, dataset, dataset_info, start_date, end_date,
+                     overwrite):
+    """Download dataset.
+
+    Parameters
+    ----------
+    config : dict
+        ESMValTool's user configuration
+    dataset : str
+        Name of the dataset
+    dataset_info : dict
+         Dataset information from the datasets.yml file
+    start_date : datetime
+        Start of the interval to download
+    end_date : datetime
+        End of the interval to download
+    overwrite : bool
+        Overwrite already downloaded files
+    """
+    downloader = WGetDownloader(
+        config=config,
+        dataset=dataset,
+        dataset_info=dataset_info,
+        overwrite=overwrite,
+    )
+
+    downloader.download_file(
+        "https://www.nodc.noaa.gov/archive/arc0211/0277099/2.3/data/0-data/"
+        "MPI_MOBO-DIC_2004-2019_v2.nc",
+        wget_options=[],
+    )
diff --git a/esmvaltool/cmorizers/data/formatters/datasets/mobo_dic2004_2019.py b/esmvaltool/cmorizers/data/formatters/datasets/mobo_dic2004_2019.py
new file mode 100644
index 0000000000..570e20f715
--- /dev/null
+++ b/esmvaltool/cmorizers/data/formatters/datasets/mobo_dic2004_2019.py
@@ -0,0 +1,17 @@
+"""ESMValTool CMORizer for MOBO-DIC2004-2019 data.
+
+Tier
+    Tier 2: other freely-available dataset.
+
+Source
+    https://www.nodc.noaa.gov/archive/arc0211/0277099/2.3/data/0-data/
+
+Last access
+    20231009
+
+Download and processing instructions
+    Download the file MPI_MOBO-DIC_2004-2019_v2.nc
+
+"""
+
+from .mobo_dic_mpim import cmorization  # noqa
diff --git a/esmvaltool/cmorizers/data/formatters/datasets/mobo_dic_mpim.py b/esmvaltool/cmorizers/data/formatters/datasets/mobo_dic_mpim.py
index 68884c22ae..9ae096104f 100644
--- a/esmvaltool/cmorizers/data/formatters/datasets/mobo_dic_mpim.py
+++ b/esmvaltool/cmorizers/data/formatters/datasets/mobo_dic_mpim.py
@@ -20,6 +20,7 @@
 from pathlib import Path
 
 import iris
+import numpy as np
 from cf_units import Unit
 from dask import array as da
 from iris import NameConstraint
@@ -30,6 +31,9 @@
 logger = logging.getLogger(__name__)
 
 
+TIME_UNITS = Unit('days since 1950-01-01 00:00:00', calendar='standard')
+
+
 def _callback_fix_missing_value(cube, field, _):
     """Create masked array from missing_value."""
     if hasattr(field.cf_data, 'missing_value'):
@@ -40,20 +44,18 @@ def _callback_fix_missing_value(cube, field, _):
 
 def _fix_climatological_time(cube):
     """Fix climatology coordinate."""
-    time_units = Unit('days since 1950-01-01 00:00:00', calendar='standard')
-
     # Following the doc the covered time period of the climatology is
     # January 2004 to December 2017 (Use 2011 as the "mean" year). See
     # https://www.ncei.noaa.gov/access/metadata/landing-page/bin/
     # iso?id=gov.noaa.nodc%3A0221526
-    time_points = time_units.date2num(
+    time_points = TIME_UNITS.date2num(
         [datetime(2011, m, 15) for m in range(1, 13)]
     )
     time_bounds = [
         [datetime(2004, m, 1), datetime(2017, m + 1, 1)] for m in range(1, 12)
     ]
     time_bounds.append([datetime(2004, 12, 1), datetime(2018, 1, 1)])
-    time_bounds = time_units.date2num(time_bounds)
+    time_bounds = TIME_UNITS.date2num(time_bounds)
 
     # Add new time coordinate to cube
     time_coord = DimCoord(
@@ -62,7 +64,7 @@ def _fix_climatological_time(cube):
         standard_name='time',
         long_name='time',
         var_name='time',
-        units=time_units,
+        units=TIME_UNITS,
         climatological=True,
     )
     cube.remove_coord('month of the year')
@@ -73,6 +75,49 @@ def _fix_climatological_time(cube):
     cube.add_cell_method(CellMethod('mean over years', coords=time_coord))
 
 
+def _fix_time(cube):
+    """Fix time coordinate."""
+    julian_day_coord = cube.coord('Julian Day')
+
+    # Calculate bounds of new time coordinate
+    # print(str(julian_day_coord.units))
+    datetime_base = datetime.strptime(
+        str(julian_day_coord.units).partition(' since ')[2],
+        '%Y-%m-%d %H:%M:%S',
+    )
+    base_year = datetime_base.year
+    base_month = datetime_base.month
+    all_months = list(julian_day_coord.points.astype(int)) + [
+        julian_day_coord.points.astype(int).max() + 1  # 1 more month for bnds
+    ]
+    bounds_datetimes = [
+        datetime(base_year + (m - 1) // 12, base_month + (m - 1) % 12, 1)
+        for m in all_months
+    ]
+    time_bounds = np.stack(
+        (
+            TIME_UNITS.date2num(bounds_datetimes[:-1]),
+            TIME_UNITS.date2num(bounds_datetimes[1:]),
+        ),
+        axis=-1,
+    )
+
+    # Calculate time points as mean of bounds
+    time_points = np.mean(time_bounds, axis=1)
+
+    # Add new time coordinate to cube
+    time_coord = DimCoord(
+        time_points,
+        bounds=time_bounds,
+        standard_name='time',
+        long_name='time',
+        var_name='time',
+        units=TIME_UNITS,
+    )
+    cube.remove_coord('Julian Day')
+    cube.add_dim_coord(time_coord, 0)
+
+
 def _fix_var_metadata(var_info, cmor_info, cube):
     """Fix variable metadata.
 
@@ -121,7 +166,10 @@ def _extract_variable(var_info, cmor_info, attrs, filepath, out_dir):
     _fix_var_metadata(var_info, cmor_info, cube)
 
     # Fix coordinates
-    _fix_climatological_time(cube)
+    if cube.coords('month of the year'):  # MOBO-DIC_MPIM
+        _fix_climatological_time(cube)
+    elif cube.coords('Julian Day'):  # MOBO-DIC2004-2019
+        _fix_time(cube)
     cube.coord('depth').units = 'm'
     utils.fix_coords(cube, overwrite_time_bounds=False)
 
diff --git a/esmvaltool/recipes/examples/recipe_check_obs.yml b/esmvaltool/recipes/examples/recipe_check_obs.yml
index 1686b268b5..9a9e080b52 100644
--- a/esmvaltool/recipes/examples/recipe_check_obs.yml
+++ b/esmvaltool/recipes/examples/recipe_check_obs.yml
@@ -552,6 +552,16 @@ diagnostics:
     scripts: null
 
 
+  MOBO-DIC2004-2019:
+    description: MOBO-DIC2004-2019 check
+    variables:
+      dissic:
+    additional_datasets:
+      - {dataset: MOBO-DIC2004-2019, project: OBS6, mip: Omon, tier: 2,
+         type: reanaly, version: '2.3', start_year: 2004, end_year: 2019}
+    scripts: null
+
+
   NCEP-NCAR-R1:
     description: NCEP-NCAR-R1 check
     variables:
diff --git a/esmvaltool/references/mobo_dic2004_2019.bibtex b/esmvaltool/references/mobo_dic2004_2019.bibtex
new file mode 100644
index 0000000000..928fc33afd
--- /dev/null
+++ b/esmvaltool/references/mobo_dic2004_2019.bibtex
@@ -0,0 +1,12 @@
+@article{mobo_dic2004_2019,
+  doi = {10.1029/2022gb007677},
+  url = {https://doi.org/10.1029/2022gb007677},
+  year = {2023},
+  month = may,
+  publisher = {American Geophysical Union ({AGU})},
+  volume = {37},
+  number = {5},
+  author = {L. Keppler and P. Landschützer and S. K. Lauvset and N. Gruber},
+  title = {Recent Trends and Variability in the Oceanic Storage of Dissolved Inorganic Carbon},
+  journal = {Global Biogeochemical Cycles}
+}

From 0f6b00eb3ec58dc3e9f3cb6460802d002a6ce43b Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Fri, 3 Nov 2023 17:01:59 +0000
Subject: [PATCH 63/93] [Condalock] Update Linux condalock file (#3406)

Co-authored-by: valeriupredoi <valeriupredoi@users.noreply.github.com>
---
 conda-linux-64.lock | 17 +++++++++--------
 1 file changed, 9 insertions(+), 8 deletions(-)

diff --git a/conda-linux-64.lock b/conda-linux-64.lock
index 3873ea2feb..82bef1df0b 100644
--- a/conda-linux-64.lock
+++ b/conda-linux-64.lock
@@ -30,7 +30,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-13.2.0-h807b86a_2.cond
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 https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-h7f98852_4.tar.bz2#a1fd65c7ccbf10880423d82bca54eb54
-https://conda.anaconda.org/conda-forge/linux-64/c-ares-1.20.1-hd590300_1.conda#2facbaf5ee1a56967aecaee89799160e
+https://conda.anaconda.org/conda-forge/linux-64/c-ares-1.21.0-hd590300_0.conda#c06fa0440048270817b9e3142cc661bf
 https://conda.anaconda.org/conda-forge/linux-64/charls-2.4.2-h59595ed_0.conda#4336bd67920dd504cd8c6761d6a99645
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@@ -61,6 +61,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libiconv-1.17-h166bdaf_0.tar.bz2
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 https://conda.anaconda.org/conda-forge/linux-64/libnuma-2.0.16-h0b41bf4_1.conda#28bfe2cb11357ccc5be21101a6b7ce86
+https://conda.anaconda.org/conda-forge/linux-64/libopenlibm4-0.8.1-hd590300_1.conda#e6af610e01d04927a5060c95ce4e0875
 https://conda.anaconda.org/conda-forge/linux-64/libsanitizer-13.2.0-h7e041cc_2.conda#aa27066e2dcef56db7bc674f2230b6c9
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 https://conda.anaconda.org/conda-forge/linux-64/libtool-2.4.7-h27087fc_0.conda#f204c8ba400ec475452737094fb81d52
@@ -78,7 +79,6 @@ https://conda.anaconda.org/conda-forge/linux-64/metis-5.1.0-h59595ed_1007.conda#
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 https://conda.anaconda.org/conda-forge/linux-64/nspr-4.35-h27087fc_0.conda#da0ec11a6454ae19bff5b02ed881a2b1
-https://conda.anaconda.org/conda-forge/linux-64/openlibm-0.8.1-h7f98852_0.tar.bz2#ba0c56761f2380babaa783b2a37b4d08
 https://conda.anaconda.org/conda-forge/linux-64/openssl-3.1.4-hd590300_0.conda#412ba6938c3e2abaca8b1129ea82e238
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 https://conda.anaconda.org/conda-forge/linux-64/pixman-0.42.2-h59595ed_0.conda#700edd63ccd5fc66b70b1c028cea9a68
@@ -124,7 +124,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libnghttp2-1.55.1-h47da74e_0.con
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-https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.43.2-h2797004_0.conda#4b441a1ee22397d5a27dc1126b849edd
+https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.44.0-h2797004_0.conda#b58e6816d137f3aabf77d341dd5d732b
 https://conda.anaconda.org/conda-forge/linux-64/libssh2-1.11.0-h0841786_0.conda#1f5a58e686b13bcfde88b93f547d23fe
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 https://conda.anaconda.org/conda-forge/linux-64/libxcb-1.15-h0b41bf4_0.conda#33277193f5b92bad9fdd230eb700929c
@@ -132,6 +132,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libxgboost-1.7.6-cuda118_h4159b1
 https://conda.anaconda.org/conda-forge/linux-64/libxml2-2.11.5-h0d562d8_0.conda#558ab736404275d7df61c473c1af35aa
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 https://conda.anaconda.org/conda-forge/linux-64/mpfr-4.2.1-h9458935_0.conda#4c28f3210b30250037a4a627eeee9e0f
+https://conda.anaconda.org/conda-forge/linux-64/openlibm-0.8.1-hd590300_1.conda#6eba22eb06d69e53d0ca01eef42bc675
 https://conda.anaconda.org/conda-forge/linux-64/pcre2-10.40-hc3806b6_0.tar.bz2#69e2c796349cd9b273890bee0febfe1b
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 https://conda.anaconda.org/conda-forge/linux-64/readline-8.2-h8228510_1.conda#47d31b792659ce70f470b5c82fdfb7a4
@@ -169,7 +170,7 @@ https://conda.anaconda.org/conda-forge/linux-64/nss-3.94-h1d7d5a4_0.conda#7caef7
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 https://conda.anaconda.org/conda-forge/linux-64/python-3.11.6-hab00c5b_0_cpython.conda#b0dfbe2fcbfdb097d321bfd50ecddab1
-https://conda.anaconda.org/conda-forge/linux-64/sqlite-3.43.2-h2c6b66d_0.conda#c37b95bcd6c6833dacfd5df0ae2f4303
+https://conda.anaconda.org/conda-forge/linux-64/sqlite-3.44.0-h2c6b66d_0.conda#df56c636df4a98990462d66ac7be2330
 https://conda.anaconda.org/conda-forge/linux-64/tktable-2.10-h0c5db8f_5.conda#9464044754ea25557a9c93f0327d90a6
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 https://conda.anaconda.org/conda-forge/linux-64/xorg-libx11-1.8.7-h8ee46fc_0.conda#49e482d882669206653b095f5206c05b
@@ -186,7 +187,7 @@ https://conda.anaconda.org/conda-forge/linux-64/brotli-1.0.9-h166bdaf_9.conda#46
 https://conda.anaconda.org/conda-forge/linux-64/brotli-python-1.0.9-py311ha362b79_9.conda#ced5340f5dc6cff43a80deac8d0e398f
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-https://conda.anaconda.org/conda-forge/noarch/charset-normalizer-3.3.1-pyhd8ed1ab_0.conda#985378f74689fccce52f158027bd9acd
+https://conda.anaconda.org/conda-forge/noarch/charset-normalizer-3.3.2-pyhd8ed1ab_0.conda#7f4a9e3fcff3f6356ae99244a014da6a
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@@ -359,7 +360,7 @@ https://conda.anaconda.org/conda-forge/noarch/python-dateutil-2.8.2-pyhd8ed1ab_0
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-https://conda.anaconda.org/conda-forge/linux-64/ruamel.yaml-0.18.3-py311h459d7ec_0.conda#a4457243c80f077cf2b38c1c56096f57
+https://conda.anaconda.org/conda-forge/linux-64/ruamel.yaml-0.18.4-py311h459d7ec_0.conda#a73b5092b7b7f3dfa58b02179d7fed8e
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@@ -376,7 +377,7 @@ https://conda.anaconda.org/conda-forge/linux-64/arpack-3.7.0-hdefa2d7_2.tar.bz2#
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-https://conda.anaconda.org/conda-forge/noarch/django-4.2.6-pyhd8ed1ab_0.conda#bebc7fbd0b86a4e28a931c306cd5324e
+https://conda.anaconda.org/conda-forge/noarch/django-4.2.7-pyhd8ed1ab_0.conda#107fbbd296283091c717acd51a3a87fd
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@@ -458,7 +459,7 @@ https://conda.anaconda.org/conda-forge/linux-64/gdal-3.7.0-py311h281082f_2.conda
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+https://conda.anaconda.org/conda-forge/linux-64/matplotlib-base-3.8.1-py311h54ef318_0.conda#201fdabdb86bb8fb6e99fa3f0dab8122
 https://conda.anaconda.org/conda-forge/noarch/myproxyclient-2.1.0-pyhd8ed1ab_2.tar.bz2#363b0816e411feb0df925d4f224f026a
 https://conda.anaconda.org/conda-forge/noarch/nbformat-5.9.2-pyhd8ed1ab_0.conda#61ba076de6530d9301a0053b02f093d2
 https://conda.anaconda.org/conda-forge/linux-64/netcdf4-1.6.4-nompi_py311h4d7c953_100.conda#c03492d0342e512e58aa2d6c5fdaaa91

From 89fc56534f9ba5ec68a037551653587dc453ff44 Mon Sep 17 00:00:00 2001
From: Alistair Sellar <alistair.sellar@metoffice.gov.uk>
Date: Mon, 6 Nov 2023 09:18:36 +0000
Subject: [PATCH 64/93] Enhance provenance documentation (#3305)

---
 doc/sphinx/source/community/diagnostic.rst    | 55 ++++++++++++-------
 .../diag_scripts/examples/diagnostic.py       |  3 +
 2 files changed, 39 insertions(+), 19 deletions(-)

diff --git a/doc/sphinx/source/community/diagnostic.rst b/doc/sphinx/source/community/diagnostic.rst
index 641a2da892..285815f7cf 100644
--- a/doc/sphinx/source/community/diagnostic.rst
+++ b/doc/sphinx/source/community/diagnostic.rst
@@ -179,6 +179,10 @@ and finally it will store provenance information. Provenance information is stor
 and provided that the provenance tree is small, also plotted in an SVG file for
 human inspection.
 In addition to provenance information, a caption is also added to the plots.
+
+Provenance information from the recipe is automatically recorded by ESMValCore, whereas
+diagnostic scripts must include code specifically to record provenance. See below for 
+documentation of provenance attributes that can be included in a recipe.
 When contributing a diagnostic, please make sure it records the provenance,
 and that no warnings related to provenance are generated when running the recipe.
 To allow the ESMValCore to keep track of provenance (e.g. which input files
@@ -233,20 +237,25 @@ Arbitrarily named other items are also supported.
 Please see the (installed version of the) file
 `esmvaltool/config-references.yml <https://github.com/ESMValGroup/ESMValTool/blob/main/esmvaltool/config-references.yml>`_
 for all available information on each item, see :ref:`esmvalcore:config-ref` for
-an introduction.
-In this file, the information is written in the form of ``key: value``.
-Note that we add the keys to the diagnostics.
-The keys will automatically be replaced by their values in the final provenance records.
-For example, in the ``config-references.yml`` there is a category for types of the plots:
+an introduction. It is also possible to add custom provenance information by adding items to each category in this file.
+In this file, the information is written in the form
+
+.. code-block:: console
+
+  key:
+    value: description
+
+for example
 
 .. code-block:: console
 
   plot_types:
     errorbar: error bar plot
 
-In the diagnostics, we add the key as:
-:code:`plot_types: [errorbar]`
-It is also possible to add custom provenance information by adding items to each category in this file.
+To use these items, include them in the provenance record dictionary in the form 
+:code:`key: [value]`
+i.e. for the example above as
+:code:`'plot_types': ['errorbar']`.
 
 In order to communicate with the diagnostic script, two interfaces have been defined,
 which are described in the `ESMValCore documentation <https://docs.esmvaltool.org/projects/esmvalcore/en/latest/interfaces.html>`_.
@@ -258,7 +267,7 @@ see the instructions and examples below on how to add provenance information:
 
 Recording provenance in a Python diagnostic script
 --------------------------------------------------
-Always use :meth:`esmvaltool.diag_scripts.shared.run_diagnostic` at the end of your script:
+Always use :func:`esmvaltool.diag_scripts.shared.run_diagnostic` at the end of your script:
 
 .. code-block:: python
 
@@ -266,16 +275,9 @@ Always use :meth:`esmvaltool.diag_scripts.shared.run_diagnostic` at the end of y
     with run_diagnostic() as config:
         main(config)
 
-And make use of a :class:`esmvaltool.diag_scripts.shared.ProvenanceLogger` to log provenance:
-
-.. code-block:: python
-
-  with ProvenanceLogger(cfg) as provenance_logger:
-        provenance_logger.log(diagnostic_file, provenance_record)
-
-The ``diagnostic_file`` can be obtained using :class:`esmvaltool.diag_scripts.shared.get_diagnostic_filename`.
-
-The ``provenance_record`` is a dictionary of provenance items, for example:
+Create a ``provenance_record`` for each diagnostic file (i.e. image or data 
+file) that the diagnostic script outputs. The ``provenance_record`` is a 
+dictionary of provenance items, for example:
 
 .. code-block:: python
 
@@ -294,10 +296,25 @@ The ``provenance_record`` is a dictionary of provenance items, for example:
         'statistics': ['mean'],
       }
 
+To save a matplotlib figure, use the convenience function 
+:func:`esmvaltool.diag_scripts.shared.save_figure`. Similarly, to save Iris cubes use 
+:func:`esmvaltool.diag_scripts.shared.save_data`. Both of these functions take
+``provenance_record`` as an argument and log the provenance accordingly.
 Have a look at the example Python diagnostic in
 `esmvaltool/diag_scripts/examples/diagnostic.py <https://github.com/ESMValGroup/ESMValTool/blob/main/esmvaltool/diag_scripts/examples/diagnostic.py>`_
 for a complete example.
 
+For any other files created, you will need to make use of a 
+:class:`esmvaltool.diag_scripts.shared.ProvenanceLogger` to log provenance. Include the
+following code directly after the file is saved:
+
+.. code-block:: python
+
+  with ProvenanceLogger(cfg) as provenance_logger:
+        provenance_logger.log(diagnostic_file, provenance_record)
+
+The full path of a ``diagnostic_file`` can be obtained using :class:`esmvaltool.diag_scripts.shared.get_diagnostic_filename`.
+
 Recording provenance in an NCL diagnostic script
 ------------------------------------------------
 Always call the ``log_provenance`` procedure after plotting from your NCL diag_script:
diff --git a/esmvaltool/diag_scripts/examples/diagnostic.py b/esmvaltool/diag_scripts/examples/diagnostic.py
index 6ef63d13f1..a9e4f8667e 100644
--- a/esmvaltool/diag_scripts/examples/diagnostic.py
+++ b/esmvaltool/diag_scripts/examples/diagnostic.py
@@ -20,6 +20,9 @@
 
 def get_provenance_record(attributes, ancestor_files):
     """Create a provenance record describing the diagnostic data and plot."""
+    # Associated recipe uses contains a caption string with placeholders
+    # like {long_name} that are now populated from attributes dictionary.
+    # Note that for simple recipes, caption can be set here as a simple string
     caption = attributes['caption'].format(**attributes)
 
     record = {

From ec9fd78f952291c121794c663e4e5f3fa7a72c79 Mon Sep 17 00:00:00 2001
From: Valeriu Predoi <valeriu.predoi@gmail.com>
Date: Mon, 6 Nov 2023 14:34:54 +0000
Subject: [PATCH 65/93] [conda-lock] Updare conda lock file to use ESMValCore
 2.10 release candidate (RC) (#3407)

---
 conda-linux-64.lock | 28 ++++++++++++++--------------
 1 file changed, 14 insertions(+), 14 deletions(-)

diff --git a/conda-linux-64.lock b/conda-linux-64.lock
index 82bef1df0b..d920179e15 100644
--- a/conda-linux-64.lock
+++ b/conda-linux-64.lock
@@ -1,6 +1,6 @@
 # Generated by conda-lock.
 # platform: linux-64
-# input_hash: f47d35f9d83344217c0911cc8cede368892e578ba25206f3c774436c197445b3
+# input_hash: 27f8b0ad520a2e8cf3b93380288b4e9bdaaeafa07cffd2dc081bd3cbdb3fec11
 @EXPLICIT
 https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2#d7c89558ba9fa0495403155b64376d81
 https://conda.anaconda.org/conda-forge/linux-64/_py-xgboost-mutex-2.0-gpu_0.tar.bz2#7702188077361f43a4d61e64c694f850
@@ -38,7 +38,7 @@ https://conda.anaconda.org/conda-forge/linux-64/fribidi-1.0.10-h36c2ea0_0.tar.bz
 https://conda.anaconda.org/conda-forge/linux-64/geos-3.11.2-hcb278e6_0.conda#3b8e364995e3575e57960d29c1e5ab14
 https://conda.anaconda.org/conda-forge/linux-64/gettext-0.21.1-h27087fc_0.tar.bz2#14947d8770185e5153fdd04d4673ed37
 https://conda.anaconda.org/conda-forge/linux-64/gflags-2.2.2-he1b5a44_1004.tar.bz2#cddaf2c63ea4a5901cf09524c490ecdc
-https://conda.anaconda.org/conda-forge/linux-64/ghostscript-10.02.0-h59595ed_0.conda#8ab9369b573e62ddf9456f1fe4dfc39d
+https://conda.anaconda.org/conda-forge/linux-64/ghostscript-10.02.1-h59595ed_0.conda#3750ef83be92ff8de6e44da80d509847
 https://conda.anaconda.org/conda-forge/linux-64/giflib-5.2.1-h0b41bf4_3.conda#96f3b11872ef6fad973eac856cd2624f
 https://conda.anaconda.org/conda-forge/linux-64/gmp-6.2.1-h58526e2_0.tar.bz2#b94cf2db16066b242ebd26db2facbd56
 https://conda.anaconda.org/conda-forge/linux-64/graphite2-1.3.13-h58526e2_1001.tar.bz2#8c54672728e8ec6aa6db90cf2806d220
@@ -137,7 +137,7 @@ https://conda.anaconda.org/conda-forge/linux-64/pcre2-10.40-hc3806b6_0.tar.bz2#6
 https://conda.anaconda.org/conda-forge/linux-64/perl-5.32.1-4_hd590300_perl5.conda#3e785bff761095eb7f8676f4694bd1b1
 https://conda.anaconda.org/conda-forge/linux-64/readline-8.2-h8228510_1.conda#47d31b792659ce70f470b5c82fdfb7a4
 https://conda.anaconda.org/conda-forge/linux-64/s2n-1.3.46-h06160fa_0.conda#413d96a0b655c8f8aacc36473a2dbb04
-https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-h2797004_0.conda#513336054f884f95d9fd925748f41ef3
+https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_h4845f30_101.conda#d453b98d9c83e71da0741bb0ff4d76bc
 https://conda.anaconda.org/conda-forge/linux-64/ucx-1.14.1-h64cca9d_5.conda#39aa3b356d10d7e5add0c540945a0944
 https://conda.anaconda.org/conda-forge/linux-64/xorg-fixesproto-5.0-h7f98852_1002.tar.bz2#65ad6e1eb4aed2b0611855aff05e04f6
 https://conda.anaconda.org/conda-forge/linux-64/xorg-libsm-1.2.4-h7391055_0.conda#93ee23f12bc2e684548181256edd2cf6
@@ -149,7 +149,7 @@ https://conda.anaconda.org/conda-forge/linux-64/blosc-1.21.5-h0f2a231_0.conda#00
 https://conda.anaconda.org/conda-forge/linux-64/boost-cpp-1.78.0-h6582d0a_3.conda#d3c3c7698d0b878aab1b86db95407c8e
 https://conda.anaconda.org/conda-forge/linux-64/brotli-bin-1.0.9-h166bdaf_9.conda#d47dee1856d9cb955b8076eeff304a5b
 https://conda.anaconda.org/conda-forge/linux-64/bwidget-1.9.14-ha770c72_1.tar.bz2#5746d6202ba2abad4a4707f2a2462795
-https://conda.anaconda.org/conda-forge/linux-64/c-blosc2-2.10.5-hb4ffafa_0.conda#831974f6788127baf502fca9001a5fb4
+https://conda.anaconda.org/conda-forge/linux-64/c-blosc2-2.11.1-hb4ffafa_0.conda#c898b02b6ed79db692e6a85f7bdba176
 https://conda.anaconda.org/conda-forge/linux-64/fftw-3.3.10-nompi_hc118613_108.conda#6fa90698000b05dfe8ce6515794fe71a
 https://conda.anaconda.org/conda-forge/linux-64/freetype-2.12.1-h267a509_2.conda#9ae35c3d96db2c94ce0cef86efdfa2cb
 https://conda.anaconda.org/conda-forge/linux-64/gfortran_impl_linux-64-13.2.0-h76e1118_2.conda#4983e17132a8fac913475db6e7aba288
@@ -234,7 +234,7 @@ https://conda.anaconda.org/conda-forge/linux-64/lxml-4.9.3-py311h1a07684_1.conda
 https://conda.anaconda.org/conda-forge/linux-64/lz4-4.3.2-py311h38e4bf4_1.conda#f8e0b648d77bbe44d1fe8af8cc56a590
 https://conda.anaconda.org/conda-forge/linux-64/markupsafe-2.1.3-py311h459d7ec_1.conda#71120b5155a0c500826cf81536721a15
 https://conda.anaconda.org/conda-forge/noarch/mccabe-0.7.0-pyhd8ed1ab_0.tar.bz2#34fc335fc50eef0b5ea708f2b5f54e0c
-https://conda.anaconda.org/conda-forge/noarch/mistune-3.0.1-pyhd8ed1ab_0.conda#1dad8397c94e4de97a70de552a7dcf49
+https://conda.anaconda.org/conda-forge/noarch/mistune-3.0.2-pyhd8ed1ab_0.conda#5cbee699846772cc939bef23a0d524ed
 https://conda.anaconda.org/conda-forge/linux-64/msgpack-python-1.0.6-py311h9547e67_0.conda#e826b71bf3dc8c91ee097663e2bcface
 https://conda.anaconda.org/conda-forge/linux-64/multidict-6.0.4-py311h459d7ec_1.conda#3dc76316237c8f7e7231d61b76c62b7c
 https://conda.anaconda.org/conda-forge/noarch/munch-4.0.0-pyhd8ed1ab_0.conda#376b32e8f9d3eacbd625f37d39bd507d
@@ -264,7 +264,7 @@ https://conda.anaconda.org/conda-forge/linux-64/python-xxhash-3.4.1-py311h459d7e
 https://conda.anaconda.org/conda-forge/noarch/pytz-2023.3.post1-pyhd8ed1ab_0.conda#c93346b446cd08c169d843ae5fc0da97
 https://conda.anaconda.org/conda-forge/linux-64/pyyaml-6.0.1-py311h459d7ec_1.conda#52719a74ad130de8fb5d047dc91f247a
 https://conda.anaconda.org/conda-forge/linux-64/pyzmq-25.1.1-py311h34ded2d_2.conda#ea365280db99687905b4d76cf6a3568c
-https://conda.anaconda.org/conda-forge/linux-64/rpds-py-0.10.6-py311h46250e7_0.conda#b7237977dbca779aaaab65f42f5558d9
+https://conda.anaconda.org/conda-forge/linux-64/rpds-py-0.12.0-py311h46250e7_0.conda#1de71b7a1bef273d49132ffd90101b8d
 https://conda.anaconda.org/conda-forge/linux-64/ruamel.yaml.clib-0.2.7-py311h459d7ec_2.conda#56bc3fe5180c0b23e05c7a5708153ac7
 https://conda.anaconda.org/conda-forge/noarch/semver-3.0.2-pyhd8ed1ab_0.conda#5efb3fccda53974aed800b6d575f72ed
 https://conda.anaconda.org/conda-forge/noarch/setoptconf-tmp-0.3.1-pyhd8ed1ab_0.tar.bz2#af3e36d4effb85b9b9f93cd1db0963df
@@ -284,7 +284,7 @@ https://conda.anaconda.org/conda-forge/noarch/termcolor-2.3.0-pyhd8ed1ab_0.conda
 https://conda.anaconda.org/conda-forge/noarch/threadpoolctl-3.2.0-pyha21a80b_0.conda#978d03388b62173b8e6f79162cf52b86
 https://conda.anaconda.org/conda-forge/noarch/toml-0.10.2-pyhd8ed1ab_0.tar.bz2#f832c45a477c78bebd107098db465095
 https://conda.anaconda.org/conda-forge/noarch/tomli-2.0.1-pyhd8ed1ab_0.tar.bz2#5844808ffab9ebdb694585b50ba02a96
-https://conda.anaconda.org/conda-forge/noarch/tomlkit-0.12.1-pyha770c72_0.conda#62f5b331c53d73e2f6c4c130b53518a0
+https://conda.anaconda.org/conda-forge/noarch/tomlkit-0.12.2-pyha770c72_0.conda#495ddad84b81dde4ee1138dd59ef5805
 https://conda.anaconda.org/conda-forge/noarch/toolz-0.12.0-pyhd8ed1ab_0.tar.bz2#92facfec94bc02d6ccf42e7173831a36
 https://conda.anaconda.org/conda-forge/linux-64/tornado-6.3.3-py311h459d7ec_1.conda#a700fcb5cedd3e72d0c75d095c7a6eda
 https://conda.anaconda.org/conda-forge/noarch/traitlets-5.13.0-pyhd8ed1ab_0.conda#8a9953c15e1e5a7c1baddbbf4511a567
@@ -296,7 +296,7 @@ https://conda.anaconda.org/conda-forge/noarch/webencodings-0.5.1-pyhd8ed1ab_2.co
 https://conda.anaconda.org/conda-forge/noarch/webob-1.8.7-pyhd8ed1ab_0.tar.bz2#a8192f3585f341ea66c60c189580ac67
 https://conda.anaconda.org/conda-forge/noarch/wheel-0.41.3-pyhd8ed1ab_0.conda#3fc026b9c87d091c4b34a6c997324ae8
 https://conda.anaconda.org/conda-forge/linux-64/wrapt-1.15.0-py311h459d7ec_1.conda#f4d770a09066aaa313b5cc22c0f6e9d1
-https://conda.anaconda.org/conda-forge/noarch/xlsxwriter-3.1.7-pyhd8ed1ab_0.conda#57ed13683ed80362014f6499e27f7b05
+https://conda.anaconda.org/conda-forge/noarch/xlsxwriter-3.1.9-pyhd8ed1ab_0.conda#70e533db62a710ae216fdaccc4a983c8
 https://conda.anaconda.org/conda-forge/linux-64/xorg-libxext-1.3.4-h0b41bf4_2.conda#82b6df12252e6f32402b96dacc656fec
 https://conda.anaconda.org/conda-forge/linux-64/xorg-libxfixes-5.0.3-h7f98852_1004.tar.bz2#e9a21aa4d5e3e5f1aed71e8cefd46b6a
 https://conda.anaconda.org/conda-forge/linux-64/xorg-libxrender-0.9.11-hd590300_0.conda#ed67c36f215b310412b2af935bf3e530
@@ -326,7 +326,7 @@ https://conda.anaconda.org/conda-forge/linux-64/cytoolz-0.12.2-py311h459d7ec_1.c
 https://conda.anaconda.org/conda-forge/noarch/docformatter-1.7.5-pyhd8ed1ab_0.conda#3a941b6083e945aa87e739a9b85c82e9
 https://conda.anaconda.org/conda-forge/noarch/docrep-0.3.2-pyh44b312d_0.tar.bz2#235523955bc1bfb019d7ec8a2bb58f9a
 https://conda.anaconda.org/conda-forge/noarch/fire-0.5.0-pyhd8ed1ab_0.conda#9fd22aae8d2f319e80f68b295ab91d64
-https://conda.anaconda.org/conda-forge/linux-64/fonttools-4.43.1-py311h459d7ec_0.conda#ac995b680de3bdce2531c553b27dfe7e
+https://conda.anaconda.org/conda-forge/linux-64/fonttools-4.44.0-py311h459d7ec_0.conda#f12f4d7361178f94df1052d6b63fd868
 https://conda.anaconda.org/conda-forge/noarch/geopy-2.4.0-pyhd8ed1ab_0.conda#90faaa7eaeba3cc877074c0916efe30c
 https://conda.anaconda.org/conda-forge/noarch/gitdb-4.0.11-pyhd8ed1ab_0.conda#623b19f616f2ca0c261441067e18ae40
 https://conda.anaconda.org/conda-forge/linux-64/hdf5-1.14.0-nompi_hb72d44e_103.conda#975973a4350ab45ff1981fe535a12af5
@@ -360,7 +360,7 @@ https://conda.anaconda.org/conda-forge/noarch/python-dateutil-2.8.2-pyhd8ed1ab_0
 https://conda.anaconda.org/conda-forge/noarch/python-utils-3.8.1-pyhd8ed1ab_0.conda#4dc77041fea14c63ecea50ce0eb92873
 https://conda.anaconda.org/conda-forge/noarch/referencing-0.30.2-pyhd8ed1ab_0.conda#a33161b983172ba6ef69d5fc850650cd
 https://conda.anaconda.org/conda-forge/noarch/retrying-1.3.3-py_2.tar.bz2#a11f356d6f93b74b4a84e9501afd48b4
-https://conda.anaconda.org/conda-forge/linux-64/ruamel.yaml-0.18.4-py311h459d7ec_0.conda#a73b5092b7b7f3dfa58b02179d7fed8e
+https://conda.anaconda.org/conda-forge/linux-64/ruamel.yaml-0.18.5-py311h459d7ec_0.conda#1101ec27377f8e45d8431a5f21d744f1
 https://conda.anaconda.org/conda-forge/noarch/tinycss2-1.2.1-pyhd8ed1ab_0.tar.bz2#7234c9eefff659501cd2fe0d2ede4d48
 https://conda.anaconda.org/conda-forge/noarch/tqdm-4.66.1-pyhd8ed1ab_0.conda#03c97908b976498dcae97eb4e4f3149c
 https://conda.anaconda.org/conda-forge/noarch/typing-extensions-4.8.0-hd8ed1ab_0.conda#384462e63262a527bda564fa2d9126c0
@@ -417,7 +417,7 @@ https://conda.anaconda.org/conda-forge/noarch/cdsapi-0.6.1-pyhd8ed1ab_0.conda#45
 https://conda.anaconda.org/conda-forge/linux-64/cftime-1.6.3-py311h1f0f07a_0.conda#b7e6d52b39e199238c3400cafaabafb3
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 https://conda.anaconda.org/conda-forge/noarch/colorspacious-1.1.2-pyh24bf2e0_0.tar.bz2#b73afa0d009a51cabd3ec99c4d2ef4f3
-https://conda.anaconda.org/conda-forge/linux-64/contourpy-1.1.1-py311h9547e67_1.conda#52d3de443952d33c5cee6b24b172ce96
+https://conda.anaconda.org/conda-forge/linux-64/contourpy-1.2.0-py311h9547e67_0.conda#40828c5b36ef52433e21f89943e09f33
 https://conda.anaconda.org/conda-forge/noarch/dask-core-2023.10.1-pyhd8ed1ab_0.conda#cf1f26a9e21311f10cfe9dbf0e0d99bc
 https://conda.anaconda.org/conda-forge/noarch/eofs-1.4.0-py_0.tar.bz2#6e166cd37cfeadefcfca1ffe00f222bb
 https://conda.anaconda.org/conda-forge/noarch/flake8-polyfill-1.0.2-py_0.tar.bz2#a53db35e3d07f0af2eccd59c2a00bffe
@@ -476,7 +476,7 @@ https://conda.anaconda.org/conda-forge/noarch/tifffile-2023.9.26-pyhd8ed1ab_0.co
 https://conda.anaconda.org/conda-forge/noarch/xarray-2023.10.1-pyhd8ed1ab_0.conda#9b20e5d68eea6878a0a6fc57a3043889
 https://conda.anaconda.org/conda-forge/noarch/zarr-2.16.1-pyhd8ed1ab_0.conda#59ec835edbee50266b7bdbadab7ba335
 https://conda.anaconda.org/conda-forge/linux-64/cartopy-0.22.0-py311h320fe9a_1.conda#10d1806e20da040c58c36deddf51c70c
-https://conda.anaconda.org/conda-forge/noarch/cf_xarray-0.8.4-pyhd8ed1ab_0.conda#18472f8f9452f962fe0bcb1b8134b494
+https://conda.anaconda.org/conda-forge/noarch/cf_xarray-0.8.6-pyhd8ed1ab_0.conda#2e33e3bdf2b1a79989ad792ac22104d3
 https://conda.anaconda.org/conda-forge/noarch/cmocean-3.0.3-pyhd8ed1ab_0.conda#eec7df83d725696d32c7bf99aff21d82
 https://conda.anaconda.org/conda-forge/noarch/dask-jobqueue-0.8.2-pyhd8ed1ab_0.conda#cc344a296a41369bcb05f7216661cec8
 https://conda.anaconda.org/conda-forge/noarch/esgf-pyclient-0.3.1-pyh1a96a4e_2.tar.bz2#64068564a9c2932bf30e9b4ec567927d
@@ -623,7 +623,7 @@ https://conda.anaconda.org/conda-forge/noarch/r-scales-1.2.1-r41hc72bb7e_1.tar.b
 https://conda.anaconda.org/conda-forge/linux-64/r-specsverification-0.5_3-r41ha503ecb_3.conda#2bc51f0d44b98092ba57cf2f8671b490
 https://conda.anaconda.org/conda-forge/linux-64/r-splancs-2.01_43-r41h8da6f51_1.tar.bz2#3a6aad0706541141d10e3b514467a080
 https://conda.anaconda.org/conda-forge/linux-64/r-vctrs-0.6.2-r41ha503ecb_0.conda#1f7610a1863648cab254a9f85bd29dcd
-https://conda.anaconda.org/conda-forge/noarch/iris-esmf-regrid-0.8.0-pyhd8ed1ab_0.conda#56e85460d22fa7d4fb06300f785dd1e1
+https://conda.anaconda.org/conda-forge/noarch/iris-esmf-regrid-0.9.0-pyhd8ed1ab_0.conda#570f2c6e387fd6dac5356a5152f91b3f
 https://conda.anaconda.org/conda-forge/noarch/nbconvert-7.10.0-pyhd8ed1ab_0.conda#800568b9c39cfd87a2a6a9a0488ea265
 https://conda.anaconda.org/conda-forge/noarch/r-cyclocomp-1.1.0-r41hc72bb7e_1005.tar.bz2#800e1da5bf774be48934b8865dd78d33
 https://conda.anaconda.org/conda-forge/noarch/r-gridextra-2.3-r41hc72bb7e_1004.tar.bz2#71ebed7e976df735ff3443bb88bd154f
@@ -634,7 +634,7 @@ https://conda.anaconda.org/conda-forge/noarch/r-pillar-1.9.0-r41hc72bb7e_0.conda
 https://conda.anaconda.org/conda-forge/noarch/r-pkgload-1.3.2-r41hc72bb7e_0.tar.bz2#e23a1a8420ab52056d86a6f9691d23fa
 https://conda.anaconda.org/conda-forge/linux-64/r-purrr-1.0.1-r41h133d619_0.conda#d7404238cac0da3c97dc08503d116a2f
 https://conda.anaconda.org/conda-forge/noarch/r-r.cache-0.16.0-r41hc72bb7e_1.tar.bz2#aef451160d655cc630d8038d934dced3
-https://conda.anaconda.org/conda-forge/noarch/esmvalcore-2.9.0-pyhd8ed1ab_0.conda#1f80c9bce2737630da4e71332c9d39c1
+https://conda.anaconda.org/conda-forge/label/esmvalcore_rc/noarch/esmvalcore-2.10.0rc1-pyh39db41b_0.conda#b973ee8c35712a7d21830ed06bdbc42d
 https://conda.anaconda.org/conda-forge/noarch/r-climprojdiags-0.3.2-r41hc72bb7e_0.conda#9922b863cd10035cbb75e3c2edae64a7
 https://conda.anaconda.org/conda-forge/linux-64/r-tibble-3.2.1-r41h133d619_1.conda#3ae9b78fb1d8a44deed24a27cce33ebf
 https://conda.anaconda.org/conda-forge/noarch/r-ggplot2-3.4.2-r41hc72bb7e_0.conda#c2b04f4ff351d84bf51fd5a77b5c9b6c

From 9293c00c6a2507906d44e41752333913b365c019 Mon Sep 17 00:00:00 2001
From: Manuel Schlund <32543114+schlunma@users.noreply.github.com>
Date: Wed, 8 Nov 2023 08:43:59 +0100
Subject: [PATCH 66/93] Recipe changes for new statistics preprocessors
 (percentiles) (#3351)

Co-authored-by: Klaus Zimmermann <klaus.zimmermann@smhi.se>
---
 .../recipes/examples/recipe_preprocessor_test.yml      | 10 ++++++++--
 esmvaltool/recipes/recipe_kcs.yml                      |  8 ++++++--
 2 files changed, 14 insertions(+), 4 deletions(-)

diff --git a/esmvaltool/recipes/examples/recipe_preprocessor_test.yml b/esmvaltool/recipes/examples/recipe_preprocessor_test.yml
index df97678ac7..cce4e89df6 100644
--- a/esmvaltool/recipes/examples/recipe_preprocessor_test.yml
+++ b/esmvaltool/recipes/examples/recipe_preprocessor_test.yml
@@ -75,10 +75,16 @@ preprocessors:
     multi_model_statistics: false
 
 
-  # Simple ensemble mean and median for multiple models
+  # Simple ensemble mean, median, and percentiles for multiple models
   preprocessor_5:
     ensemble_statistics:
-      statistics: [mean, median]
+      statistics:
+        - mean
+        - median
+        - operator: percentile
+          percent: 5
+        - operator: percentile
+          percent: 95
       exclude: [GFDL-ESM2G]
 
   # Calculate ensemble means, then multi-model mean
diff --git a/esmvaltool/recipes/recipe_kcs.yml b/esmvaltool/recipes/recipe_kcs.yml
index cbb7e85592..6eebb2c0e6 100644
--- a/esmvaltool/recipes/recipe_kcs.yml
+++ b/esmvaltool/recipes/recipe_kcs.yml
@@ -64,7 +64,11 @@ preprocessors:
       standardize: false
     multi_model_statistics:
       span: full
-      statistics: [p10, p90]
+      statistics:
+        - operator: percentile
+          percent: 10
+        - operator: percentile
+          percent: 90
   preprocessor_local: &extract_NL
     extract_point:
       longitude: 6.25
@@ -91,7 +95,7 @@ diagnostics:
       global_matching:
         script: kcs/global_matching.py
         scenario_years: [2050, 2085]
-        scenario_percentiles: [P10, P90]
+        scenario_percentiles: [Percentile10, Percentile90]
 
   local_resampling:
     description: >

From 2f08df266a38cdbc131d484779cbd4012d430f7a Mon Sep 17 00:00:00 2001
From: Romain Beucher <romain.beucher@anu.edu.au>
Date: Fri, 10 Nov 2023 00:33:53 +1100
Subject: [PATCH 67/93] Update GPCP dataset name in recipe_quantilebias to
 align with ESGF (#3330)

Co-authored-by: Bouwe Andela <bouweandela@gmail.com>
---
 esmvaltool/recipes/recipe_quantilebias.yml | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/esmvaltool/recipes/recipe_quantilebias.yml b/esmvaltool/recipes/recipe_quantilebias.yml
index 57eee9d05e..2da81b5960 100644
--- a/esmvaltool/recipes/recipe_quantilebias.yml
+++ b/esmvaltool/recipes/recipe_quantilebias.yml
@@ -20,8 +20,8 @@ documentation:
     - c3s-magic
 
 datasets:
-   - {dataset: CanESM2, project: CMIP5, exp: historical, ensemble: r1i1p1, start_year: 1979, end_year: 2005}
-   - {dataset: GPCP-SG, project: obs4MIPs, level: L3, version: v2.3, tier: 1, start_year: 1979, end_year: 2005}
+  - {dataset: CanESM2, project: CMIP5, exp: historical, ensemble: r1i1p1, start_year: 1979, end_year: 2005}
+  - {dataset: GPCP-V2.3, project: obs4MIPs, level: L3, tier: 1, start_year: 1979, end_year: 2005}
 
 preprocessors:
   mask_regrid_preproc:
@@ -37,7 +37,7 @@ diagnostics:
     variables:
       pr:
         preprocessor: mask_regrid_preproc
-        reference_dataset: "GPCP-SG"
+        reference_dataset: "GPCP-V2.3"
         mip: Amon
 
     scripts:

From 1b435c5d096f0c85171def1440068c0ceb00f11d Mon Sep 17 00:00:00 2001
From: Romain Beucher <romain.beucher@anu.edu.au>
Date: Fri, 10 Nov 2023 00:38:09 +1100
Subject: [PATCH 68/93] Update obs4MIPs names to ESGF's in Schlunder20esd
 recipe (#3329)

Co-authored-by: Bouwe Andela <bouweandela@gmail.com>
---
 esmvaltool/recipes/recipe_schlund20esd.yml | 30 +++++++++++-----------
 1 file changed, 15 insertions(+), 15 deletions(-)

diff --git a/esmvaltool/recipes/recipe_schlund20esd.yml b/esmvaltool/recipes/recipe_schlund20esd.yml
index 28d9e83375..041ae07e41 100644
--- a/esmvaltool/recipes/recipe_schlund20esd.yml
+++ b/esmvaltool/recipes/recipe_schlund20esd.yml
@@ -858,9 +858,9 @@ diagnostics:
         mip: Amon
         start_year: 1986
         end_year: 2005
-        reference_dataset: GPCP-SG
+        reference_dataset: GPCP-V2.2
         additional_datasets:
-          - {dataset: GPCP-SG, project: obs4MIPs, level: L3, version: v2.2, tier: 1}
+          - {dataset: GPCP-V2.2, project: obs4MIPs, level: L3, tier: 1}
     additional_datasets:
       - {dataset: ACCESS1-0}
       - {dataset: ACCESS1-3}
@@ -919,9 +919,9 @@ diagnostics:
         mip: Amon
         start_year: 1986
         end_year: 2005
-        reference_dataset: GPCP-SG
+        reference_dataset: GPCP-V2.2
         additional_datasets:
-          - {dataset: GPCP-SG, project: obs4MIPs, level: L3, version: v2.2, tier: 1}
+          - {dataset: GPCP-V2.2, project: obs4MIPs, level: L3, tier: 1}
     additional_datasets:
       - {dataset: ACCESS-CM2,      ensemble: r1i1p1f1, grid: gn, institute: CSIRO-ARCCSS}
       - {dataset: ACCESS-ESM1-5,   ensemble: r1i1p1f1, grid: gn}
@@ -994,9 +994,9 @@ diagnostics:
         mip: Amon
         start_year: 2003
         end_year: 2005
-        reference_dataset: AIRS
+        reference_dataset: AIRS-2-1
         additional_datasets:
-          - {dataset: AIRS, project: obs4MIPs, level: L3, version: RetStd-v5, tier: 1}
+          - {dataset: AIRS-2-1, project: obs4MIPs, level: L3, tier: 1}
     additional_datasets:
       - {dataset: ACCESS1-0}
       - {dataset: ACCESS1-3}
@@ -1055,9 +1055,9 @@ diagnostics:
         mip: Amon
         start_year: 2003
         end_year: 2005
-        reference_dataset: AIRS
+        reference_dataset: AIRS-2-1
         additional_datasets:
-          - {dataset: AIRS, project: obs4MIPs, level: L3, version: RetStd-v5, tier: 1}
+          - {dataset: AIRS-2-1, project: obs4MIPs, level: L3, tier: 1}
     additional_datasets:
       - {dataset: ACCESS-CM2,      ensemble: r1i1p1f1, grid: gn, institute: CSIRO-ARCCSS}
       - {dataset: ACCESS-ESM1-5,   ensemble: r1i1p1f1, grid: gn}
@@ -1283,7 +1283,7 @@ diagnostics:
         end_year: 2005
         reference_dataset: CERES-EBAF
         additional_datasets:
-          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7, tier: 1}
+          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1}
       rsutcs:
         <<: *var_settings_cmip5
         preprocessor: default
@@ -1292,7 +1292,7 @@ diagnostics:
         end_year: 2005
         reference_dataset: CERES-EBAF
         additional_datasets:
-          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7, tier: 1}
+          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1}
       rsdt:
         <<: *var_settings_cmip5
         preprocessor: default
@@ -1301,7 +1301,7 @@ diagnostics:
         end_year: 2005
         reference_dataset: CERES-EBAF
         additional_datasets:
-          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7, tier: 1}
+          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1}
     additional_datasets:
       - {dataset: ACCESS1-0}
       - {dataset: ACCESS1-3}
@@ -1380,7 +1380,7 @@ diagnostics:
         end_year: 2005
         reference_dataset: CERES-EBAF
         additional_datasets:
-          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7, tier: 1}
+          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1}
       rsutcs:
         <<: *var_settings_cmip6
         preprocessor: default
@@ -1389,7 +1389,7 @@ diagnostics:
         end_year: 2005
         reference_dataset: CERES-EBAF
         additional_datasets:
-          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7, tier: 1}
+          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1}
       rsdt:
         <<: *var_settings_cmip6
         preprocessor: default
@@ -1885,7 +1885,7 @@ diagnostics:
         end_year: 2010
         reference_dataset: 'AIRS-2-0|MLS-AURA'
         additional_datasets:
-          - {dataset: AIRS-2-0, project: obs4MIPs, level: L3, version: v2, tier: 1}
+          - {dataset: AIRS-2-0, project: obs4MIPs, level: L3, tier: 1}
           - {dataset: MLS-AURA, project: OBS6, type: sat, version: '004', tier: 3}
     additional_datasets:
       - {dataset: ACCESS1-0}
@@ -1940,7 +1940,7 @@ diagnostics:
         end_year: 2010
         reference_dataset: 'AIRS-2-0|MLS-AURA'
         additional_datasets:
-          - {dataset: AIRS-2-0, project: obs4MIPs, level: L3, version: v2, tier: 1}
+          - {dataset: AIRS-2-0, project: obs4MIPs, level: L3, tier: 1}
           - {dataset: MLS-AURA, project: OBS6, type: sat, version: '004', tier: 3}
     additional_datasets:
       - {dataset: ACCESS-CM2,      ensemble: r1i1p1f1, grid: gn, institute: CSIRO-ARCCSS}

From 201bb178e129c8d169776720e529688639f9e1b7 Mon Sep 17 00:00:00 2001
From: Romain Beucher <romain.beucher@anu.edu.au>
Date: Fri, 10 Nov 2023 00:38:56 +1100
Subject: [PATCH 69/93] Update obs4MIPs names in flatoipcc recipes (#3328)

Co-authored-by: Bouwe Andela <bouweandela@gmail.com>
---
 .../ipccwg1ar5ch9/recipe_flato13ipcc_figures_92_95.yml      | 6 +++---
 .../recipe_flato13ipcc_figures_938_941_cmip6.yml            | 4 ++--
 2 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/esmvaltool/recipes/ipccwg1ar5ch9/recipe_flato13ipcc_figures_92_95.yml b/esmvaltool/recipes/ipccwg1ar5ch9/recipe_flato13ipcc_figures_92_95.yml
index 298b2bbc07..80286e716a 100644
--- a/esmvaltool/recipes/ipccwg1ar5ch9/recipe_flato13ipcc_figures_92_95.yml
+++ b/esmvaltool/recipes/ipccwg1ar5ch9/recipe_flato13ipcc_figures_92_95.yml
@@ -267,10 +267,10 @@ diagnostics:
     variables:
       pr:
         preprocessor: clim
-        reference_dataset: GPCP-SG
+        reference_dataset: GPCP-V2.2
         mip: Amon
     additional_datasets:
-      - {dataset: GPCP-SG, project: obs4MIPs, level: L3, version: v2.2,
+      - {dataset: GPCP-V2.2, project: obs4MIPs, level: L3,
          start_year: 1986, end_year: 2005, tier: 1}
       - {dataset: ACCESS1-0, project: CMIP5, exp: historical, ensemble: r1i1p1,
          start_year: 1986, end_year: 2005}
@@ -385,7 +385,7 @@ diagnostics:
         mip: Amon
         derive: true
     additional_datasets:
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7,
+      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B,
          start_year: 2001, end_year: 2010, tier: 1}
       - {dataset: ACCESS1-0, project: CMIP5, exp: historical, ensemble: r1i1p1,
          start_year: 1986, end_year: 2005}
diff --git a/esmvaltool/recipes/ipccwg1ar5ch9/recipe_flato13ipcc_figures_938_941_cmip6.yml b/esmvaltool/recipes/ipccwg1ar5ch9/recipe_flato13ipcc_figures_938_941_cmip6.yml
index dad979e8aa..e67625b257 100644
--- a/esmvaltool/recipes/ipccwg1ar5ch9/recipe_flato13ipcc_figures_938_941_cmip6.yml
+++ b/esmvaltool/recipes/ipccwg1ar5ch9/recipe_flato13ipcc_figures_938_941_cmip6.yml
@@ -322,13 +322,13 @@ diagnostics:
     variables:
       pr:
         preprocessor: clima_nomask_pr
-        reference_dataset: GPCP-SG
+        reference_dataset: GPCP-V2.2
         mip: Amon
         ensemble: r1i1p1
         start_year: 1980
         end_year: 2005
     additional_datasets:
-      - {dataset: GPCP-SG, project: OBS, project: obs4MIPs, level: L3, version: v2.2, tier: 1}
+      - {dataset: GPCP-V2.2, project: obs4MIPs, tier: 1}
       # - {dataset: CRU, project: OBS, type: reanaly, version: TS4.02, tier: 2}
     scripts:
       clim:

From 7fb0aa9d83ecd5e4a987320d2d8cae97bdd7d7d9 Mon Sep 17 00:00:00 2001
From: Romain Beucher <romain.beucher@anu.edu.au>
Date: Fri, 10 Nov 2023 00:40:40 +1100
Subject: [PATCH 70/93] Update obs4mips dataset versions (ESGF) in clouds
 recipes (#3326)

---
 .../recipes/clouds/recipe_clouds_bias.yml     | 10 ++--
 .../recipes/clouds/recipe_clouds_ipcc.yml     |  9 ++--
 .../recipes/clouds/recipe_lauer13jclim.yml    | 54 +++++++------------
 3 files changed, 27 insertions(+), 46 deletions(-)

diff --git a/esmvaltool/recipes/clouds/recipe_clouds_bias.yml b/esmvaltool/recipes/clouds/recipe_clouds_bias.yml
index 0d28235431..d424397b22 100644
--- a/esmvaltool/recipes/clouds/recipe_clouds_bias.yml
+++ b/esmvaltool/recipes/clouds/recipe_clouds_bias.yml
@@ -171,11 +171,10 @@ diagnostics:
     variables:
       pr:
         preprocessor: clim
-        reference_dataset: GPCP-SG
+        reference_dataset: GPCP-V2.2
         mip: Amon
     additional_datasets:
-      - {dataset: GPCP-SG, project: obs4MIPs, level: L3, version: v2.2,
-         start_year: 1986, end_year: 2005, tier: 1}
+      - {dataset: GPCP-V2.2, project: obs4MIPs, level: L3, start_year: 1986, end_year: 2005, tier: 1}
     scripts:
       clim:
         <<: *clim_settings
@@ -198,11 +197,10 @@ diagnostics:
     variables:
       clt:
         preprocessor: clim
-        reference_dataset: MODIS
+        reference_dataset: MODIS-1-0
         mip: Amon
     additional_datasets:
-      - {dataset: MODIS, project: obs4MIPs, level: L3, version: C5,
-         start_year: 2001, end_year: 2010, tier: 1}
+      - {dataset: MODIS-1-0, project: obs4MIPs, level: L3, start_year: 2001, end_year: 2010, tier: 1}
     scripts:
       clim:
         <<: *clim_settings
diff --git a/esmvaltool/recipes/clouds/recipe_clouds_ipcc.yml b/esmvaltool/recipes/clouds/recipe_clouds_ipcc.yml
index 0df31e074e..2fb14b4795 100644
--- a/esmvaltool/recipes/clouds/recipe_clouds_ipcc.yml
+++ b/esmvaltool/recipes/clouds/recipe_clouds_ipcc.yml
@@ -145,8 +145,7 @@ diagnostics:
         mip: Amon
         derive: true
     additional_datasets:
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7,
-         start_year: 2001, end_year: 2010, tier: 1}
+      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, start_year: 2001, end_year: 2010, tier: 1}
     scripts:
       clim: &clim_settings
         script: clouds/clouds_ipcc.ncl
@@ -168,8 +167,7 @@ diagnostics:
         mip: Amon
         derive: true
     additional_datasets:
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7,
-         start_year: 2001, end_year: 2010, tier: 1}
+      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, start_year: 2001, end_year: 2010, tier: 1}
     scripts:
       clim:
         <<: *clim_settings
@@ -188,8 +186,7 @@ diagnostics:
         mip: Amon
         derive: true
     additional_datasets:
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7,
-         start_year: 2001, end_year: 2010, tier: 1}
+      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, start_year: 2001, end_year: 2010, tier: 1}
     scripts:
       clim:
         <<: *clim_settings
diff --git a/esmvaltool/recipes/clouds/recipe_lauer13jclim.yml b/esmvaltool/recipes/clouds/recipe_lauer13jclim.yml
index 2a7051b5d5..3d741e485d 100644
--- a/esmvaltool/recipes/clouds/recipe_lauer13jclim.yml
+++ b/esmvaltool/recipes/clouds/recipe_lauer13jclim.yml
@@ -168,11 +168,10 @@ diagnostics:
     variables:
       clt:
         preprocessor: clim
-        reference_dataset: MODIS
+        reference_dataset: MODIS-1-0
         mip: Amon
     additional_datasets:
-      - {dataset: MODIS, project: obs4MIPs, level: L3, version: C5,
-         start_year: 2001, end_year: 2010, tier: 1}
+      - {dataset: MODIS-1-0, project: obs4MIPs, level: L3, start_year: 2001, end_year: 2010, tier: 1}
     scripts:
       clim:
         <<: *clim_settings
@@ -187,11 +186,10 @@ diagnostics:
     variables:
       pr:
         preprocessor: clim
-        reference_dataset: GPCP-SG
+        reference_dataset: GPCP-V2.2
         mip: Amon
     additional_datasets:
-      - {dataset: GPCP-SG, project: obs4MIPs, level: L3, version: v2.2,
-         start_year: 1986, end_year: 2005, tier: 1}
+      - {dataset: GPCP-V2.2, project: obs4MIPs, level: L3, start_year: 1986, end_year: 2005, tier: 1}
     scripts:
       clim:
         <<: *clim_settings
@@ -211,8 +209,7 @@ diagnostics:
         mip: Amon
         derive: true
     additional_datasets:
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7,
-         start_year: 2001, end_year: 2010, tier: 1}
+      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, start_year: 2001, end_year: 2010, tier: 1}
     scripts:
       clim:
         <<: *clim_settings
@@ -232,8 +229,7 @@ diagnostics:
         mip: Amon
         derive: true
     additional_datasets:
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7,
-         start_year: 2001, end_year: 2010, tier: 1}
+      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, start_year: 2001, end_year: 2010, tier: 1}
     scripts:
       clim:
         <<: *clim_settings
@@ -253,11 +249,10 @@ diagnostics:
     variables:
       clt:
         preprocessor: clim
-        reference_dataset: MODIS
+        reference_dataset: MODIS-1-0
         mip: Amon
     additional_datasets:
-      - {dataset: MODIS, project: obs4MIPs, level: L3, version: C5,
-         start_year: 2001, end_year: 2010, tier: 1}
+      - {dataset: MODIS-1-0, project: obs4MIPs, level: L3, start_year: 2001, end_year: 2010, tier: 1}
     scripts:
       clim: &taylor_settings
         script: clouds/clouds_taylor.ncl
@@ -314,8 +309,7 @@ diagnostics:
         mip: Amon
         derive: true
     additional_datasets:
-      - {dataset: UWisc, project: OBS, type: sat, version: v2,
-         start_year: 1988, end_year: 2007, tier: 3}
+      - {dataset: UWisc, project: OBS, type: sat, version: v2, start_year: 1988, end_year: 2007, tier: 3}
     scripts:
       clim:
         <<: *taylor_settings
@@ -335,8 +329,7 @@ diagnostics:
         mip: Amon
         derive: true
     additional_datasets:
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7,
-         start_year: 2001, end_year: 2010, tier: 1}
+      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, start_year: 2001, end_year: 2010, tier: 1}
     scripts:
       clim:
         <<: *taylor_settings
@@ -356,8 +349,7 @@ diagnostics:
         mip: Amon
         derive: true
     additional_datasets:
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7,
-         start_year: 2001, end_year: 2010, tier: 1}
+      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, start_year: 2001, end_year: 2010, tier: 1}
     scripts:
       clim:
         <<: *taylor_settings
@@ -372,11 +364,10 @@ diagnostics:
     variables:
       pr:
         preprocessor: clim
-        reference_dataset: GPCP-SG
+        reference_dataset: GPCP-V2.2
         mip: Amon
     additional_datasets:
-      - {dataset: GPCP-SG, project: obs4MIPs, level: L3, version: v2.2,
-         start_year: 1986, end_year: 2005, tier: 1}
+      - {dataset: GPCP-V2.2, project: obs4MIPs, level: L3, start_year: 1986, end_year: 2005, tier: 1}
     scripts:
       clim:
         <<: *taylor_settings
@@ -402,8 +393,7 @@ diagnostics:
         mip: Amon
         derive: true
     additional_datasets:
-      - {dataset: UWisc, project: OBS, type: sat, version: v2,
-         start_year: 1988, end_year: 2007, tier: 3}
+      - {dataset: UWisc, project: OBS, type: sat, version: v2, start_year: 1988, end_year: 2007, tier: 3}
     scripts:
       clim: &intera_settings
         script: clouds/clouds_interannual.ncl
@@ -435,11 +425,10 @@ diagnostics:
     variables:
       clt:
         preprocessor: clim
-        reference_dataset: MODIS
+        reference_dataset: MODIS-1-0
         mip: Amon
     additional_datasets:
-      - {dataset: MODIS, project: obs4MIPs, level: L3, version: C5,
-         start_year: 2001, end_year: 2010, tier: 1}
+      - {dataset: MODIS-1-0, project: obs4MIPs, level: L3, start_year: 2001, end_year: 2010, tier: 1}
     scripts:
       clim:
         <<: *intera_settings
@@ -459,8 +448,7 @@ diagnostics:
         mip: Amon
         derive: true
     additional_datasets:
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7,
-         start_year: 2001, end_year: 2010, tier: 1}
+      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, start_year: 2001, end_year: 2010, tier: 1}
     scripts:
       clim:
         <<: *intera_settings
@@ -480,8 +468,7 @@ diagnostics:
         mip: Amon
         derive: true
     additional_datasets:
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7,
-         start_year: 2001, end_year: 2010, tier: 1}
+      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, start_year: 2001, end_year: 2010, tier: 1}
     scripts:
       clim:
         <<: *intera_settings
@@ -496,11 +483,10 @@ diagnostics:
     variables:
       pr:
         preprocessor: clim
-        reference_dataset: GPCP-SG
+        reference_dataset: GPCP-V2.2
         mip: Amon
     additional_datasets:
-      - {dataset: GPCP-SG, project: obs4MIPs, level: L3, version: v2.2,
-         start_year: 1986, end_year: 2005, tier: 1}
+      - {dataset: GPCP-V2.2, project: obs4MIPs, level: L3, start_year: 1986, end_year: 2005, tier: 1}
     scripts:
       clim:
         <<: *intera_settings

From 4003f162e9278911019a8c695b7ae6436d9b190d Mon Sep 17 00:00:00 2001
From: Romain Beucher <romain.beucher@anu.edu.au>
Date: Fri, 10 Nov 2023 00:42:39 +1100
Subject: [PATCH 71/93] Update recipe_radiation_budget to use obs4MIP
 CERES-EBAF available on ESGF (#3323)

---
 esmvaltool/recipes/recipe_radiation_budget.yml | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/esmvaltool/recipes/recipe_radiation_budget.yml b/esmvaltool/recipes/recipe_radiation_budget.yml
index 2f56cb4f9c..4a81307283 100644
--- a/esmvaltool/recipes/recipe_radiation_budget.yml
+++ b/esmvaltool/recipes/recipe_radiation_budget.yml
@@ -52,13 +52,13 @@ diagnostics:
         mip: Amon
         preprocessor: single_value
         additional_datasets:
-          - {dataset: CERES-EBAF, project: obs4mips, level: L3B, version: Ed2-7,
+          - {dataset: CERES-EBAF, project: obs4mips, level: L3B,
              start_year: 2000, end_year: 2010, tier: 1}
       rsutcs:
         mip: Amon
         preprocessor: single_value
         additional_datasets:
-          - {dataset: CERES-EBAF, project: obs4mips, level: L3B, version: Ed2-7,
+          - {dataset: CERES-EBAF, project: obs4mips, level: L3B,
              start_year: 2000, end_year: 2010, tier: 1}
       rsds:
         mip: Amon
@@ -70,13 +70,13 @@ diagnostics:
         mip: Amon
         preprocessor: single_value
         additional_datasets:
-          - {dataset: CERES-EBAF, project: obs4mips, level: L3B, version: Ed2-7,
+          - {dataset: CERES-EBAF, project: obs4mips, level: L3B,
              start_year: 2000, end_year: 2010, tier: 1}
       rlutcs:
         mip: Amon
         preprocessor: single_value
         additional_datasets:
-          - {dataset: CERES-EBAF, project: obs4mips, level: L3B, version: Ed2-7,
+          - {dataset: CERES-EBAF, project: obs4mips, level: L3B,
              start_year: 2000, end_year: 2010, tier: 1}
       rlds:
         mip: Amon

From d14c3093473d47447db2903c0084af6a3e3e79c0 Mon Sep 17 00:00:00 2001
From: Romain Beucher <romain.beucher@anu.edu.au>
Date: Fri, 10 Nov 2023 03:17:35 +1100
Subject: [PATCH 72/93] Update Obs4MIPs datasets names (ESGF) in ECS recipes
 (#3327)

---
 esmvaltool/recipes/recipe_ecs_constraints.yml | 18 +++---
 esmvaltool/recipes/recipe_ecs_scatter.yml     | 57 ++++++++-----------
 2 files changed, 34 insertions(+), 41 deletions(-)

diff --git a/esmvaltool/recipes/recipe_ecs_constraints.yml b/esmvaltool/recipes/recipe_ecs_constraints.yml
index 3655503e8a..0abc4f20e6 100644
--- a/esmvaltool/recipes/recipe_ecs_constraints.yml
+++ b/esmvaltool/recipes/recipe_ecs_constraints.yml
@@ -522,9 +522,9 @@ diagnostics:
         mip: Amon
         start_year: 1986
         end_year: 2005
-        reference_dataset: GPCP-SG
+        reference_dataset: GPCP-V2.2
         additional_datasets:
-          - {dataset: GPCP-SG, project: obs4MIPs, level: L3, version: v2.2, tier: 1}
+          - {dataset: GPCP-V2.2, project: obs4MIPs, level: L3, tier: 1}
     additional_datasets:
       - {dataset: ACCESS1-0}
       - {dataset: ACCESS1-3}
@@ -593,9 +593,9 @@ diagnostics:
         mip: Amon
         start_year: 2003
         end_year: 2005
-        reference_dataset: AIRS
+        reference_dataset: AIRS-2-1
         additional_datasets:
-          - {dataset: AIRS, project: obs4MIPs, level: L3, version: RetStd-v5, tier: 1}
+          - {dataset: AIRS-2-1, project: obs4MIPs, level: L3, tier: 1}
     additional_datasets:
       - {dataset: ACCESS1-0}
       - {dataset: ACCESS1-3}
@@ -755,7 +755,7 @@ diagnostics:
         end_year: 2005
         reference_dataset: CERES-EBAF
         additional_datasets:
-          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7, tier: 1}
+          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1}
       rsutcs:
         <<: *var_settings_cmip5
         preprocessor: default
@@ -764,7 +764,7 @@ diagnostics:
         end_year: 2005
         reference_dataset: CERES-EBAF
         additional_datasets:
-          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7, tier: 1}
+          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1}
       rsdt:
         <<: *var_settings_cmip5
         preprocessor: default
@@ -773,7 +773,7 @@ diagnostics:
         end_year: 2005
         reference_dataset: CERES-EBAF
         additional_datasets:
-          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7, tier: 1}
+          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1}
     additional_datasets:
       - {dataset: ACCESS1-0}
       - {dataset: ACCESS1-3}
@@ -1175,9 +1175,9 @@ diagnostics:
         exp: [historical, rcp85]
         start_year: 2005
         end_year: 2010
-        reference_dataset: 'AIRS-2-0|MLS-AURA'
+        reference_dataset: AIRS-2-0|MLS-AURA
         additional_datasets:
-          - {dataset: AIRS-2-0, project: obs4MIPs, level: L3, version: v2, tier: 1}
+          - {dataset: AIRS-2-0, project: obs4MIPs, level: L3, tier: 1}
           - {dataset: MLS-AURA, project: OBS6, type: sat, version: '004', tier: 3}
     additional_datasets:
       - {dataset: ACCESS1-0}
diff --git a/esmvaltool/recipes/recipe_ecs_scatter.yml b/esmvaltool/recipes/recipe_ecs_scatter.yml
index a052caf1c4..eae1034e42 100644
--- a/esmvaltool/recipes/recipe_ecs_scatter.yml
+++ b/esmvaltool/recipes/recipe_ecs_scatter.yml
@@ -126,14 +126,14 @@ diagnostics:
       - atmos
     variables:
       pr:
-        reference_dataset: TRMM-L3
+        reference_dataset: TRMM
         mip: Amon
         exp: historical
         start_year: 1986
         end_year: 2005
         project: CMIP5
         additional_datasets:
-          - {dataset: TRMM-L3, project: obs4MIPs, level: v7, version: 7A,
+          - {dataset: TRMM, project: obs4MIPs, level: v7,
              start_year: 1998, end_year: 2013, tier: 1}
           - {dataset: ACCESS1-0, ensemble: r1i1p1}
           # - {dataset: ACCESS1-3, ensemble: r1i1p1}
@@ -162,11 +162,11 @@ diagnostics:
           - {dataset: MRI-CGCM3, ensemble: r1i1p1}
           - {dataset: NorESM1-M, ensemble: r1i1p1}
       prStderr:
-        reference_dataset: TRMM-L3
+        reference_dataset: TRMM
         mip: Amon
         frequency: mon
         additional_datasets:
-          - {dataset: TRMM-L3, project: obs4MIPs, level: v7, version: 7A,
+          - {dataset: TRMM, project: obs4MIPs, level: v7,
              start_year: 1998, end_year: 2013, tier: 1}
     scripts:
       ecs_scatter:
@@ -188,14 +188,14 @@ diagnostics:
     variables:
       hus:
         preprocessor: pp500
-        reference_dataset: AIRS
+        reference_dataset: AIRS-2-1
         mip: Amon
         exp: historical
         start_year: 1986
         end_year: 2005
         project: CMIP5
         additional_datasets:
-          - {dataset: AIRS, project: obs4MIPs, level: L3, version: RetStd-v5,
+          - {dataset: AIRS-2-1, project: obs4MIPs, level: L3,
              start_year: 2003, end_year: 2010, tier: 1}
           - {dataset: ACCESS1-0, ensemble: r1i1p1}
           # - {dataset: ACCESS1-3, ensemble: r1i1p1}
@@ -225,11 +225,11 @@ diagnostics:
           - {dataset: NorESM1-M, ensemble: r1i1p1}
       husStderr:
         preprocessor: pp500
-        reference_dataset: AIRS
+        reference_dataset: AIRS-2-1
         mip: Amon
         frequency: mon
         additional_datasets:
-          - {dataset: AIRS, project: obs4MIPs, level: L3, version: RetStd-v5,
+          - {dataset: AIRS-2-1, project: obs4MIPs, level: L3,
              start_year: 2003, end_year: 2010, tier: 1}
     scripts:
       ecs_scatter:
@@ -396,24 +396,24 @@ diagnostics:
         exp: historical
         project: CMIP5
         additional_datasets:
-          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7,
-             start_year: 2001, end_year: 2005, tier: 1}
+          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, start_year: 2001, end_year: 2005,
+             tier: 1}
       rsutcs:
         reference_dataset: CERES-EBAF
         mip: Amon
         exp: historical
         project: CMIP5
         additional_datasets:
-          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7,
-             start_year: 2001, end_year: 2005, tier: 1}
+          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, start_year: 2001, end_year: 2005,
+             tier: 1}
       rsdt:
         reference_dataset: CERES-EBAF
         mip: Amon
         exp: historical
         project: CMIP5
         additional_datasets:
-          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7,
-             start_year: 2001, end_year: 2005, tier: 1}
+          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, start_year: 2001, end_year: 2005,
+             tier: 1}
     scripts:
       ecs_scatter:
         diag: covrefl
@@ -433,15 +433,14 @@ diagnostics:
       - atmos
     variables:
       pr:
-        reference_dataset: TRMM-L3
+        reference_dataset: TRMM
         start_year: 1998
         end_year: 2013
         exp: historical
         mip: Amon
         project: CMIP6
         additional_datasets:
-          - {dataset: TRMM-L3, project: obs4MIPs, level: v7,
-             version: 7A, tier: 1}
+          - {dataset: TRMM, project: obs4MIPs, level: v7, tier: 1}
           - {dataset: BCC-CSM2-MR, grid: gn, ensemble: r1i1p1f1}
           - {dataset: BCC-ESM1, grid: gn, ensemble: r1i1p1f1}
           - {dataset: CAMS-CSM1-0, grid: gn, ensemble: r1i1p1f1}
@@ -457,14 +456,13 @@ diagnostics:
           - {dataset: MIROC6, grid: gn, ensemble: r1i1p1f1}
           - {dataset: MRI-ESM2-0, grid: gn, ensemble: r1i1p1f1}
       prStderr:
-        reference_dataset: TRMM-L3
+        reference_dataset: TRMM
         mip: Amon
         frequency: mon
         start_year: 1998
         end_year: 2013
         additional_datasets:
-          - {dataset: TRMM-L3, project: obs4MIPs, level: v7,
-             version: 7A, tier: 1}
+          - {dataset: TRMM, project: obs4MIPs, level: v7, tier: 1}
     scripts:
       ecs_scatter:
         diag: itczidx
@@ -484,15 +482,14 @@ diagnostics:
     variables:
       hus:
         preprocessor: pp500
-        reference_dataset: AIRS
+        reference_dataset: AIRS-2-1
         start_year: 2003
         end_year: 2010
         exp: historical
         mip: Amon
         project: CMIP6
         additional_datasets:
-          - {dataset: AIRS, project: obs4MIPs, level: L3,
-             version: RetStd-v5, tier: 1}
+          - {dataset: AIRS-2-1, project: obs4MIPs, level: L3, tier: 1}
           - {dataset: BCC-CSM2-MR, grid: gn, ensemble: r1i1p1f1}
           - {dataset: BCC-ESM1, grid: gn, ensemble: r1i1p1f1}
           - {dataset: CAMS-CSM1-0, grid: gn, ensemble: r1i1p1f1}
@@ -509,14 +506,13 @@ diagnostics:
           - {dataset: MRI-ESM2-0, grid: gn, ensemble: r1i1p1f1}
       husStderr:
         preprocessor: pp500
-        reference_dataset: AIRS
+        reference_dataset: AIRS-2-1
         mip: Amon
         frequency: mon
         start_year: 2003
         end_year: 2010
         additional_datasets:
-          - {dataset: AIRS, project: obs4MIPs, level: L3,
-             version: RetStd-v5, tier: 1}
+          - {dataset: AIRS-2-1, project: obs4MIPs, level: L3, tier: 1}
     scripts:
       ecs_scatter:
         diag: humidx
@@ -689,8 +685,7 @@ diagnostics:
         mip: Amon
         project: CMIP6
         additional_datasets:
-          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B,
-             version: Ed2-7, tier: 1}
+          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1}
           - {dataset: BCC-CSM2-MR, grid: gn, ensemble: r1i1p1f1}
           - {dataset: BCC-ESM1, grid: gn, ensemble: r2i1p1f1}
           # - {dataset: CAMS-CSM1-0, grid: gn, ensemble: r1i1p1f1}
@@ -713,8 +708,7 @@ diagnostics:
         mip: Amon
         project: CMIP6
         additional_datasets:
-          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B,
-             version: Ed2-7, tier: 1}
+          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1}
           - {dataset: BCC-CSM2-MR, grid: gn, ensemble: r1i1p1f1}
           - {dataset: BCC-ESM1, grid: gn, ensemble: r2i1p1f1}
           # - {dataset: CAMS-CSM1-0, grid: gn, ensemble: r1i1p1f1}
@@ -737,8 +731,7 @@ diagnostics:
         mip: Amon
         project: CMIP6
         additional_datasets:
-          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B,
-             version: Ed2-7, tier: 1}
+          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1}
           - {dataset: BCC-CSM2-MR, grid: gn, ensemble: r1i1p1f1}
           - {dataset: BCC-ESM1, grid: gn, ensemble: r2i1p1f1}
           # - {dataset: CAMS-CSM1-0, grid: gn, ensemble: r1i1p1f1}

From 838d5f5d61e0498187985411867a7fe46ea6e944 Mon Sep 17 00:00:00 2001
From: Romain Beucher <romain.beucher@anu.edu.au>
Date: Mon, 13 Nov 2023 21:25:34 +1100
Subject: [PATCH 73/93] Update obs4mips names in Bock et al recipes for
 compatibility with ESGF (#3324)

Co-authored-by: Bouwe Andela <bouweandela@gmail.com>
---
 .../bock20jgr/recipe_bock20jgr_fig_6-7.yml    | 38 +++++++------------
 .../bock20jgr/recipe_bock20jgr_fig_8-10.yml   |  3 +-
 2 files changed, 15 insertions(+), 26 deletions(-)

diff --git a/esmvaltool/recipes/bock20jgr/recipe_bock20jgr_fig_6-7.yml b/esmvaltool/recipes/bock20jgr/recipe_bock20jgr_fig_6-7.yml
index c54ffc5f1e..93e4284ec5 100644
--- a/esmvaltool/recipes/bock20jgr/recipe_bock20jgr_fig_6-7.yml
+++ b/esmvaltool/recipes/bock20jgr/recipe_bock20jgr_fig_6-7.yml
@@ -359,7 +359,7 @@ diagnostics:
     variables:
       pr:
         preprocessor: ppNOLEV1
-        reference_dataset: GPCP-SG
+        reference_dataset: GPCP-V2.2
         alternative_dataset: GHCN
         mip: Amon
         project: CMIP5
@@ -393,8 +393,7 @@ diagnostics:
       - {dataset: FGOALS-f3-L, ensemble: r1i1p1f1, grid: gr, project: CMIP6}
       - {dataset: MCM-UA-1-0, grid: gn, ensemble: r1i1p1f1, project: CMIP6}
 
-      - {dataset: GPCP-SG, project: obs4MIPs, level: L3,
-         version: v2.2, tier: 1}
+      - {dataset: GPCP-V2.2, project: obs4MIPs, level: L3, tier: 1}
       - {dataset: GHCN, project: OBS, type: ground, version: 1, tier: 2}
     scripts:
       grading:
@@ -530,8 +529,7 @@ diagnostics:
       - {dataset: CIESM, grid: gr, ensemble: r1i1p1f1, project: CMIP6}
       - {dataset: FGOALS-f3-L, ensemble: r1i1p1f1, grid: gr, project: CMIP6}
 
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B,
-         version: Ed2-8, tier: 1, start_year: 2001, end_year: 2015}
+      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1, start_year: 2001, end_year: 2015}
     scripts:
       grading:
         <<: *grading_settings
@@ -568,8 +566,7 @@ diagnostics:
       - {dataset: CanESM5-CanOE, ensemble: r1i1p2f1, grid: gn, project: CMIP6}
       - {dataset: FGOALS-f3-L, ensemble: r1i1p1f1, grid: gr, project: CMIP6}
 
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B,
-         version: Ed2-8, tier: 1, start_year: 2001, end_year: 2015}
+      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1, start_year: 2001, end_year: 2015}
     scripts:
       grading:
         <<: *grading_settings
@@ -611,8 +608,7 @@ diagnostics:
       - {dataset: FGOALS-f3-L, ensemble: r1i1p1f1, grid: gr, project: CMIP6}
       - {dataset: MCM-UA-1-0, grid: gn, ensemble: r1i1p1f1, project: CMIP6}
 
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B,
-         version: Ed2-8, tier: 1, start_year: 2001, end_year: 2015}
+      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1, start_year: 2001, end_year: 2015}
     scripts:
       grading:
         <<: *grading_settings
@@ -628,7 +624,7 @@ diagnostics:
     variables:
       hus:
         preprocessor: pp400
-        reference_dataset: AIRS
+        reference_dataset: AIRS-2-1
         alternative_dataset: ERA-Interim
         mip: Amon
         project: CMIP5
@@ -652,10 +648,8 @@ diagnostics:
       - {dataset: FGOALS-f3-L, ensemble: r1i1p1f1, grid: gr, project: CMIP6}
       - {dataset: MCM-UA-1-0, grid: gn, ensemble: r1i1p1f1, project: CMIP6}
 
-      - {dataset: AIRS, project: obs4MIPs, level: L3,
-         version: RetStd-v5, tier: 1, start_year: 2003, end_year: 2010}
-      - {dataset: ERA-Interim, project: OBS6, type: reanaly,
-         version: 1, tier: 3}
+      - {dataset: AIRS-2-1, project: obs4MIPs, level: L3, tier: 1, start_year: 2003, end_year: 2010}
+      - {dataset: ERA-Interim, project: OBS6, type: reanaly, version: 1, tier: 3}
     scripts:
       grading:
         <<: *grading_settings
@@ -694,8 +688,7 @@ diagnostics:
       - {dataset: CIESM, grid: gr, ensemble: r1i1p1f1, project: CMIP6}
       - {dataset: FGOALS-f3-L, ensemble: r1i1p1f1, grid: gr, project: CMIP6}
 
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B,
-         version: Ed2-8, tier: 1, start_year: 2001, end_year: 2015}
+      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1, start_year: 2001, end_year: 2015}
     scripts:
       grading:
         <<: *grading_settings
@@ -744,8 +737,7 @@ diagnostics:
       - {dataset: FGOALS-f3-L, ensemble: r1i1p1f1, grid: gr, project: CMIP6}
       - {dataset: MCM-UA-1-0, grid: gn, ensemble: r1i1p1f1, project: CMIP6}
 
-      - {dataset: ERA-Interim, project: OBS6, type: reanaly,
-         version: 1, tier: 3}
+      - {dataset: ERA-Interim, project: OBS6, type: reanaly, version: 1, tier: 3}
       - {dataset: NCEP-NCAR-R1, project: OBS6, type: reanaly, version: 1, tier: 2}
     scripts:
       grading:
@@ -1085,7 +1077,7 @@ diagnostics:
     variables:
       pr:
         <<: *var_settings
-        reference_dataset: GPCP-SG
+        reference_dataset: GPCP-V2.2
         alternative_dataset: GHCN
     additional_datasets:
       - {<<: *cmip3, dataset: bccr_bcm2_0, institute: BCCR}
@@ -1113,7 +1105,7 @@ diagnostics:
       - {dataset: FGOALS-f3-L, ensemble: r1i1p1f1, grid: gr, project: CMIP6}
       - {dataset: MCM-UA-1-0, grid: gn, ensemble: r1i1p1f1, project: CMIP6}
 
-      - {dataset: GPCP-SG, project: obs4MIPs, level: L3, version: v2.2, tier: 1}
+      - {dataset: GPCP-V2.2, project: obs4MIPs, level: L3, tier: 1}
       - {dataset: GHCN, project: OBS, type: ground, version: 1, tier: 2}
 
   psl_cor:
@@ -1175,8 +1167,7 @@ diagnostics:
       - {dataset: FGOALS-f3-L, ensemble: r1i1p1f1, grid: gr, project: CMIP6}
       - {dataset: MCM-UA-1-0, grid: gn, ensemble: r1i1p1f1, project: CMIP6}
 
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-8,
-         tier: 1, start_year: 2001, end_year: 2015}
+      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1, start_year: 2001, end_year: 2015}
 
   swcre_cor:
     <<: *corr_diag
@@ -1199,8 +1190,7 @@ diagnostics:
       - {dataset: CanESM5-CanOE, ensemble: r1i1p2f1, grid: gn, project: CMIP6}
       - {dataset: FGOALS-f3-L, ensemble: r1i1p1f1, grid: gr, project: CMIP6}
 
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-8,
-         tier: 1, start_year: 2001, end_year: 2015}
+      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1, start_year: 2001, end_year: 2015}
 
   fig_7:
     title: Collection of pattern correlations
diff --git a/esmvaltool/recipes/bock20jgr/recipe_bock20jgr_fig_8-10.yml b/esmvaltool/recipes/bock20jgr/recipe_bock20jgr_fig_8-10.yml
index 652490ca09..a01020e709 100644
--- a/esmvaltool/recipes/bock20jgr/recipe_bock20jgr_fig_8-10.yml
+++ b/esmvaltool/recipes/bock20jgr/recipe_bock20jgr_fig_8-10.yml
@@ -415,8 +415,7 @@ diagnostics:
         derive: true
         additional_datasets: *cmip3_all
     additional_datasets:
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7,
-         start_year: 2001, end_year: 2010, tier: 1}
+      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, start_year: 2001, end_year: 2010, tier: 1}
     scripts:
       clim:
         script: clouds/clouds_ipcc.ncl

From ac28b1f830b547318198d18d13132a70ad752de2 Mon Sep 17 00:00:00 2001
From: Valeriu Predoi <valeriu.predoi@gmail.com>
Date: Tue, 14 Nov 2023 07:23:38 +0000
Subject: [PATCH 74/93] re-add communities and grants in zenodo file (#3416)

---
 .zenodo.json | 36 +++++++++++++++++++++++++++++++++++-
 1 file changed, 35 insertions(+), 1 deletion(-)

diff --git a/.zenodo.json b/.zenodo.json
index 11e2188ba9..c6a731981f 100644
--- a/.zenodo.json
+++ b/.zenodo.json
@@ -388,5 +388,39 @@
   },
   "publication_date": "2023-07-06",
   "title": "ESMValTool",
-  "version": "v2.9.0"
+  "version": "v2.9.0",
+  "communities": [ 
+      { 
+          "identifier": "is-enes3" 
+      }, 
+      { 
+          "identifier": "dlr_de" 
+      }, 
+      { 
+          "identifier": "ecfunded" 
+      }, 
+      { 
+          "identifier": "nlesc" 
+      } 
+  ], 
+  "grants": [ 
+      { 
+          "id": "10.13039/501100000780::282672" 
+      }, 
+      { 
+          "id": "10.13039/501100000780::641727" 
+      }, 
+      { 
+          "id": "10.13039/501100000780::641816" 
+      }, 
+      { 
+          "id": "10.13039/501100000780::727862" 
+      }, 
+      { 
+          "id": "10.13039/501100000780::776613" 
+      }, 
+      { 
+          "id": "10.13039/501100000780::824084" 
+      } 
+  ] 
 }

From 7c1921d3227ee79ecb595bfcc89c91865bc32b5a Mon Sep 17 00:00:00 2001
From: Manuel Schlund <32543114+schlunma@users.noreply.github.com>
Date: Tue, 14 Nov 2023 10:12:42 +0100
Subject: [PATCH 75/93] Support `CenteredNorm` in diagnostic
 monitor/multidatasets.py (#3415)

Co-authored-by: Klaus Zimmermann <klaus.zimmermann@smhi.se>
---
 .../diag_scripts/monitor/multi_datasets.py    | 99 ++++++++++++++-----
 1 file changed, 72 insertions(+), 27 deletions(-)

diff --git a/esmvaltool/diag_scripts/monitor/multi_datasets.py b/esmvaltool/diag_scripts/monitor/multi_datasets.py
index 4299e2538c..abfed90f9d 100644
--- a/esmvaltool/diag_scripts/monitor/multi_datasets.py
+++ b/esmvaltool/diag_scripts/monitor/multi_datasets.py
@@ -225,13 +225,17 @@
     ``plot_func``. String arguments can include facets in curly brackets which
     will be derived from the corresponding dataset, e.g., ``{project}``,
     ``{short_name}``, ``{exp}``. Examples: ``default: {levels: 2}, CMIP6:
-    {vmin: 200, vmax: 250}``.
+    {vmin: 200, vmax: 250}``. In addition to the normalization_ options
+    supported by the plot function, the option ``norm: centered`` can be
+    specified. In this case, the keywords ``vcenter`` and ``halfrange`` should
+    be used instead of ``vmin`` or ``vmax`` (see
+    :class:`~matplotlib.colors.CenteredNorm`).
 plot_kwargs_bias: dict, optional
     Optional keyword arguments for the plot function defined by ``plot_func``
     for plotting biases. These keyword arguments update (and potentially
     overwrite) the ``plot_kwargs`` for the bias plot. This option has no effect
     if no reference dataset is given. See option ``plot_kwargs`` for more
-    details. By default, uses ``cmap: bwr``.
+    details. By default, uses ``cmap: bwr`` and ``norm: centered``.
 projection: str, optional (default: 'Robinson')
     Projection used for the map plot. Needs to be a valid projection class of
     :mod:`cartopy.crs`. Keyword arguments can be specified using the option
@@ -248,10 +252,9 @@
     ``{project}``, ``{short_name}``, ``{exp}``.  Examples: ``title: 'Awesome
     Plot of {long_name}'``, ``xlabel: '{short_name}'``, ``xlim: [0, 5]``.
 rasterize: bool, optional (default: True)
-    If ``True``, use `rasterization
-    <https://matplotlib.org/stable/gallery/misc/rasterization_demo.html>`_ for
-    map plots to produce smaller files. This is only relevant for vector
-    graphics (e.g., ``output_file_type=pdf,svg,ps``).
+    If ``True``, use rasterization_ for map plots to produce smaller files.
+    This is only relevant for vector graphics (e.g., ``output_file_type:
+    pdf,svg,ps``).
 show_stats: bool, optional (default: True)
     Show basic statistics on the plots.
 x_pos_stats_avg: float, optional (default: 0.0)
@@ -309,13 +312,17 @@
     ``plot_func``. String arguments can include facets in curly brackets which
     will be derived from the corresponding dataset, e.g., ``{project}``,
     ``{short_name}``, ``{exp}``. Examples: ``default: {levels: 2}, CMIP6:
-    {vmin: 200, vmax: 250}``.
+    {vmin: 200, vmax: 250}``. In addition to the normalization_ options
+    supported by the plot function, the option ``norm: centered`` can be
+    specified. In this case, the keywords ``vcenter`` and ``halfrange`` should
+    be used instead of ``vmin`` or ``vmax`` (see
+    :class:`~matplotlib.colors.CenteredNorm`).
 plot_kwargs_bias: dict, optional
     Optional keyword arguments for the plot function defined by ``plot_func``
     for plotting biases. These keyword arguments update (and potentially
     overwrite) the ``plot_kwargs`` for the bias plot. This option has no effect
     if no reference dataset is given. See option ``plot_kwargs`` for more
-    details. By default, uses ``cmap: bwr``.
+    details. By default, uses ``cmap: bwr`` and ``norm: centered``.
 pyplot_kwargs: dict, optional
     Optional calls to functions of :mod:`matplotlib.pyplot`. Dictionary keys
     are functions of :mod:`matplotlib.pyplot`. Dictionary values are used as
@@ -324,10 +331,9 @@
     ``{project}``, ``{short_name}``, ``{exp}``.  Examples: ``title: 'Awesome
     Plot of {long_name}'``, ``xlabel: '{short_name}'``, ``xlim: [0, 5]``.
 rasterize: bool, optional (default: True)
-    If ``True``, use `rasterization
-    <https://matplotlib.org/stable/gallery/misc/rasterization_demo.html>`_ for
-    profile plots to produce smaller files. This is only relevant for vector
-    graphics (e.g., ``output_file_type=pdf,svg,ps``).
+    If ``True``, use rasterization_ for profile plots to produce smaller files.
+    This is only relevant for vector graphics (e.g., ``output_file_type:
+    pdf,svg,ps``).
 show_stats: bool, optional (default: True)
     Show basic statistics on the plots.
 show_y_minor_ticklabels: bool, optional (default: False)
@@ -456,13 +462,17 @@
     ``plot_func``. String arguments can include facets in curly brackets which
     will be derived from the corresponding dataset, e.g., ``{project}``,
     ``{short_name}``, ``{exp}``. Examples: ``default: {levels: 2}, CMIP6:
-    {vmin: 200, vmax: 250}``.
+    {vmin: 200, vmax: 250}``. In addition to the normalization_ options
+    supported by the plot function, the option ``norm: centered`` can be
+    specified. In this case, the keywords ``vcenter`` and ``halfrange`` should
+    be used instead of ``vmin`` or ``vmax`` (see
+    :class:`~matplotlib.colors.CenteredNorm`).
 plot_kwargs_bias: dict, optional
     Optional keyword arguments for the plot function defined by ``plot_func``
     for plotting biases. These keyword arguments update (and potentially
     overwrite) the ``plot_kwargs`` for the bias plot. This option has no effect
     if no reference dataset is given. See option ``plot_kwargs`` for more
-    details. By default, uses ``cmap: bwr``.
+    details. By default, uses ``cmap: bwr`` and ``norm: centered``.
 pyplot_kwargs: dict, optional
     Optional calls to functions of :mod:`matplotlib.pyplot`. Dictionary keys
     are functions of :mod:`matplotlib.pyplot`. Dictionary values are used as
@@ -471,10 +481,9 @@
     ``{project}``, ``{short_name}``, ``{exp}``.  Examples: ``title: 'Awesome
     Plot of {long_name}'``, ``xlabel: '{short_name}'``, ``xlim: [0, 5]``.
 rasterize: bool, optional (default: True)
-    If ``True``, use `rasterization
-    <https://matplotlib.org/stable/gallery/misc/rasterization_demo.html>`_ for
-    profile plots to produce smaller files. This is only relevant for vector
-    graphics (e.g., ``output_file_type=pdf,svg,ps``).
+    If ``True``, use rasterization_ for profile plots to produce smaller files.
+    This is only relevant for vector graphics (e.g., ``output_file_type:
+    pdf,svg,ps``).
 show_stats: bool, optional (default: True)
     Show basic statistics on the plots.
 show_y_minor_ticklabels: bool, optional (default: False)
@@ -536,13 +545,17 @@
     ``plot_func``. String arguments can include facets in curly brackets which
     will be derived from the corresponding dataset, e.g., ``{project}``,
     ``{short_name}``, ``{exp}``. Examples: ``default: {levels: 2}, CMIP6:
-    {vmin: 200, vmax: 250}``.
+    {vmin: 200, vmax: 250}``. In addition to the normalization_ options
+    supported by the plot function, the option ``norm: centered`` can be
+    specified. In this case, the keywords ``vcenter`` and ``halfrange`` should
+    be used instead of ``vmin`` or ``vmax`` (see
+    :class:`~matplotlib.colors.CenteredNorm`).
 plot_kwargs_bias: dict, optional
     Optional keyword arguments for the plot function defined by ``plot_func``
     for plotting biases. These keyword arguments update (and potentially
     overwrite) the ``plot_kwargs`` for the bias plot. This option has no effect
     if no reference dataset is given. See option ``plot_kwargs`` for more
-    details. By default, uses ``cmap: bwr``.
+    details. By default, uses ``cmap: bwr`` and ``norm: centered``.
 pyplot_kwargs: dict, optional
     Optional calls to functions of :mod:`matplotlib.pyplot`. Dictionary keys
     are functions of :mod:`matplotlib.pyplot`. Dictionary values are used as
@@ -550,11 +563,10 @@
     curly brackets which will be derived from the corresponding dataset, e.g.,
     ``{project}``, ``{short_name}``, ``{exp}``.  Examples: ``title: 'Awesome
     Plot of {long_name}'``, ``xlabel: '{short_name}'``, ``xlim: [0, 5]``.
-rasterize: bool, optional (default: False)
-    If ``True``, use `rasterization
-    <https://matplotlib.org/stable/gallery/misc/rasterization_demo.html>`_ for
-    profile plots to produce smaller files. This is only relevant for vector
-    graphics (e.g., ``output_file_type=pdf,svg,ps``).
+rasterize: bool, optional (default: True)
+    If ``True``, use rasterization_ for profile plots to produce smaller files.
+    This is only relevant for vector graphics (e.g., ``output_file_type:
+    pdf,svg,ps``).
 show_y_minor_ticks: bool, optional (default: True)
     Show minor ticks for time on the Y axis.
 show_x_minor_ticks: bool, optional (default: True)
@@ -570,8 +582,14 @@
    anchors to share the configuration of common arguments with other monitor
    diagnostic script.
 
+.. _rasterization: https://matplotlib.org/stable/gallery/misc/
+   rasterization_demo.html
+.. _normalization: https://matplotlib.org/stable/users/explain/colors/
+   colormapnorms.html
+
 """
 import logging
+import warnings
 from copy import deepcopy
 from pathlib import Path
 from pprint import pformat
@@ -586,6 +604,7 @@
 from iris.analysis.cartography import area_weights
 from iris.coord_categorisation import add_year
 from iris.coords import AuxCoord
+from matplotlib.colors import CenteredNorm
 from matplotlib.gridspec import GridSpec
 from matplotlib.ticker import (
     AutoMinorLocator,
@@ -703,6 +722,9 @@ def __init__(self, config):
                 self.plots[plot_type]['plot_kwargs_bias'].setdefault(
                     'cmap', 'bwr'
                 )
+                self.plots[plot_type]['plot_kwargs_bias'].setdefault(
+                    'norm', 'centered'
+                )
                 if 'projection' not in self.plots[plot_type]:
                     self.plots[plot_type].setdefault('projection', 'Robinson')
                     self.plots[plot_type].setdefault(
@@ -734,6 +756,9 @@ def __init__(self, config):
                 self.plots[plot_type]['plot_kwargs_bias'].setdefault(
                     'cmap', 'bwr'
                 )
+                self.plots[plot_type]['plot_kwargs_bias'].setdefault(
+                    'norm', 'centered'
+                )
                 self.plots[plot_type].setdefault('pyplot_kwargs', {})
                 self.plots[plot_type].setdefault('rasterize', True)
                 self.plots[plot_type].setdefault('show_stats', True)
@@ -776,6 +801,9 @@ def __init__(self, config):
                 self.plots[plot_type].setdefault('plot_kwargs_bias', {})
                 self.plots[plot_type]['plot_kwargs_bias'].setdefault(
                     'cmap', 'bwr')
+                self.plots[plot_type]['plot_kwargs_bias'].setdefault(
+                    'norm', 'centered'
+                )
                 self.plots[plot_type].setdefault('pyplot_kwargs', {})
                 self.plots[plot_type].setdefault('rasterize', True)
                 self.plots[plot_type].setdefault('show_stats', True)
@@ -802,8 +830,11 @@ def __init__(self, config):
                 self.plots[plot_type]['plot_kwargs_bias'].setdefault(
                     'cmap', 'bwr'
                 )
+                self.plots[plot_type]['plot_kwargs_bias'].setdefault(
+                    'norm', 'centered'
+                )
                 self.plots[plot_type].setdefault('pyplot_kwargs', {})
-                self.plots[plot_type].setdefault('rasterize', False)
+                self.plots[plot_type].setdefault('rasterize', True)
                 self.plots[plot_type].setdefault(
                     'show_y_minor_ticks', True
                 )
@@ -1043,6 +1074,13 @@ def _get_plot_kwargs(self, plot_type, dataset, bias=False):
                          'variable_vs_lat'):
             plot_kwargs.setdefault('label', label)
 
+        if plot_kwargs.get('norm') == 'centered':
+            norm = CenteredNorm(
+                vcenter=plot_kwargs.pop('vcenter', 0.0),
+                halfrange=plot_kwargs.pop('halfrange', None),
+            )
+            plot_kwargs['norm'] = norm
+
         return deepcopy(plot_kwargs)
 
     def _load_and_preprocess_data(self):
@@ -2485,7 +2523,14 @@ def compute(self):
 def main():
     """Run diagnostic."""
     with run_diagnostic() as config:
-        MultiDatasets(config).compute()
+        with warnings.catch_warnings():
+            warnings.filterwarnings(
+                'ignore',
+                message="Using DEFAULT_SPHERICAL_EARTH_RADIUS",
+                category=UserWarning,
+                module='iris',
+            )
+            MultiDatasets(config).compute()
 
 
 if __name__ == '__main__':

From 7473e8ba8a61ef679529d08deca062ff09a6c5d0 Mon Sep 17 00:00:00 2001
From: Romain Beucher <romain.beucher@anu.edu.au>
Date: Tue, 14 Nov 2023 23:22:07 +1100
Subject: [PATCH 76/93] Update Obs4MIPs names in perfmetrics_CMIP5 (#3325)

Co-authored-by: Klaus Zimmermann <klaus.zimmermann@smhi.se>
---
 .../recipes/recipe_perfmetrics_CMIP5.yml      | 26 +++++++------------
 .../recipes/recipe_perfmetrics_CMIP5_4cds.yml | 16 ++++++------
 .../recipes/recipe_perfmetrics_land_CMIP5.yml | 23 ++++++----------
 3 files changed, 26 insertions(+), 39 deletions(-)

diff --git a/esmvaltool/recipes/recipe_perfmetrics_CMIP5.yml b/esmvaltool/recipes/recipe_perfmetrics_CMIP5.yml
index ee7c8e96e1..f1ff96eb64 100644
--- a/esmvaltool/recipes/recipe_perfmetrics_CMIP5.yml
+++ b/esmvaltool/recipes/recipe_perfmetrics_CMIP5.yml
@@ -613,7 +613,7 @@ diagnostics:
     variables:
       pr:
         preprocessor: ppNOLEV1
-        reference_dataset: GPCP-SG
+        reference_dataset: GPCP-V2.2
         mip: Amon
         project: CMIP5
         exp: historical
@@ -670,8 +670,7 @@ diagnostics:
       - {dataset: MRI-ESM1}
       - {dataset: NorESM1-M}
       - {dataset: NorESM1-ME}
-      - {dataset: GPCP-SG, project: obs4MIPs, level: L3,
-         version: v2.2, tier: 1}
+      - {dataset: GPCP-V2.2, project: obs4MIPs, level: L3, tier: 1}
     scripts:
       grading:
         <<: *grading_settings
@@ -811,8 +810,7 @@ diagnostics:
       - {dataset: MRI-CGCM3}
       - {dataset: NorESM1-M}
       - {dataset: NorESM1-ME}
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B,
-         version: Ed2-7, tier: 1}
+      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1}
     scripts:
       latlon:
         <<: *latlon_settings
@@ -883,8 +881,7 @@ diagnostics:
       - {dataset: MRI-CGCM3}
       - {dataset: NorESM1-M}
       - {dataset: NorESM1-ME}
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B,
-         version: Ed2-7, tier: 1}
+      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1}
     scripts:
       latlon:
         <<: *latlon_settings
@@ -958,8 +955,7 @@ diagnostics:
       - {dataset: MRI-CGCM3}
       - {dataset: NorESM1-M}
       - {dataset: NorESM1-ME}
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B,
-         version: Ed2-7, tier: 1}
+      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1}
     scripts:
       grading:
         <<: *grading_settings
@@ -975,7 +971,7 @@ diagnostics:
     variables:
       hus:
         preprocessor: pp400
-        reference_dataset: AIRS
+        reference_dataset: AIRS-2-1
         alternative_dataset: ERA-Interim
         mip: Amon
         project: CMIP5
@@ -1024,10 +1020,9 @@ diagnostics:
       - {dataset: MRI-ESM1}
       - {dataset: NorESM1-M}
       - {dataset: NorESM1-ME}
-      - {dataset: AIRS, project: obs4MIPs, level: L3,
-         version: RetStd-v5, tier: 1}
-      - {dataset: ERA-Interim, project: OBS6, type: reanaly,
-         version: 1, tier: 3}
+      - {dataset: AIRS-2-1, project: obs4MIPs, level: L3, tier: 1}
+      - {dataset: ERA-Interim, project: OBS6,
+         type: reanaly, version: 1, tier: 3}
     scripts:
       grading:
         <<: *grading_settings
@@ -1090,8 +1085,7 @@ diagnostics:
       - {dataset: MRI-CGCM3}
       - {dataset: NorESM1-M}
       - {dataset: NorESM1-ME}
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B,
-         version: Ed2-7, tier: 1}
+      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1}
     scripts:
       grading:
         <<: *grading_settings
diff --git a/esmvaltool/recipes/recipe_perfmetrics_CMIP5_4cds.yml b/esmvaltool/recipes/recipe_perfmetrics_CMIP5_4cds.yml
index b9e6b1ad1e..6e80cef108 100644
--- a/esmvaltool/recipes/recipe_perfmetrics_CMIP5_4cds.yml
+++ b/esmvaltool/recipes/recipe_perfmetrics_CMIP5_4cds.yml
@@ -1025,7 +1025,7 @@ diagnostics:
     variables:
       hus:
         preprocessor: pp400
-        reference_dataset: AIRS
+        reference_dataset: AIRS-2-1
         alternative_dataset: ERA-Interim
         mip: Amon
         project: CMIP5
@@ -1074,9 +1074,9 @@ diagnostics:
       - {dataset: MRI-ESM1}
       - {dataset: NorESM1-M}
       - {dataset: NorESM1-ME}
-      - {dataset: AIRS, project: obs4MIPs, level: L3, version: RetStd-v5, tier: 1}
-      - {dataset: ERA-Interim, project: OBS6, type: reanaly,
-         version: 1, tier: 3}
+      - {dataset: AIRS-2-1, project: obs4MIPs, level: L3, tier: 1}
+      - {dataset: ERA-Interim, project: OBS6,
+         type: reanaly, version: 1, tier: 3}
     scripts:
       grading:
         <<: *grading_settings
@@ -1271,7 +1271,7 @@ diagnostics:
     variables:
       pr:
         preprocessor: ppNOLEV1
-        reference_dataset: GPCP-SG
+        reference_dataset: GPCP-V2.2
         mip: Amon
         project: CMIP5
         exp: historical
@@ -1328,7 +1328,7 @@ diagnostics:
       - {dataset: MRI-ESM1}
       - {dataset: NorESM1-M}
       - {dataset: NorESM1-ME}
-      - {dataset: GPCP-SG, project: obs4MIPs, level: L3, version: v2.2, tier: 1}
+      - {dataset: GPCP-V2.2, project: obs4MIPs, level: L3, tier: 1}
     scripts:
       grading:
         <<: *grading_settings
@@ -1477,7 +1477,7 @@ diagnostics:
       - {dataset: MRI-CGCM3}
       - {dataset: NorESM1-M}
       - {dataset: NorESM1-ME}
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7, tier: 1}
+      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1}
     scripts:
       grading:
         <<: *grading_settings
@@ -1544,7 +1544,7 @@ diagnostics:
       - {dataset: MRI-CGCM3}
       - {dataset: NorESM1-M}
       - {dataset: NorESM1-ME}
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, version: Ed2-7, tier: 1}
+      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1}
     scripts:
       grading:
         <<: *grading_settings
diff --git a/esmvaltool/recipes/recipe_perfmetrics_land_CMIP5.yml b/esmvaltool/recipes/recipe_perfmetrics_land_CMIP5.yml
index 834b97e158..11ed80bbaa 100644
--- a/esmvaltool/recipes/recipe_perfmetrics_land_CMIP5.yml
+++ b/esmvaltool/recipes/recipe_perfmetrics_land_CMIP5.yml
@@ -420,7 +420,7 @@ diagnostics:
       rlus:
         short_name: rlus
         preprocessor: ppNOLEV1
-        reference_dataset: CERES-EBAF
+        reference_dataset: CERES-EBAF_Surface
         mip: Amon
         project: CMIP5
         exp: historical
@@ -460,9 +460,7 @@ diagnostics:
       - {dataset: MRI-CGCM3}
       - {dataset: NorESM1-M}
       - {dataset: NorESM1-ME}
-
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B,
-         version: Ed2-8, tier: 1, start_year: 2001, end_year: 2015}
+      - {dataset: CERES-EBAF_Surface, project: obs4MIPs, level: L3B, tier: 1, start_year: 2001, end_year: 2013}
     scripts:
       grading:
         <<: *grading_settings
@@ -478,7 +476,7 @@ diagnostics:
       rlds:
         short_name: rlds
         preprocessor: ppNOLEV1
-        reference_dataset: CERES-EBAF
+        reference_dataset: CERES-EBAF_Surface
         mip: Amon
         project: CMIP5
         exp: historical
@@ -519,9 +517,7 @@ diagnostics:
       - {dataset: MRI-CGCM3}
       - {dataset: NorESM1-M}
       - {dataset: NorESM1-ME}
-
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B,
-         version: Ed2-8, tier: 1, start_year: 2001, end_year: 2015}
+      - {dataset: CERES-EBAF_Surface, project: obs4MIPs, level: L3B, tier: 1, start_year: 2001, end_year: 2013}
     scripts:
       grading:
         <<: *grading_settings
@@ -537,7 +533,7 @@ diagnostics:
       rsus:
         short_name: rsus
         preprocessor: ppNOLEV1
-        reference_dataset: CERES-EBAF
+        reference_dataset: CERES-EBAF_Surface
         mip: Amon
         project: CMIP5
         exp: historical
@@ -577,9 +573,7 @@ diagnostics:
       - {dataset: MRI-CGCM3}
       - {dataset: NorESM1-M}
       - {dataset: NorESM1-ME}
-
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B,
-         version: Ed2-8, tier: 1, start_year: 2001, end_year: 2015}
+      - {dataset: CERES-EBAF_Surface, project: obs4MIPs, level: L3B, tier: 1, start_year: 2001, end_year: 2013}
     scripts:
       grading:
         <<: *grading_settings
@@ -595,7 +589,7 @@ diagnostics:
       rsds:
         short_name: rsds
         preprocessor: ppNOLEV1
-        reference_dataset: CERES-EBAF
+        reference_dataset: CERES-EBAF_Surface
         mip: Amon
         project: CMIP5
         exp: historical
@@ -637,8 +631,7 @@ diagnostics:
       - {dataset: NorESM1-M}
       - {dataset: NorESM1-ME}
 
-      - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B,
-         version: Ed2-8, tier: 1, start_year: 2001, end_year: 2015}
+      - {dataset: CERES-EBAF_Surface, project: obs4MIPs, level: L3B, tier: 1, start_year: 2001, end_year: 2013}
     scripts:
       grading:
         <<: *grading_settings

From 5de9058fbc41f06c9bb2e32cc33b716af0a6c4bf Mon Sep 17 00:00:00 2001
From: Bouwe Andela <b.andela@esciencecenter.nl>
Date: Tue, 14 Nov 2023 13:25:48 +0100
Subject: [PATCH 77/93] Use new preprocessor statistics calling convention for
 recipe_easy_ipcc.yml (#3418)

---
 esmvaltool/diag_scripts/examples/make_plot.py    |  4 ++--
 esmvaltool/recipes/examples/recipe_easy_ipcc.yml | 10 ++++++----
 2 files changed, 8 insertions(+), 6 deletions(-)

diff --git a/esmvaltool/diag_scripts/examples/make_plot.py b/esmvaltool/diag_scripts/examples/make_plot.py
index b2aa4158f5..796d55cd49 100644
--- a/esmvaltool/diag_scripts/examples/make_plot.py
+++ b/esmvaltool/diag_scripts/examples/make_plot.py
@@ -42,8 +42,8 @@ def main(cfg):
             label=labels.get(exp, exp),
         )
 
-        p17 = iris.load_cube(group['MultiModelP17'])
-        p83 = iris.load_cube(group['MultiModelP83'])
+        p17 = iris.load_cube(group['MultiModelPercentile17'])
+        p83 = iris.load_cube(group['MultiModelPercentile83'])
         time_coord = mean.coord('time')
         time_axis = time_coord.units.num2date(time_coord.core_points())
         plt.fill_between(
diff --git a/esmvaltool/recipes/examples/recipe_easy_ipcc.yml b/esmvaltool/recipes/examples/recipe_easy_ipcc.yml
index 7f5696e2b9..40040e2835 100644
--- a/esmvaltool/recipes/examples/recipe_easy_ipcc.yml
+++ b/esmvaltool/recipes/examples/recipe_easy_ipcc.yml
@@ -29,12 +29,14 @@ preprocessors:
       units: 'degrees_C'
     ensemble_statistics:
       statistics:
-        - mean
+        - operator: mean
     multi_model_statistics:
       statistics:
-        - mean
-        - p17
-        - p83
+        - operator: mean
+        - operator: percentile
+          percent: 17
+        - operator: percentile
+          percent: 83
       span: full
       keep_input_datasets: false
       ignore_scalar_coords: true

From f16c7eab77b78cfc4f74b9c0bd3d6f1d8533ee58 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Tue, 14 Nov 2023 16:57:42 +0000
Subject: [PATCH 78/93] [Condalock] Update Linux condalock file (#3413)

Co-authored-by: valeriupredoi <valeriupredoi@users.noreply.github.com>
---
 conda-linux-64.lock | 51 +++++++++++++++++++++++----------------------
 1 file changed, 26 insertions(+), 25 deletions(-)

diff --git a/conda-linux-64.lock b/conda-linux-64.lock
index d920179e15..b50b8be803 100644
--- a/conda-linux-64.lock
+++ b/conda-linux-64.lock
@@ -1,6 +1,6 @@
 # Generated by conda-lock.
 # platform: linux-64
-# input_hash: 27f8b0ad520a2e8cf3b93380288b4e9bdaaeafa07cffd2dc081bd3cbdb3fec11
+# input_hash: 05ccb0eb21a22bcda85523e4fc91a3c5d43c69b2fc56e17f5c81159b2e906d6b
 @EXPLICIT
 https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2#d7c89558ba9fa0495403155b64376d81
 https://conda.anaconda.org/conda-forge/linux-64/_py-xgboost-mutex-2.0-gpu_0.tar.bz2#7702188077361f43a4d61e64c694f850
@@ -29,7 +29,7 @@ https://conda.anaconda.org/conda-forge/noarch/fonts-conda-ecosystem-1-0.tar.bz2#
 https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-13.2.0-h807b86a_2.conda#c28003b0be0494f9a7664389146716ff
 https://conda.anaconda.org/conda-forge/linux-64/aom-3.5.0-h27087fc_0.tar.bz2#a08150fd2298460cd1fcccf626305642
 https://conda.anaconda.org/conda-forge/linux-64/aws-c-common-0.8.23-hd590300_0.conda#cc4f06f7eedb1523f3b83fd0fb3942ff
-https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-h7f98852_4.tar.bz2#a1fd65c7ccbf10880423d82bca54eb54
+https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hd590300_5.conda#69b8b6202a07720f448be700e300ccf4
 https://conda.anaconda.org/conda-forge/linux-64/c-ares-1.21.0-hd590300_0.conda#c06fa0440048270817b9e3142cc661bf
 https://conda.anaconda.org/conda-forge/linux-64/charls-2.4.2-h59595ed_0.conda#4336bd67920dd504cd8c6761d6a99645
 https://conda.anaconda.org/conda-forge/linux-64/dav1d-1.2.1-hd590300_0.conda#418c6ca5929a611cbd69204907a83995
@@ -40,7 +40,7 @@ https://conda.anaconda.org/conda-forge/linux-64/gettext-0.21.1-h27087fc_0.tar.bz
 https://conda.anaconda.org/conda-forge/linux-64/gflags-2.2.2-he1b5a44_1004.tar.bz2#cddaf2c63ea4a5901cf09524c490ecdc
 https://conda.anaconda.org/conda-forge/linux-64/ghostscript-10.02.1-h59595ed_0.conda#3750ef83be92ff8de6e44da80d509847
 https://conda.anaconda.org/conda-forge/linux-64/giflib-5.2.1-h0b41bf4_3.conda#96f3b11872ef6fad973eac856cd2624f
-https://conda.anaconda.org/conda-forge/linux-64/gmp-6.2.1-h58526e2_0.tar.bz2#b94cf2db16066b242ebd26db2facbd56
+https://conda.anaconda.org/conda-forge/linux-64/gmp-6.3.0-h59595ed_0.conda#0e33ef437202db431aa5a928248cf2e8
 https://conda.anaconda.org/conda-forge/linux-64/graphite2-1.3.13-h58526e2_1001.tar.bz2#8c54672728e8ec6aa6db90cf2806d220
 https://conda.anaconda.org/conda-forge/linux-64/icu-72.1-hcb278e6_0.conda#7c8d20d847bb45f56bd941578fcfa146
 https://conda.anaconda.org/conda-forge/linux-64/jbig-2.1-h7f98852_2003.tar.bz2#1aa0cee79792fa97b7ff4545110b60bf
@@ -120,7 +120,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libevent-2.1.12-hf998b51_1.conda
 https://conda.anaconda.org/conda-forge/linux-64/libgfortran-ng-13.2.0-h69a702a_2.conda#e75a75a6eaf6f318dae2631158c46575
 https://conda.anaconda.org/conda-forge/linux-64/libkml-1.3.0-h01aab08_1016.conda#4d0907546d556ef7f14b1dcfa0e217ce
 https://conda.anaconda.org/conda-forge/linux-64/libllvm14-14.0.6-hcd5def8_4.conda#73301c133ded2bf71906aa2104edae8b
-https://conda.anaconda.org/conda-forge/linux-64/libnghttp2-1.55.1-h47da74e_0.conda#a802251d1eaeeae041c867faf0f94fa8
+https://conda.anaconda.org/conda-forge/linux-64/libnghttp2-1.58.0-h47da74e_0.conda#9b13d5ee90fc9f09d54fd403247342b4
 https://conda.anaconda.org/conda-forge/linux-64/libpng-1.6.39-h753d276_0.conda#e1c890aebdebbfbf87e2c917187b4416
 https://conda.anaconda.org/conda-forge/linux-64/libprotobuf-4.23.3-hd1fb520_1.conda#78c10e8637a6f8d377f9989327d0267d
 https://conda.anaconda.org/conda-forge/linux-64/librttopo-1.1.0-h0d5128d_13.conda#e1d6139ff0500977a760567a4bec1ce9
@@ -149,7 +149,7 @@ https://conda.anaconda.org/conda-forge/linux-64/blosc-1.21.5-h0f2a231_0.conda#00
 https://conda.anaconda.org/conda-forge/linux-64/boost-cpp-1.78.0-h6582d0a_3.conda#d3c3c7698d0b878aab1b86db95407c8e
 https://conda.anaconda.org/conda-forge/linux-64/brotli-bin-1.0.9-h166bdaf_9.conda#d47dee1856d9cb955b8076eeff304a5b
 https://conda.anaconda.org/conda-forge/linux-64/bwidget-1.9.14-ha770c72_1.tar.bz2#5746d6202ba2abad4a4707f2a2462795
-https://conda.anaconda.org/conda-forge/linux-64/c-blosc2-2.11.1-hb4ffafa_0.conda#c898b02b6ed79db692e6a85f7bdba176
+https://conda.anaconda.org/conda-forge/linux-64/c-blosc2-2.11.2-hb4ffafa_0.conda#aa776e4716e54633d1279cf7599c3711
 https://conda.anaconda.org/conda-forge/linux-64/fftw-3.3.10-nompi_hc118613_108.conda#6fa90698000b05dfe8ce6515794fe71a
 https://conda.anaconda.org/conda-forge/linux-64/freetype-2.12.1-h267a509_2.conda#9ae35c3d96db2c94ce0cef86efdfa2cb
 https://conda.anaconda.org/conda-forge/linux-64/gfortran_impl_linux-64-13.2.0-h76e1118_2.conda#4983e17132a8fac913475db6e7aba288
@@ -158,7 +158,7 @@ https://conda.anaconda.org/conda-forge/linux-64/hdfeos2-2.20-hebf79cf_1003.conda
 https://conda.anaconda.org/conda-forge/linux-64/krb5-1.20.1-h81ceb04_0.conda#89a41adce7106749573d883b2f657d78
 https://conda.anaconda.org/conda-forge/linux-64/libarchive-3.6.2-h039dbb9_1.conda#29cf970521d30d113f3425b84cb250f6
 https://conda.anaconda.org/conda-forge/linux-64/libgit2-1.5.1-h1f77430_0.conda#16802fd0c80290248ea79a570bd83b95
-https://conda.anaconda.org/conda-forge/linux-64/libglib-2.78.0-hebfc3b9_0.conda#e618003da3547216310088478e475945
+https://conda.anaconda.org/conda-forge/linux-64/libglib-2.78.1-hebfc3b9_0.conda#ddd09e8904fde46b85f41896621803e6
 https://conda.anaconda.org/conda-forge/linux-64/libgrpc-1.56.2-h3905398_1.conda#0b01e6ff8002994bd4ddbffcdbec7856
 https://conda.anaconda.org/conda-forge/linux-64/libhwloc-2.9.3-default_h554bfaf_1009.conda#f36ddc11ca46958197a45effdd286e45
 https://conda.anaconda.org/conda-forge/linux-64/libopenblas-0.3.24-pthreads_h413a1c8_0.conda#6e4ef6ca28655124dcde9bd500e44c32
@@ -228,7 +228,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libblas-3.9.0-19_linux64_openbla
 https://conda.anaconda.org/conda-forge/linux-64/libcurl-8.1.2-h409715c_0.conda#50c873c9660ed116707ae15b663928d8
 https://conda.anaconda.org/conda-forge/linux-64/libpq-15.3-hbcd7760_1.conda#8afb2a97d256ffde95b91a6283bc598c
 https://conda.anaconda.org/conda-forge/linux-64/libwebp-1.3.1-hbf2b3c1_0.conda#4963f3f12db45a576f2b8fbe9a0b8569
-https://conda.anaconda.org/conda-forge/linux-64/llvmlite-0.40.1-py311ha6695c7_0.conda#7a2b62d839516ba0cf56717e902229f4
+https://conda.anaconda.org/conda-forge/linux-64/llvmlite-0.41.1-py311ha6695c7_0.conda#60fa8c1f3fb0d99dd10a9af2aff9c400
 https://conda.anaconda.org/conda-forge/noarch/locket-1.0.0-pyhd8ed1ab_0.tar.bz2#91e27ef3d05cc772ce627e51cff111c4
 https://conda.anaconda.org/conda-forge/linux-64/lxml-4.9.3-py311h1a07684_1.conda#aab51e50d994e58efdfa5382139b0468
 https://conda.anaconda.org/conda-forge/linux-64/lz4-4.3.2-py311h38e4bf4_1.conda#f8e0b648d77bbe44d1fe8af8cc56a590
@@ -288,14 +288,14 @@ https://conda.anaconda.org/conda-forge/noarch/tomlkit-0.12.2-pyha770c72_0.conda#
 https://conda.anaconda.org/conda-forge/noarch/toolz-0.12.0-pyhd8ed1ab_0.tar.bz2#92facfec94bc02d6ccf42e7173831a36
 https://conda.anaconda.org/conda-forge/linux-64/tornado-6.3.3-py311h459d7ec_1.conda#a700fcb5cedd3e72d0c75d095c7a6eda
 https://conda.anaconda.org/conda-forge/noarch/traitlets-5.13.0-pyhd8ed1ab_0.conda#8a9953c15e1e5a7c1baddbbf4511a567
-https://conda.anaconda.org/conda-forge/noarch/trove-classifiers-2023.10.18-pyhd8ed1ab_0.conda#5e2b0a292b9a3adb1c412a1e361b8e69
+https://conda.anaconda.org/conda-forge/noarch/trove-classifiers-2023.11.9-pyhd8ed1ab_0.conda#b9969f8fbfe372b437f794598c235601
 https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.8.0-pyha770c72_0.conda#5b1be40a26d10a06f6d4f1f9e19fa0c7
 https://conda.anaconda.org/conda-forge/linux-64/ujson-5.8.0-py311hb755f60_0.conda#91e67c62c48444e4efc08fb61835abe8
 https://conda.anaconda.org/conda-forge/noarch/untokenize-0.1.1-py_0.tar.bz2#1447ead40f2a01733a9c8dfc32988375
 https://conda.anaconda.org/conda-forge/noarch/webencodings-0.5.1-pyhd8ed1ab_2.conda#daf5160ff9cde3a468556965329085b9
 https://conda.anaconda.org/conda-forge/noarch/webob-1.8.7-pyhd8ed1ab_0.tar.bz2#a8192f3585f341ea66c60c189580ac67
 https://conda.anaconda.org/conda-forge/noarch/wheel-0.41.3-pyhd8ed1ab_0.conda#3fc026b9c87d091c4b34a6c997324ae8
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+https://conda.anaconda.org/conda-forge/linux-64/wrapt-1.16.0-py311h459d7ec_0.conda#6669b5529d206c1f880b642cdd17ae05
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 https://conda.anaconda.org/conda-forge/noarch/prospector-1.10.3-pyhd8ed1ab_0.conda#f551d4d859a1d70c6abff8310a655481
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+https://conda.anaconda.org/conda-forge/noarch/pyarrow-hotfix-0.4-pyhd8ed1ab_0.conda#1df0207f975470fb5234cdd099b9b577
 https://conda.anaconda.org/conda-forge/noarch/python-cdo-1.6.0-pyhd8ed1ab_0.conda#3fd1a0b063c1fbbe4b7bd5a5a7601e84
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@@ -623,8 +623,8 @@ https://conda.anaconda.org/conda-forge/noarch/r-scales-1.2.1-r41hc72bb7e_1.tar.b
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-https://conda.anaconda.org/conda-forge/noarch/nbconvert-7.10.0-pyhd8ed1ab_0.conda#800568b9c39cfd87a2a6a9a0488ea265
+https://conda.anaconda.org/conda-forge/noarch/dask-2023.11.0-pyhd8ed1ab_0.conda#b77d7b91f78b3c50cceb19eb1611a6cf
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@@ -634,9 +634,10 @@ https://conda.anaconda.org/conda-forge/noarch/r-pillar-1.9.0-r41hc72bb7e_0.conda
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+https://conda.anaconda.org/conda-forge/noarch/iris-esmf-regrid-0.9.0-pyhd8ed1ab_0.conda#570f2c6e387fd6dac5356a5152f91b3f
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From d07cf3bdf6670245a4288d61af9a9173bc566a94 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Tue, 21 Nov 2023 13:28:55 +0000
Subject: [PATCH 79/93] [Condalock] Update Linux condalock file (#3432)

Co-authored-by: valeriupredoi <valeriupredoi@users.noreply.github.com>
---
 conda-linux-64.lock | 76 ++++++++++++++++++++++-----------------------
 1 file changed, 38 insertions(+), 38 deletions(-)

diff --git a/conda-linux-64.lock b/conda-linux-64.lock
index b50b8be803..42d1ec03fc 100644
--- a/conda-linux-64.lock
+++ b/conda-linux-64.lock
@@ -5,7 +5,7 @@
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 https://conda.anaconda.org/conda-forge/noarch/sparse-0.14.0-pyhd8ed1ab_0.conda#ee01b310177a0612554b9d20e537fdbe
 https://conda.anaconda.org/conda-forge/noarch/tifffile-2023.9.26-pyhd8ed1ab_0.conda#d133bea7d8ac17552492a0629229eeb1
-https://conda.anaconda.org/conda-forge/noarch/xarray-2023.10.1-pyhd8ed1ab_0.conda#9b20e5d68eea6878a0a6fc57a3043889
+https://conda.anaconda.org/conda-forge/noarch/xarray-2023.11.0-pyhd8ed1ab_0.conda#f445b20bac3db8f604a48592087b2d8f
 https://conda.anaconda.org/conda-forge/noarch/zarr-2.16.1-pyhd8ed1ab_0.conda#59ec835edbee50266b7bdbadab7ba335
 https://conda.anaconda.org/conda-forge/linux-64/cartopy-0.22.0-py311h320fe9a_1.conda#10d1806e20da040c58c36deddf51c70c
 https://conda.anaconda.org/conda-forge/noarch/cf_xarray-0.8.6-pyhd8ed1ab_0.conda#2e33e3bdf2b1a79989ad792ac22104d3
@@ -490,7 +490,7 @@ https://conda.anaconda.org/conda-forge/noarch/nc-time-axis-1.4.1-pyhd8ed1ab_0.ta
 https://conda.anaconda.org/conda-forge/linux-64/ncl-6.6.2-hf70af60_47.conda#ee27133164cb9f5e74681bdb8839688f
 https://conda.anaconda.org/conda-forge/linux-64/nco-5.1.6-hd62b316_0.conda#af7780f76ee37325d264327e21a478f5
 https://conda.anaconda.org/conda-forge/linux-64/psyplot-1.4.3-py311h38be061_1.tar.bz2#f0c9a1067c03e8f05e53ef0c5ad5fab3
-https://conda.anaconda.org/conda-forge/linux-64/py-xgboost-1.7.6-cuda118_py311had8614c_5.conda#773ca1174fd4cddb6f7ddc129fa78b90
+https://conda.anaconda.org/conda-forge/linux-64/py-xgboost-1.7.6-cuda118_py311h0be3a32_6.conda#e9989e03af742084940a11c7c3c395a5
 https://conda.anaconda.org/conda-forge/noarch/pylint-celery-0.3-py_1.tar.bz2#e29456a611a62d3f26105a2f9c68f759
 https://conda.anaconda.org/conda-forge/noarch/pylint-django-2.5.3-pyhd8ed1ab_0.tar.bz2#00d8853fb1f87195722ea6a582cc9b56
 https://conda.anaconda.org/conda-forge/noarch/pylint-flask-0.6-py_0.tar.bz2#5a9afd3d0a61b08d59eed70fab859c1b
@@ -599,12 +599,12 @@ https://conda.anaconda.org/conda-forge/linux-64/r-xml2-1.3.4-r41h1ad5fc0_1.conda
 https://conda.anaconda.org/conda-forge/linux-64/r-zoo-1.8_12-r41h133d619_0.conda#1d432d2eba171727afd03507faa5e2f6
 https://conda.anaconda.org/conda-forge/noarch/seaborn-0.13.0-hd8ed1ab_0.conda#ebd31a95a7008b7e164dad9dbbb5bb5a
 https://conda.anaconda.org/conda-forge/noarch/xesmf-0.8.2-pyhd8ed1ab_0.conda#8e765a0eca0ce1cfa889cd9af82a23a8
-https://conda.anaconda.org/conda-forge/linux-64/xgboost-1.7.6-cuda118_py311had8614c_5.conda#75abf6b4513743cb4c8be4715a55f17b
+https://conda.anaconda.org/conda-forge/linux-64/xgboost-1.7.6-cuda118_py311h0be3a32_6.conda#f061993f8ed8ca90d2bb6a547a47109f
 https://conda.anaconda.org/conda-forge/noarch/nbconvert-pandoc-7.11.0-pyhd8ed1ab_0.conda#51bd005efab7e5c5c2af2570327bd213
 https://conda.anaconda.org/conda-forge/noarch/prov-2.0.0-pyhd3deb0d_0.tar.bz2#aa9b3ad140f6c0668c646f32e20ccf82
 https://conda.anaconda.org/conda-forge/noarch/psy-maps-1.4.2-pyhd8ed1ab_0.tar.bz2#3ed13103dfd46f71dc870d188bd0b276
 https://conda.anaconda.org/conda-forge/linux-64/psy-reg-1.4.0-py311h38be061_3.conda#6f7871722c07922028043144e8873b37
-https://conda.anaconda.org/conda-forge/noarch/pyarrow-hotfix-0.4-pyhd8ed1ab_0.conda#1df0207f975470fb5234cdd099b9b577
+https://conda.anaconda.org/conda-forge/noarch/pyarrow-hotfix-0.5-pyhd8ed1ab_0.conda#a172245c7fdb6696f2ab357501e6d13e
 https://conda.anaconda.org/conda-forge/noarch/python-cdo-1.6.0-pyhd8ed1ab_0.conda#3fd1a0b063c1fbbe4b7bd5a5a7601e84
 https://conda.anaconda.org/conda-forge/linux-64/r-akima-0.6_2.3-r41h92ddd45_0.tar.bz2#bac0b7627ef744c98f4bc48885f52e72
 https://conda.anaconda.org/conda-forge/noarch/r-callr-3.7.3-r41hc72bb7e_0.tar.bz2#af0891cc9b87e2954c9a3c66f144992d
@@ -652,7 +652,7 @@ https://conda.anaconda.org/conda-forge/noarch/r-lintr-3.0.2-r41hc72bb7e_0.tar.bz
 https://conda.anaconda.org/conda-forge/noarch/r-s2dverification-2.10.3-r41hc72bb7e_1.tar.bz2#2253f130c8dab435824d6ddb10a41c73
 https://conda.anaconda.org/conda-forge/noarch/autodocsumm-0.2.6-pyhd8ed1ab_0.tar.bz2#4409dd7e06a62c3b2aa9e96782c49c6d
 https://conda.anaconda.org/conda-forge/noarch/nbsphinx-0.9.3-pyhd8ed1ab_0.conda#0dbaa7d08d3d79b2a1a4dd6a02cc4581
-https://conda.anaconda.org/conda-forge/noarch/pydata-sphinx-theme-0.14.3-pyhd8ed1ab_0.conda#3a52e29fde69705040bcbe74cbdcbd5c
+https://conda.anaconda.org/conda-forge/noarch/pydata-sphinx-theme-0.14.3-pyhd8ed1ab_1.conda#fbe2993dd48f14724b90bf12e92cc164
 https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-applehelp-1.0.7-pyhd8ed1ab_0.conda#aebfabcb60c33a89c1f9290cab49bc93
 https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-devhelp-1.0.5-pyhd8ed1ab_0.conda#ebf08f5184d8eaa486697bc060031953
 https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-htmlhelp-2.0.4-pyhd8ed1ab_0.conda#a9a89000dfd19656ad004b937eeb6828

From 1647d46ee3c5deb084fa4ac59024a46581d618c3 Mon Sep 17 00:00:00 2001
From: Manuel Schlund <32543114+schlunma@users.noreply.github.com>
Date: Wed, 22 Nov 2023 14:27:58 +0100
Subject: [PATCH 80/93] Fixed plot paths in NCL provenance tracking (#3422)

Co-authored-by: Klaus Zimmermann <klaus.zimmermann@smhi.se>
---
 esmvaltool/diag_scripts/austral_jet/asr.ncl    |  2 +-
 esmvaltool/diag_scripts/austral_jet/main.ncl   |  2 +-
 .../diag_scripts/carbon_ec/carbon_beta.ncl     |  6 +-----
 .../carbon_ec/carbon_co2_cycle.ncl             |  6 +-----
 .../carbon_ec/carbon_constraint.ncl            |  2 +-
 .../carbon_ec/carbon_gammaHist.ncl             |  2 +-
 .../ch12_calc_IAV_for_stippandhatch.ncl        |  3 +--
 .../diag_scripts/mder/select_for_mder.ncl      |  2 +-
 .../diag_scripts/perfmetrics/collect.ncl       |  5 +++--
 .../russell18jgr/russell18jgr-fig2.ncl         |  2 +-
 .../russell18jgr/russell18jgr-fig3b-2.ncl      |  2 +-
 .../russell18jgr/russell18jgr-fig3b.ncl        |  2 +-
 .../russell18jgr/russell18jgr-fig4.ncl         |  2 +-
 .../russell18jgr/russell18jgr-fig5.ncl         |  2 +-
 .../russell18jgr/russell18jgr-fig5g.ncl        |  2 +-
 .../russell18jgr/russell18jgr-fig6a.ncl        |  2 +-
 .../russell18jgr/russell18jgr-fig6b.ncl        |  2 +-
 .../russell18jgr/russell18jgr-fig7h.ncl        |  2 +-
 .../russell18jgr/russell18jgr-fig7i.ncl        |  2 +-
 .../russell18jgr/russell18jgr-fig9a.ncl        |  2 +-
 .../russell18jgr/russell18jgr-fig9b.ncl        |  2 +-
 .../russell18jgr/russell18jgr-fig9c.ncl        |  2 +-
 .../russell18jgr/russell18jgr-polar.ncl        |  2 +-
 .../tebaldi21esd/calc_IAV_hatching.ncl         |  3 +--
 .../diag_scripts/xco2_analysis/delta_T.ncl     |  2 +-
 .../diag_scripts/xco2_analysis/global_maps.ncl |  4 ++--
 esmvaltool/diag_scripts/xco2_analysis/main.ncl |  6 +++---
 .../diag_scripts/xco2_analysis/panel_plots.ncl |  4 ++--
 .../diag_scripts/xco2_analysis/sat_masks.ncl   |  4 ++--
 .../xco2_analysis/station_comparison.ncl       |  6 +++---
 esmvaltool/interface_scripts/logging.ncl       | 18 +++++++++++++++++-
 31 files changed, 56 insertions(+), 49 deletions(-)

diff --git a/esmvaltool/diag_scripts/austral_jet/asr.ncl b/esmvaltool/diag_scripts/austral_jet/asr.ncl
index c12b66f166..5d855ad393 100644
--- a/esmvaltool/diag_scripts/austral_jet/asr.ncl
+++ b/esmvaltool/diag_scripts/austral_jet/asr.ncl
@@ -289,7 +289,7 @@ begin
     work_dir = output@work_dir
     opt = diag_script_info
     log_info(opt@wdiag)
-    plot_path = "missing"
+    plot_path = "n/a"
     plot_type = ""
 
     ; Iterate over all datasets
diff --git a/esmvaltool/diag_scripts/austral_jet/main.ncl b/esmvaltool/diag_scripts/austral_jet/main.ncl
index 446133e1d5..c078830687 100644
--- a/esmvaltool/diag_scripts/austral_jet/main.ncl
+++ b/esmvaltool/diag_scripts/austral_jet/main.ncl
@@ -731,7 +731,7 @@ begin
   if (output) then
     work_dir := output@work_dir
     opt = diag_script_info
-    plot_path = "missing"
+    plot_path = "n/a"
     plot_type = ""
 
     ; Iterate over all desired diagnostics
diff --git a/esmvaltool/diag_scripts/carbon_ec/carbon_beta.ncl b/esmvaltool/diag_scripts/carbon_ec/carbon_beta.ncl
index eb43b10cd3..0d6319ea85 100644
--- a/esmvaltool/diag_scripts/carbon_ec/carbon_beta.ncl
+++ b/esmvaltool/diag_scripts/carbon_ec/carbon_beta.ncl
@@ -279,11 +279,7 @@ begin
   create_legend_lines(leg@annots, leg, plot_dir + \
                       DIAG_SCRIPT + "_legend", "markers")
 
-  if (file_type .ne. "png") then
-    plotname = plot_dir + plot_file + "." + file_type
-  else
-    plotname = plot_dir + plot_file + ".000001.png"
-  end if
+  plotname = plot_dir + plot_file + "." + file_type
 
   ; Call provenance logger
   log_provenance(ncdf_outfile, \
diff --git a/esmvaltool/diag_scripts/carbon_ec/carbon_co2_cycle.ncl b/esmvaltool/diag_scripts/carbon_ec/carbon_co2_cycle.ncl
index 7876ffdb62..f37b7bc23a 100644
--- a/esmvaltool/diag_scripts/carbon_ec/carbon_co2_cycle.ncl
+++ b/esmvaltool/diag_scripts/carbon_ec/carbon_co2_cycle.ncl
@@ -492,11 +492,7 @@ begin
   ; Write NetCDF output
   ncdf_outfile = ncdf_write(CO2var, new_path)
 
-  if (file_type .ne. "png") then
-    plotname = plot_dir + plot_file + "." + file_type
-  else
-    plotname = plot_dir + plot_file + ".000001.png"
-  end if
+  plotname = plot_dir + plot_file + "." + file_type
 
   ; -----------------------------------------------------------
   ; Call provenance logger
diff --git a/esmvaltool/diag_scripts/carbon_ec/carbon_constraint.ncl b/esmvaltool/diag_scripts/carbon_ec/carbon_constraint.ncl
index 94d5b8145c..61f1f5c5a3 100644
--- a/esmvaltool/diag_scripts/carbon_ec/carbon_constraint.ncl
+++ b/esmvaltool/diag_scripts/carbon_ec/carbon_constraint.ncl
@@ -331,7 +331,7 @@ begin
 
   ; Call provenance logger
   log_provenance(ncdf_outfile, \
-                 output_dir + "." + file_type, \
+                 output_dir + plot_file + "." + file_type, \
                  XStg + " vs " + YStg, \
                  (/"anomaly", "corr", "stddev"/), \
                  (/"trop", "global"/),\
diff --git a/esmvaltool/diag_scripts/carbon_ec/carbon_gammaHist.ncl b/esmvaltool/diag_scripts/carbon_ec/carbon_gammaHist.ncl
index 1479620173..589b0d72e8 100644
--- a/esmvaltool/diag_scripts/carbon_ec/carbon_gammaHist.ncl
+++ b/esmvaltool/diag_scripts/carbon_ec/carbon_gammaHist.ncl
@@ -336,7 +336,7 @@ begin
 
   ; Call provenance logger
   log_provenance(ncdf_outfile, \
-                 output_dir + "." + file_type, \
+                 output_dir + plot_file + "." + file_type, \
                  XStg + " vs " + YStg, \
                  (/"anomaly", "corr", "stddev"/), \
                  (/"trop", "global"/),\
diff --git a/esmvaltool/diag_scripts/ipcc_ar5/ch12_calc_IAV_for_stippandhatch.ncl b/esmvaltool/diag_scripts/ipcc_ar5/ch12_calc_IAV_for_stippandhatch.ncl
index df1ea2375a..e92d60ab43 100644
--- a/esmvaltool/diag_scripts/ipcc_ar5/ch12_calc_IAV_for_stippandhatch.ncl
+++ b/esmvaltool/diag_scripts/ipcc_ar5/ch12_calc_IAV_for_stippandhatch.ncl
@@ -410,7 +410,6 @@ begin
 
   ; collect meta-data
   nc_file = ncdf_outfile
-  plot_file = work_dir + "/None"
   caption = "Inter-annual variability based on piControl runs."
   statistics = ("var")
   domains = ("global")
@@ -418,7 +417,7 @@ begin
   authors = (/"lorenz_ruth"/)
   references = (/"collins13ipcc"/)
   infiles = metadata_att_as_array(info_items, "filename")
-  log_provenance(nc_file, plot_file, caption, statistics, domains, \
+  log_provenance(nc_file, "n/a", caption, statistics, domains, \
                  plot_types, authors, references, infiles)
 
   leave_msg(DIAG_SCRIPT, "")
diff --git a/esmvaltool/diag_scripts/mder/select_for_mder.ncl b/esmvaltool/diag_scripts/mder/select_for_mder.ncl
index 8c9198a8f6..d07cda657f 100644
--- a/esmvaltool/diag_scripts/mder/select_for_mder.ncl
+++ b/esmvaltool/diag_scripts/mder/select_for_mder.ncl
@@ -97,7 +97,7 @@ begin
   AUTHORS = (/"wenzel_sabrina", "schlund_manuel"/)
   DOMAIN = diag_script_info@domain
   PLOT_TYPE = ""
-  PLOT_FILE = "missing"
+  PLOT_FILE = "n/a"
   REFERENCES = (/"wenzel16jclim"/)
 
   ; Get reference dataset(s)
diff --git a/esmvaltool/diag_scripts/perfmetrics/collect.ncl b/esmvaltool/diag_scripts/perfmetrics/collect.ncl
index 503a9c50d8..a2b14ab733 100644
--- a/esmvaltool/diag_scripts/perfmetrics/collect.ncl
+++ b/esmvaltool/diag_scripts/perfmetrics/collect.ncl
@@ -502,8 +502,9 @@ begin
   domains = (/"global"/)
 
   ; Call provenance logger
-  log_provenance(ncdf_outfile, plotpath, caption, statistics, domains, \
-                 plottype, authors, references, data_files)
+  log_provenance(ncdf_outfile, plotpath + "." + file_type, caption, \
+                 statistics, domains, plottype, authors, references, \
+                 data_files)
 
   leave_msg(DIAG_SCRIPT, "")
 
diff --git a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig2.ncl b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig2.ncl
index aa0db4d6a6..034d3a1287 100644
--- a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig2.ncl
+++ b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig2.ncl
@@ -158,7 +158,7 @@ begin
 
   ; Call provenance logger
   log_provenance(ncdf_outfile, \
-                 plotpath, \
+                 plotpath + "." + output_type(), \
                  "Russell et al 2018 figure 2", \
                  "mean", \
                  "sh", \
diff --git a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig3b-2.ncl b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig3b-2.ncl
index c182468947..c912663321 100644
--- a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig3b-2.ncl
+++ b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig3b-2.ncl
@@ -274,7 +274,7 @@ begin
     delete(last_index)
     delete(out_var)
     log_provenance(ncdf_outfile, \
-                   plotpath, \
+                   plotpath + "." + output_type(), \
                    "Russell et al 2018 figure 3b part 2", \
                    "mean", \
                    "sh",   \
diff --git a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig3b.ncl b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig3b.ncl
index 0b6b9d155f..fd4cf3f43b 100644
--- a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig3b.ncl
+++ b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig3b.ncl
@@ -264,7 +264,7 @@ begin
     delete(last_index)
     delete(out_var)
     log_provenance(ncdf_outfile, \
-                   plotpath, \
+                   plotpath + "." + output_type(), \
                    "Russell et al 2018 figure 3b", \
                    "mean", \
                    "sh", \
diff --git a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig4.ncl b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig4.ncl
index 10f94a62b2..4e62c7b552 100644
--- a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig4.ncl
+++ b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig4.ncl
@@ -368,7 +368,7 @@ begin
     delete(totaltransport)
     ; Call provenance logger
     log_provenance(ncdf_outfile, \
-                   plotpath, \
+                   plotpath + "." + file_type, \
                    "Russell et al 2018 figure 4", \
                    "mean", \
                    "sh", \
diff --git a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig5.ncl b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig5.ncl
index bddd26791b..5a60ea03d9 100644
--- a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig5.ncl
+++ b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig5.ncl
@@ -169,7 +169,7 @@ begin
     delete(dataset)
 
     log_provenance(ncdf_outfile, \
-                   plotpath, \
+                   plotpath + "." + output_type(), \
                    "Russell et al 2018 figure 5 -polar", \
                    "mean", \
                    "sh", \
diff --git a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig5g.ncl b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig5g.ncl
index 128fb25f43..67d8c53491 100644
--- a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig5g.ncl
+++ b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig5g.ncl
@@ -226,7 +226,7 @@ begin
 
     ; Call provenance logger
     log_provenance(ncdf_outfile, \
-                   plotpath, \
+                   plotpath + "." + output_type(), \
                    "Russell et al 2018 figure 5g", \
                    "mean", \
                    "sh",   \
diff --git a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig6a.ncl b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig6a.ncl
index 29bbe4ace7..206d2909cc 100644
--- a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig6a.ncl
+++ b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig6a.ncl
@@ -699,7 +699,7 @@ begin
     ncdf_outfile = ncdf_write(out_var, nc_filename)
 
     log_provenance(ncdf_outfile, \
-                   plotpath, \
+                   plotpath + "." + output_type(), \
                    "Russell et al 2018 figure 6 part a", \
                    "mean", \
                    "sh",   \
diff --git a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig6b.ncl b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig6b.ncl
index bbbf72c72d..2287b62adf 100644
--- a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig6b.ncl
+++ b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig6b.ncl
@@ -678,7 +678,7 @@ begin
     ncdf_outfile = ncdf_write(out_var, nc_filename)
 
     log_provenance(ncdf_outfile, \
-                   plotpath, \
+                   plotpath + "." + output_type(), \
                    "Russell et al 2018 figure 6b", \
                    "mean", \
                    "sh", \
diff --git a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig7h.ncl b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig7h.ncl
index 4a698f455e..249712d29f 100644
--- a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig7h.ncl
+++ b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig7h.ncl
@@ -164,7 +164,7 @@ begin
     delete(var_lon_avg)
     delete(dataset)
     log_provenance(ncdf_outfile, \
-                   plotpath, \
+                   plotpath + "." + output_type(), \
                    "Russell et al 2018 figure 7h", \
                    "mean", \
                    "sh", \
diff --git a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig7i.ncl b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig7i.ncl
index dd56bd4a41..7abcc9e7a9 100644
--- a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig7i.ncl
+++ b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig7i.ncl
@@ -202,7 +202,7 @@ begin
     end if
 
     log_provenance(ncdf_outfile, \
-                   plotpath, \
+                   plotpath + "." + output_type(), \
                    "Russell et al 2018 figure 7i", \
                    "mean", \
                    "sh", \
diff --git a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig9a.ncl b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig9a.ncl
index 99cf97b2ce..8bef8cb204 100644
--- a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig9a.ncl
+++ b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig9a.ncl
@@ -317,7 +317,7 @@ begin
     ncdf_outfile = ncdf_write(outvar, nc_filename)
 
     log_provenance(ncdf_outfile, \
-                   plotpath, \
+                   plotpath + "." + output_type(), \
                    "Russell et al 2018 figure 9a", \
                    "mean", \
                    "sh", \
diff --git a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig9b.ncl b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig9b.ncl
index bade43d9cf..8afd05425a 100644
--- a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig9b.ncl
+++ b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig9b.ncl
@@ -335,7 +335,7 @@ begin
     ncdf_outfile = ncdf_write(outvar, nc_filename)
 
     log_provenance(ncdf_outfile, \
-                   plotpath, \
+                   plotpath + "." + output_type(), \
                    "Russell et al 2018 figure 9b", \
                    "mean", \
                    "sh", \
diff --git a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig9c.ncl b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig9c.ncl
index e669bac579..0e5c828a6a 100644
--- a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig9c.ncl
+++ b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-fig9c.ncl
@@ -331,7 +331,7 @@ begin
     ncdf_outfile = ncdf_write(outvar, nc_filename)
 
     log_provenance(ncdf_outfile, \
-                   plotpath, \
+                   plotpath + "." + output_type(), \
                    "Russell et al 2018 figure 9c", \
                    "mean", \
                    "sh", \
diff --git a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-polar.ncl b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-polar.ncl
index e01771babf..b9c8f1faaa 100644
--- a/esmvaltool/diag_scripts/russell18jgr/russell18jgr-polar.ncl
+++ b/esmvaltool/diag_scripts/russell18jgr/russell18jgr-polar.ncl
@@ -232,7 +232,7 @@ begin
     ncdf_outfile = ncdf_write(dataset, nc_filename)
     delete(dataset)
     log_provenance(ncdf_outfile, \
-                   plotpath, \
+                   plotpath + "." + output_type(), \
                    "Russell et al 2018 polar plot " + var0, \
                    "mean", \
                    "sh", \
diff --git a/esmvaltool/diag_scripts/tebaldi21esd/calc_IAV_hatching.ncl b/esmvaltool/diag_scripts/tebaldi21esd/calc_IAV_hatching.ncl
index 8484a00871..f8f0d83511 100644
--- a/esmvaltool/diag_scripts/tebaldi21esd/calc_IAV_hatching.ncl
+++ b/esmvaltool/diag_scripts/tebaldi21esd/calc_IAV_hatching.ncl
@@ -399,7 +399,6 @@ begin
 
   ; collect meta-data
   nc_file = ncdf_outfile
-  plot_file = plot_dir + "/None"
   caption = "Inter-annual variability based on piControl runs."
   statistics = ("var")
   domains = ("global")
@@ -407,7 +406,7 @@ begin
   authors = (/"lorenz_ruth"/)
   references = (/"collins13ipcc"/)
   infiles = metadata_att_as_array(info_items, "filename")
-  log_provenance(nc_file, plot_file, caption, statistics, domains, \
+  log_provenance(nc_file, "n/a", caption, statistics, domains, \
                  plot_types, authors, references, infiles)
 
   leave_msg(DIAG_SCRIPT, "")
diff --git a/esmvaltool/diag_scripts/xco2_analysis/delta_T.ncl b/esmvaltool/diag_scripts/xco2_analysis/delta_T.ncl
index af7498d75b..f83f56cb31 100644
--- a/esmvaltool/diag_scripts/xco2_analysis/delta_T.ncl
+++ b/esmvaltool/diag_scripts/xco2_analysis/delta_T.ncl
@@ -332,7 +332,7 @@ begin
   ncdf_outfile = ncdf_write(delta_t_detr, outfile_netcdf_dtgr_detr)
 
   log_provenance(ncdf_outfile, \
-                 outfile_netcdf_dtgr_detr, \
+                 outfile_dtgr_detr + "." + file_type, \
                  "Sensitivity of interannual variability of " \
                  + var0 + " growth rate in the " + region + ", " + \
                  start_year + "-" + end_year + "to the interannual " \
diff --git a/esmvaltool/diag_scripts/xco2_analysis/global_maps.ncl b/esmvaltool/diag_scripts/xco2_analysis/global_maps.ncl
index 9aa205db32..d1748425d4 100644
--- a/esmvaltool/diag_scripts/xco2_analysis/global_maps.ncl
+++ b/esmvaltool/diag_scripts/xco2_analysis/global_maps.ncl
@@ -472,7 +472,7 @@ begin
 
   ; Provenance
   log_provenance(ncdf_outfile, \
-                 outfile, \
+                 outfile + "." + file_type, \
                  "Maps of mean Seasonal Cycle Amplitude of " + var0 + " " \
                  + DATASETS(imod) + " for " + start_year + "-" \
                  + end_year + ". Top: SCA with observational sampling (left)" \
@@ -587,7 +587,7 @@ begin
 
   ; Provenance
   log_provenance(ncdf_outfile, \
-                 outfile_scap, \
+                 outfile_scap + "." + file_type, \
                  "Maps of mean Seasonal Cycle Amplitude of " \
                  + var0 + " for " + start_year + "-" \
                  + end_year + ". Similar to Gier et al 2020, Fig 5.", \
diff --git a/esmvaltool/diag_scripts/xco2_analysis/main.ncl b/esmvaltool/diag_scripts/xco2_analysis/main.ncl
index 8f585e5f62..0739e52edb 100644
--- a/esmvaltool/diag_scripts/xco2_analysis/main.ncl
+++ b/esmvaltool/diag_scripts/xco2_analysis/main.ncl
@@ -438,7 +438,7 @@ begin
 
   ; Provenance
   log_provenance(ncdf_outfile, \
-                 outfile_ts_panels, \
+                 outfile_ts_panels + "." + file_type, \
                  "Timeseries, growth rate and seasonal cycle of " \
                  + var0 + " for " + region + ", " + start_year + "-" \
                  + end_year + ". Using masking: " + opt_mask \
@@ -550,7 +550,7 @@ begin
 
   ; Provenance
   log_provenance(ncdf_outfile, \
-                 outfile_grbp, \
+                 outfile_grbp + "." + file_type, \
                  "Growth Rate histogram of " \
                  + var0 + " for " + region + ", " + start_year + "-" \
                  + end_year + ". Using masking: " + opt_mask \
@@ -653,7 +653,7 @@ begin
 
   ; Provenance
   log_provenance(ncdf_outfile, \
-                 outfile_sabp, \
+                 outfile_sabp + "." + file_type, \
                  "Seasonal Cycle Amplitude histogram of " \
                  + var0 + " for " + region + ", " + start_year + "-" \
                  + end_year + ". Using masking: " + opt_mask, \
diff --git a/esmvaltool/diag_scripts/xco2_analysis/panel_plots.ncl b/esmvaltool/diag_scripts/xco2_analysis/panel_plots.ncl
index bcd4c82002..08fe30ad0f 100644
--- a/esmvaltool/diag_scripts/xco2_analysis/panel_plots.ncl
+++ b/esmvaltool/diag_scripts/xco2_analysis/panel_plots.ncl
@@ -360,7 +360,7 @@ begin
 
   ; Provenance
   log_provenance(ncdf_outfile, \
-                 outfile_scaplot, \
+                 outfile_scaplot + "." + file_type, \
                  "Trend of Seasonal Cycle Amplitude with " \
                  + var0 + " for " + region + ", " + start_year + "-" \
                  + end_year + ". Using masking: " + opt_mask \
@@ -391,7 +391,7 @@ begin
 
   ; Provenance
   log_provenance(ncdf_outfile, \
-                 outfile_grplot, \
+                 outfile_grplot + "." + file_type, \
                  "Trend of Growth Rate with " \
                  + var0 + " for " + region + ", " + start_year + "-" \
                  + end_year + ". Using masking: " + opt_mask \
diff --git a/esmvaltool/diag_scripts/xco2_analysis/sat_masks.ncl b/esmvaltool/diag_scripts/xco2_analysis/sat_masks.ncl
index c54df52d90..2bed5c74a6 100644
--- a/esmvaltool/diag_scripts/xco2_analysis/sat_masks.ncl
+++ b/esmvaltool/diag_scripts/xco2_analysis/sat_masks.ncl
@@ -258,7 +258,7 @@ begin
 
   ; Provenance
   log_provenance(ncdf_outfile, \
-                 outfile, \
+                 outfile + "." + file_type, \
                  var0 + "fractional data coverage " + start_year + "-" \
                  + end_year + ". Similar to Gier et al 2020, Fig 1.", \
                  (/"mean"/), \
@@ -377,7 +377,7 @@ begin
     delete(res)
 
     log_provenance(ncdf_outfile, \
-                   outfile_c3s, \
+                   outfile_c3s + "." + file_type, \
                    var0 + "fractional data coverage for different obs " \
                    + "periods. Similar to Gier et al 2020, Fig 8.", \
                    (/"mean"/), \
diff --git a/esmvaltool/diag_scripts/xco2_analysis/station_comparison.ncl b/esmvaltool/diag_scripts/xco2_analysis/station_comparison.ncl
index 53734d94db..23155e36fa 100644
--- a/esmvaltool/diag_scripts/xco2_analysis/station_comparison.ncl
+++ b/esmvaltool/diag_scripts/xco2_analysis/station_comparison.ncl
@@ -285,7 +285,7 @@ begin
 
     ; Provenance
     log_provenance(ncdf_outfile, \
-                   outfile_stations_masked, \
+                   outfile_stations_masked + "." + file_type, \
                    "Time series of station " + station_array&station(istat) \
                    + ", dotted denoting areas masked like observations.", \
                    (/""/), \
@@ -334,7 +334,7 @@ begin
 
     ; Provenance
     log_provenance(ncdf_outfile, \
-                   outfile_stations_obs, \
+                   outfile_stations_obs + "." + file_type, \
                    "Time series of station " + station_array&station(istat) \
                    + ", for " + var0 + " and " + var1 + ".", \
                    (/"mean"/), \
@@ -501,7 +501,7 @@ begin
 
         ; Provenance
     log_provenance(ncdf_outfile, \
-                   outfile_map, \
+                   outfile_map + "." + file_type, \
                    "Time series for satellite, multi-model mean and station " \
                    + var0 + " and " + var1 \
                    + ". Similar to Gier et al, 2020 Fig. 2", \
diff --git a/esmvaltool/interface_scripts/logging.ncl b/esmvaltool/interface_scripts/logging.ncl
index 3e1b10b0b2..4cb5ff1498 100644
--- a/esmvaltool/interface_scripts/logging.ncl
+++ b/esmvaltool/interface_scripts/logging.ncl
@@ -336,6 +336,12 @@ begin
   if (outfile .ne. "n/a") then
     suffix = get_file_suffix(outfile, 0)
 
+    if (ismissing(suffix)) then
+      error_msg("f", scriptname, funcname, "got invalid value for outfile " + \
+                "(path to figure): '" + outfile + "'; expected path to a " + \
+                "file or 'n/a'")
+    end if
+
     ; For PNGs, additionally check for existence of files like
     ; "plot_file.000001.png", "plot_file.000002.png", etc. and save
     ; provenance record for each of them
@@ -354,7 +360,10 @@ begin
           break
         end if
       end do
-    else
+    end if
+
+    ; For all other cases, use outfile
+    if (.not. isvar("all_outfiles")) then
       all_outfiles = outfile
     end if
 
@@ -362,6 +371,13 @@ begin
     original_entry = outstring
     do outfile_idx = 0, dimsizes(all_outfiles) - 1
       file_to_add := all_outfiles(outfile_idx)
+      if (.not. fileexists(outfile)) then
+        error_msg("f", scriptname, funcname, "outfile (path to figure) '" + \
+                  file_to_add + "' does not exist (for PNGs, this " + \
+                  "function also searches for 'FILE.000001.png', " + \
+                  "'FILE.000002.png', etc.); if no plot file is available " + \
+                  "use 'n/a'")
+      end if
       new_entry = (/original_entry/)
       new_entry(0) = "? " + file_to_add
       outstring := array_append_record(outstring, new_entry, 0)

From 4cce8928e384699dbc63ff6f3c0811726d8b9599 Mon Sep 17 00:00:00 2001
From: Romain Beucher <romain.beucher@anu.edu.au>
Date: Thu, 23 Nov 2023 00:30:24 +1100
Subject: [PATCH 81/93] recipe_smpi_4cds Update GPCP to match ESGF name (#3423)

---
 esmvaltool/recipes/recipe_smpi_4cds.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/esmvaltool/recipes/recipe_smpi_4cds.yml b/esmvaltool/recipes/recipe_smpi_4cds.yml
index 5f946986b4..3a60419d69 100644
--- a/esmvaltool/recipes/recipe_smpi_4cds.yml
+++ b/esmvaltool/recipes/recipe_smpi_4cds.yml
@@ -236,9 +236,9 @@ diagnostics:
       pr:
         <<: *variable_settings
         preprocessor: ppNOLEV
-        reference_dataset: GPCP-SG
+        reference_dataset: GPCP-V2.2
     additional_datasets:
-      - {dataset: GPCP-SG, project: obs4MIPs, level: L3, version: v2.2, tier: 1}
+      - {dataset: GPCP-V2.2, project: obs4MIPs, level: L3, tier: 1}
     scripts:
       grading:
         script: perfmetrics/main.ncl

From 5ba10a53075a04066850ced1bfb89b8fe9844056 Mon Sep 17 00:00:00 2001
From: FranziskaWinterstein
 <119339136+FranziskaWinterstein@users.noreply.github.com>
Date: Wed, 29 Nov 2023 17:25:03 +0100
Subject: [PATCH 82/93] Fix parsing in diag validation (#3364)

Co-authored-by: Axel Lauer <axel.lauer@dlr.de>
Co-authored-by: Manuel Schlund <32543114+schlunma@users.noreply.github.com>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: valeriupredoi <valeriupredoi@users.noreply.github.com>
Co-authored-by: Valeriu Predoi <valeriu.predoi@gmail.com>
Co-authored-by: Manuel Schlund <manuel.schlund@dlr.de>
---
 esmvaltool/diag_scripts/validation.py | 68 ++++++++++++++-------------
 1 file changed, 36 insertions(+), 32 deletions(-)

diff --git a/esmvaltool/diag_scripts/validation.py b/esmvaltool/diag_scripts/validation.py
index d72cc5e1ad..52c8d1a561 100644
--- a/esmvaltool/diag_scripts/validation.py
+++ b/esmvaltool/diag_scripts/validation.py
@@ -29,27 +29,11 @@
 
 def _get_provenance_record(cfg, plot_file, caption, loc):
     """Create a provenance record describing the diagnostic data and plot."""
-    all_input_files = [
-        k for k in cfg["input_data"].keys() if k.endswith(".nc")
-    ]
-    if "_vs_" in plot_file:
-        model_1 = plot_file.split("_vs_")[0].split("_")[-1]
-        if plot_file.endswith(".png"):
-            model_2 = plot_file.split("_vs_")[1].strip(".png")
-        elif plot_file.endswith(".nc"):
-            model_2 = plot_file.split("_vs_")[1].strip(".nc")
-        ancestor_1 = [
-            k for k in all_input_files if model_1 in os.path.basename(k)
-        ][0]
-        ancestor_2 = [
-            k for k in all_input_files if model_2 in os.path.basename(k)
-        ][0]
-        ancestor_files = [ancestor_1, ancestor_2]
-    else:
-        model = os.path.basename(plot_file).split("_")[0]
-        ancestor_files = [
-            k for k in all_input_files if model in os.path.basename(k)
-        ]
+    ancestor_files = []
+    for dataset in cfg['input_data'].values():
+        if (dataset['alias'] in plot_file and
+                dataset['short_name'] in plot_file):
+            ancestor_files.append(dataset['filename'])
     record = {
         'caption': caption,
         'statistics': ['mean'],
@@ -72,9 +56,9 @@ def _get_provenance_record(cfg, plot_file, caption, loc):
 def plot_contour(cube, cfg, plt_title, file_name):
     """Plot a contour with iris.quickplot (qplot)."""
     if len(cube.shape) == 2:
-        qplt.contourf(cube, cmap='RdYlBu_r', bbox_inches='tight')
+        qplt.contourf(cube, cmap='RdYlBu_r')
     else:
-        qplt.contourf(cube[0], cmap='RdYlBu_r', bbox_inches='tight')
+        qplt.contourf(cube[0], cmap='RdYlBu_r')
     plt.title(plt_title)
     plt.gca().coastlines()
     plt.tight_layout()
@@ -138,7 +122,10 @@ def plot_latlon_cubes(cube_1,
     # plot each cube
     var = data_names.split('_')[0]
     if not obs_name:
-        cube_names = [data_names.split('_')[1], data_names.split('_')[3]]
+        cube_names = [
+            data_names.replace(f'{var}_', '').split('_vs_')[i] for i in
+            range(2)
+        ]
         for cube, cube_name in zip(cubes, cube_names):
             if not season:
                 plot_file_path = os.path.join(
@@ -179,23 +166,40 @@ def plot_zonal_cubes(cube_1, cube_2, cfg, plot_data):
     # xcoordinate: latotude or longitude (str)
     data_names, xcoordinate, period = plot_data
     var = data_names.split('_')[0]
-    cube_names = [data_names.split('_')[1], data_names.split('_')[3]]
+    cube_names = data_names.replace(var + '_', '').split('_vs_')
     lat_points = cube_1.coord(xcoordinate).points
     plt.plot(lat_points, cube_1.data, label=cube_names[0])
     plt.plot(lat_points, cube_2.data, label=cube_names[1])
+    plt.title(f'Annual Climatology of {var}' if period == 'alltime'
+              else f'{period} of {var}')
     if xcoordinate == 'latitude':
-        plt.title(period + ' Zonal Mean for ' + var + ' ' + data_names)
+        axis = plt.gca()
+        axis.set_xticks([-60, -30, 0, 30, 60],
+                        labels=['60\N{DEGREE SIGN} S',
+                                '30\N{DEGREE SIGN} S',
+                                '0\N{DEGREE SIGN}',
+                                '30\N{DEGREE SIGN} N',
+                                '60\N{DEGREE SIGN} N'])
     elif xcoordinate == 'longitude':
-        plt.title(period + ' Meridional Mean for ' + var + ' ' + data_names)
+        axis = plt.gca()
+        axis.set_xticks([0, 60, 120, 180, 240, 300, 360],
+                        labels=['0\N{DEGREE SIGN} E',
+                                '60\N{DEGREE SIGN} E',
+                                '120\N{DEGREE SIGN} E',
+                                '180\N{DEGREE SIGN} E',
+                                '240\N{DEGREE SIGN} E',
+                                '300\N{DEGREE SIGN} E',
+                                '0\N{DEGREE SIGN} E'])
     plt.xlabel(xcoordinate + ' (deg)')
-    plt.ylabel(var)
+    plt.ylabel(f'{var} [{str(cube_1.units)}]')
     plt.tight_layout()
     plt.grid()
     plt.legend()
+    png_name = f'{xcoordinate}_{period}_{data_names}.png'
     if xcoordinate == 'latitude':
-        png_name = 'Zonal_Mean_' + xcoordinate + '_' + data_names + '.png'
+        png_name = 'Zonal_Mean_' + png_name
     elif xcoordinate == 'longitude':
-        png_name = 'Merid_Mean_' + xcoordinate + '_' + data_names + '.png'
+        png_name = 'Merid_Mean_' + png_name
     plot_file_path = os.path.join(cfg['plot_dir'], period, png_name)
     plt.savefig(plot_file_path)
     save_plotted_cubes(
@@ -252,13 +256,13 @@ def coordinate_collapse(data_set, cfg):
         if 'mask_threshold' in cfg:
             thr = cfg['mask_threshold']
             data_set.data = np.ma.masked_array(data_set.data,
-                                               mask=(mask_cube.data > thr))
+                                               mask=mask_cube.data > thr)
         else:
             logger.warning('Could not find masking threshold')
             logger.warning('Please specify it if needed')
             logger.warning('Masking on 0-values = True (masked value)')
             data_set.data = np.ma.masked_array(data_set.data,
-                                               mask=(mask_cube.data == 0))
+                                               mask=mask_cube.data == 0)
 
     # if zonal mean on LON
     if analysis_type == 'zonal_mean':

From a64882083ecb07ab26adacf526b4b83593e37647 Mon Sep 17 00:00:00 2001
From: Richard Littauer <richard.littauer@gmail.com>
Date: Wed, 29 Nov 2023 11:38:54 -0500
Subject: [PATCH 83/93] [docs, minor] Update README.md (#3358)

---
 README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index 71403fbf90..694dab6a82 100644
--- a/README.md
+++ b/README.md
@@ -53,11 +53,11 @@ ESMValTool can run with the following types of [data as input](https://docs.esmv
 
 # Getting started
 
-Please see [getting started](https://docs.esmvaltool.org/en/latest/quickstart/index.html) on readthedocs as well as [ESMValTool tutorial](https://tutorial.esmvaltool.org/index.html). The tutorial is a set of lessons that together teach skills needed to work with ESMValTool in climate-related domains.
+Please see [getting started](https://docs.esmvaltool.org/en/latest/quickstart/index.html) on our instance of Read the Docs as well as [ESMValTool tutorial](https://tutorial.esmvaltool.org/index.html). The tutorial is a set of lessons that together teach skills needed to work with ESMValTool in climate-related domains.
 
 ## Getting help
 
-The easiest way to get help if you cannot find the answer in the documentation on [readthedocs](https://docs.esmvaltool.org), is to open an [issue on GitHub](https://github.com/ESMValGroup/ESMValTool/issues).
+The easiest way to get help, if you cannot find the answer in the documentation in our [docs](https://docs.esmvaltool.org), is to open an [issue on GitHub](https://github.com/ESMValGroup/ESMValTool/issues).
 
 ## Contributing
 

From d8b9d24e399b047f3041de9ac26f818860095ca6 Mon Sep 17 00:00:00 2001
From: Manuel Schlund <32543114+schlunma@users.noreply.github.com>
Date: Thu, 30 Nov 2023 13:20:07 +0100
Subject: [PATCH 84/93] Correctly handle `~` when reading `plot_folder` option
 of monitoring diagnostic (#3449)

---
 esmvaltool/diag_scripts/monitor/monitor_base.py | 10 ++++------
 1 file changed, 4 insertions(+), 6 deletions(-)

diff --git a/esmvaltool/diag_scripts/monitor/monitor_base.py b/esmvaltool/diag_scripts/monitor/monitor_base.py
index 135027f374..21dc159619 100644
--- a/esmvaltool/diag_scripts/monitor/monitor_base.py
+++ b/esmvaltool/diag_scripts/monitor/monitor_base.py
@@ -97,7 +97,9 @@ def __init__(self, config):
         )
         plot_folder = plot_folder.replace('{plot_dir}',
                                           self.cfg[names.PLOT_DIR])
-        self.plot_folder = os.path.abspath(plot_folder)
+        self.plot_folder = os.path.abspath(
+            os.path.expandvars(os.path.expanduser(plot_folder))
+        )
         self.plot_filename = config.get(
             'plot_filename',
             '{plot_type}_{real_name}_{dataset}_{mip}_{exp}_{ensemble}')
@@ -293,11 +295,7 @@ def get_plot_folder(self, var_info):
             'real_name': self._real_name(var_info['variable_group']),
             **var_info
         }
-        folder = os.path.expandvars(
-            os.path.expanduser(
-                list(_replace_tags(self.plot_folder, info))[0]
-            )
-        )
+        folder = list(_replace_tags(self.plot_folder, info))[0]
         if self.plot_folder.startswith('/'):
             folder = '/' + folder
         if not os.path.isdir(folder):

From 82e7f39c2bf52a2b42e7def1717ee19e3c286613 Mon Sep 17 00:00:00 2001
From: Manuel Schlund <32543114+schlunma@users.noreply.github.com>
Date: Thu, 30 Nov 2023 13:24:32 +0100
Subject: [PATCH 85/93] Add general model evaluation recipes (for Changelog:
 authors: @axel-lauer, @hb326, @Paulinebonnet111, @LisaBock, @schlunma)
 (#3421)

Co-authored-by: Axel Lauer <axel.lauer@dlr.de>
Co-authored-by: Pauline Bonnet <b309216@levante0.lvt.dkrz.de>
Co-authored-by: Birgit Hassler <33543691+hb326@users.noreply.github.com>
Co-authored-by: Birgit Hassler <birgit.hassler@dlr.de>
Co-authored-by: Paulinebonnet111 <123577048+Paulinebonnet111@users.noreply.github.com>
---
 .../api/esmvaltool.diag_scripts.monitor.rst   |   1 +
 doc/sphinx/source/faq.rst                     |  12 +-
 .../annual_cycle_clt_southerocean_Amon.jpg    | Bin 0 -> 76545 bytes
 .../map_swcre_MPI-ESM1-2-HR_Amon.jpg          | Bin 0 -> 148718 bytes
 .../map_tas_MPI-ESM1-2-HR_Amon.jpg            | Bin 0 -> 133214 bytes
 ...timeseries_rtnt_ambiguous_dataset_Amon.jpg | Bin 0 -> 93664 bytes
 .../variable_vs_lat_pr_Amon.jpg               | Bin 0 -> 81310 bytes
 doc/sphinx/source/recipes/index.rst           |   1 +
 .../recipes/recipe_model_evaluation.rst       |  98 +++++++
 doc/sphinx/source/recipes/recipe_monitor.rst  |  19 +-
 .../recipe_model_evaluation_basics.yml        | 260 ++++++++++++++++++
 .../recipe_model_evaluation_clouds_clim.yml   | 226 +++++++++++++++
 .../recipe_model_evaluation_clouds_cycles.yml | 178 ++++++++++++
 .../recipe_model_evaluation_precip_zonal.yml  |  72 +++++
 .../monitor/recipe_monitor_with_refs.yml      |   2 +-
 esmvaltool/recipes/recipe_psyplot.yml         |   6 +-
 esmvaltool/recipes/recipe_seaborn.yml         |   6 +-
 17 files changed, 861 insertions(+), 20 deletions(-)
 create mode 100644 doc/sphinx/source/recipes/figures/model_evaluation/annual_cycle_clt_southerocean_Amon.jpg
 create mode 100644 doc/sphinx/source/recipes/figures/model_evaluation/map_swcre_MPI-ESM1-2-HR_Amon.jpg
 create mode 100644 doc/sphinx/source/recipes/figures/model_evaluation/map_tas_MPI-ESM1-2-HR_Amon.jpg
 create mode 100644 doc/sphinx/source/recipes/figures/model_evaluation/timeseries_rtnt_ambiguous_dataset_Amon.jpg
 create mode 100644 doc/sphinx/source/recipes/figures/model_evaluation/variable_vs_lat_pr_Amon.jpg
 create mode 100644 doc/sphinx/source/recipes/recipe_model_evaluation.rst
 create mode 100644 esmvaltool/recipes/model_evaluation/recipe_model_evaluation_basics.yml
 create mode 100644 esmvaltool/recipes/model_evaluation/recipe_model_evaluation_clouds_clim.yml
 create mode 100644 esmvaltool/recipes/model_evaluation/recipe_model_evaluation_clouds_cycles.yml
 create mode 100644 esmvaltool/recipes/model_evaluation/recipe_model_evaluation_precip_zonal.yml

diff --git a/doc/sphinx/source/api/esmvaltool.diag_scripts.monitor.rst b/doc/sphinx/source/api/esmvaltool.diag_scripts.monitor.rst
index bb43997c43..3b1e3e6548 100644
--- a/doc/sphinx/source/api/esmvaltool.diag_scripts.monitor.rst
+++ b/doc/sphinx/source/api/esmvaltool.diag_scripts.monitor.rst
@@ -11,6 +11,7 @@ Examples
 --------
 
 * :ref:`recipe_monitor`
+* :ref:`recipe_model_evaluation`
 
 
 Diagnostic scripts
diff --git a/doc/sphinx/source/faq.rst b/doc/sphinx/source/faq.rst
index 15d69192ca..10c72bd2cb 100644
--- a/doc/sphinx/source/faq.rst
+++ b/doc/sphinx/source/faq.rst
@@ -113,9 +113,15 @@ a symbolic link to it so it gets picked up at every re-run iteration:
 Can ESMValTool plot arbitrary model output?
 ===========================================
 
-Recipe :ref:`recipe_monitor` allows for the plotting of any preprocessed model.
-The plotting parameters are set through a yaml configuration file, and the
-type of plots to be generated are determined in the recipe.
+:ref:`recipe_model_evaluation` provides a set of recipes that can be used for a
+basic climate model evaluation with observational data.
+This is especially useful to get an overview of the general performance of a
+simulation.
+
+Furthermore, recipe :ref:`recipe_monitor` allows for the plotting of any
+preprocessed model.
+The plotting parameters are set through a yaml configuration file, and the type
+of plots to be generated are determined in the recipe.
 
 Moreover, recipe :ref:`recipes_psyplot_diag` and the corresponding diagnostic
 :ref:`psyplot_diag.py <api.esmvaltool.diag_scripts.psyplot_diag>` provide a
diff --git a/doc/sphinx/source/recipes/figures/model_evaluation/annual_cycle_clt_southerocean_Amon.jpg b/doc/sphinx/source/recipes/figures/model_evaluation/annual_cycle_clt_southerocean_Amon.jpg
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HcmV?d00001

diff --git a/doc/sphinx/source/recipes/index.rst b/doc/sphinx/source/recipes/index.rst
index c8e6b4a320..edcc48977a 100644
--- a/doc/sphinx/source/recipes/index.rst
+++ b/doc/sphinx/source/recipes/index.rst
@@ -21,6 +21,7 @@ large variety of input data.
 .. toctree::
    :maxdepth: 1
 
+   recipe_model_evaluation
    recipe_monitor
    recipe_psyplot
    recipe_seaborn
diff --git a/doc/sphinx/source/recipes/recipe_model_evaluation.rst b/doc/sphinx/source/recipes/recipe_model_evaluation.rst
new file mode 100644
index 0000000000..9e199815e0
--- /dev/null
+++ b/doc/sphinx/source/recipes/recipe_model_evaluation.rst
@@ -0,0 +1,98 @@
+.. _recipe_model_evaluation:
+
+General model evaluation
+========================
+
+Overview
+--------
+
+These recipes and diagnostics provide a basic climate model evaluation with
+observational data.
+This is especially useful to get an overview of the performance of a
+simulation.
+The diagnostics used here allow plotting arbitrary preprocessor output, i.e.,
+arbitrary variables from arbitrary datasets.
+
+
+Available recipes and diagnostics
+---------------------------------
+
+Recipes are stored in `recipes/model_evaluation`
+
+* recipe_model_evaluation_basics.yml
+* recipe_model_evaluation_clouds_clim.yml
+* recipe_model_evaluation_clouds_cycles.yml
+* recipe_model_evaluation_precip_zonal.yml
+
+Diagnostics are stored in `diag_scripts/monitor/`
+
+* :ref:`multi_datasets.py
+  <api.esmvaltool.diag_scripts.monitor.multi_datasets>`:
+  Monitoring diagnostic to show multiple datasets in one plot (incl. biases).
+
+
+User settings
+-------------
+
+It is recommended to use a vector graphic file type (e.g., SVG) for the output
+format when running this recipe, i.e., run the recipe with the command line
+option ``--output_file_type=svg`` or use ``output_file_type: svg`` in your
+:ref:`esmvalcore:user configuration file`.
+Note that map and profile plots are rasterized by default.
+Use ``rasterize: false`` in the recipe to disable
+this.
+
+
+Recipe settings
+~~~~~~~~~~~~~~~
+
+A list of all possible configuration options that can be specified in the
+recipe is given for each diagnostic individually (see links given for the
+available diagnostics in the previous section).
+
+
+Variables
+---------
+
+Any, but the variables' number of dimensions should match the ones expected by
+each diagnostic (see links given for the available diagnostics in the previous
+section).
+
+
+Example plots
+-------------
+
+.. _fig_1:
+.. figure::  /recipes/figures/model_evaluation/map_tas_MPI-ESM1-2-HR_Amon.jpg
+   :align:   center
+   :width:   14cm
+
+Global climatology of 2m near-surface air temperature.
+
+.. _fig_2:
+.. figure::  /recipes/figures/model_evaluation/map_swcre_MPI-ESM1-2-HR_Amon.jpg
+   :align:   center
+   :width:   14cm
+
+Global climatology of the shortwave cloud radiative effect (SWCRE).
+
+.. _fig_3:
+.. figure::  /recipes/figures/model_evaluation/timeseries_rtnt_ambiguous_dataset_Amon.jpg
+   :align:   center
+   :width:   14cm
+
+Time series of the global mean top-of-the-atmosphere net radiative flux.
+
+.. _fig_4:
+.. figure::  /recipes/figures/model_evaluation/variable_vs_lat_pr_Amon.jpg
+   :align:   center
+   :width:   14cm
+
+Zonal mean precipitation.
+
+.. _fig_5:
+.. figure::  /recipes/figures/model_evaluation/annual_cycle_clt_southerocean_Amon.jpg
+   :align:   center
+   :width:   14cm
+
+Annual cycle of Southern Ocean total cloud cover.
diff --git a/doc/sphinx/source/recipes/recipe_monitor.rst b/doc/sphinx/source/recipes/recipe_monitor.rst
index 9bdfd5d40b..ee3b9b44fa 100644
--- a/doc/sphinx/source/recipes/recipe_monitor.rst
+++ b/doc/sphinx/source/recipes/recipe_monitor.rst
@@ -18,19 +18,18 @@ Available recipes and diagnostics
 
 Recipes are stored in `recipes/monitor`
 
-   * recipe_monitor.yml
-   * recipe_monitor_with_refs.yml
+* recipe_monitor.yml
+* recipe_monitor_with_refs.yml
 
 Diagnostics are stored in `diag_scripts/monitor/`
 
-   * :ref:`monitor.py <api.esmvaltool.diag_scripts.monitor.monitor>`:
-     Monitoring diagnostic to plot arbitrary preprocessor output.
-   * :ref:`compute_eofs.py <api.esmvaltool.diag_scripts.monitor.compute_eofs>`:
-     Monitoring diagnostic to plot EOF maps and associated PC timeseries.
-   * :ref:`multi_datasets.py
-     <api.esmvaltool.diag_scripts.monitor.multi_datasets>`:
-     Monitoring diagnostic to show multiple datasets in one plot (incl.
-     biases).
+* :ref:`monitor.py <api.esmvaltool.diag_scripts.monitor.monitor>`:
+  Monitoring diagnostic to plot arbitrary preprocessor output.
+* :ref:`compute_eofs.py <api.esmvaltool.diag_scripts.monitor.compute_eofs>`:
+  Monitoring diagnostic to plot EOF maps and associated PC timeseries.
+* :ref:`multi_datasets.py
+  <api.esmvaltool.diag_scripts.monitor.multi_datasets>`:
+  Monitoring diagnostic to show multiple datasets in one plot (incl. biases).
 
 
 User settings
diff --git a/esmvaltool/recipes/model_evaluation/recipe_model_evaluation_basics.yml b/esmvaltool/recipes/model_evaluation/recipe_model_evaluation_basics.yml
new file mode 100644
index 0000000000..06f8ad3b12
--- /dev/null
+++ b/esmvaltool/recipes/model_evaluation/recipe_model_evaluation_basics.yml
@@ -0,0 +1,260 @@
+# ESMValTool
+---
+documentation:
+  title: Basic Model Evaluation.
+  description: >
+    Show plots of several variables that can be used for basic model
+    evaluations ("sanity checks").
+  authors:
+    - hassler_birgit
+    - lauer_axel
+    - bonnet_pauline
+    - schlund_manuel
+  maintainer:
+    - hassler_birgit
+
+
+# Note: The following models are just examples
+datasets:
+  - {project: CMIP6, dataset: MPI-ESM1-2-HR, exp: historical, ensemble: r1i1p1f1, grid: gn}
+  - {project: CMIP6, dataset: MPI-ESM1-2-LR, exp: historical, ensemble: r1i1p1f1, grid: gn}
+
+# Note: for some observational datasets, we use preset time ranges due to
+# their limited temporal availability
+timerange_for_models: &time_period
+  timerange: '2003/2007'  # can be specified, this is just an example
+
+
+preprocessors:
+
+  timeseries_regular: &pp_timeseries_regular
+    area_statistics:
+      operator: mean
+
+  timeseries_regular_ann:
+    <<: *pp_timeseries_regular
+    annual_statistics:
+      operator: mean
+
+  timeseries_regular_pr:
+    <<: *pp_timeseries_regular
+    convert_units:
+      units: mm day-1
+
+  full_climatology: &pp_full_climatology
+    climate_statistics:
+      period: full
+    regrid:
+      target_grid: 2x2
+      scheme:
+        reference: esmf_regrid.schemes:ESMFAreaWeighted
+
+  full_climatology_pr:
+    <<: *pp_full_climatology
+    convert_units:
+      units: mm day-1
+
+  zonal_mean:
+    custom_order: true  # makes preprocessor much faster since input for extract_levels is smaller
+    climate_statistics:
+      period: full
+    extract_levels:
+      levels: {cmor_table: CMIP6, coordinate: plev19}
+      scheme: linear
+      coordinate: air_pressure
+    regrid:
+      scheme:
+        reference: esmf_regrid.schemes:ESMFAreaWeighted
+      target_grid: 2x2
+    zonal_statistics:
+      operator: mean
+
+
+diagnostics:
+
+  # Climatologies - maps (full climatology)
+
+  plot_maps_with_references_tas:
+    description: Plot climatology maps including reference datasets for tas.
+    variables:
+      tas:
+        <<: *time_period
+        mip: Amon
+        preprocessor: full_climatology
+        additional_datasets:
+          - {project: native6, dataset: ERA5, type: reanaly, version: v1, tier: 3, reference_for_monitor_diags: true}
+    scripts:
+      plot: &plot_multi_dataset_default
+        plot_folder: '{plot_dir}'
+        plot_filename: '{plot_type}_{real_name}_{dataset}_{mip}'
+        script: monitor/multi_datasets.py
+        plots:
+          map:
+            common_cbar: true
+
+  plot_maps_with_references_pr:
+    description: Plot climatology maps including reference datasets for pr.
+    variables:
+      pr:
+        <<: *time_period
+        mip: Amon
+        preprocessor: full_climatology_pr
+        additional_datasets:
+          - {project: OBS, dataset: GPCP-SG, type: atmos, version: 2.3, tier: 2, reference_for_monitor_diags: true}
+    scripts:
+      plot:
+        <<: *plot_multi_dataset_default
+        script: monitor/multi_datasets.py
+        plots:
+          map:
+            common_cbar: true
+            plot_kwargs:
+              default:
+                cmap: Blues
+
+  # Climatologies (zonal means)
+
+  plot_zonal_mean_profiles_with_references_ta:
+    description: Plot 2D zonal mean profiles including reference datasets.
+    variables:
+      ta:
+        <<: *time_period
+        mip: Amon
+        preprocessor: zonal_mean
+        additional_datasets:
+          - {project: native6, dataset: ERA5, type: reanaly, version: v1, tier: 3, reference_for_monitor_diags: true}
+    scripts:
+      plot:
+        <<: *plot_multi_dataset_default
+        script: monitor/multi_datasets.py
+        plots:
+          zonal_mean_profile:
+            common_cbar: true
+
+  plot_zonal_mean_profiles_with_references_ua:
+    description: Plot 2D zonal mean profiles including reference datasets.
+    variables:
+      ua:
+        <<: *time_period
+        mip: Amon
+        preprocessor: zonal_mean
+        additional_datasets:
+          - {project: native6, dataset: ERA5, type: reanaly, version: v1, tier: 3, reference_for_monitor_diags: true}
+    scripts:
+      plot:
+        <<: *plot_multi_dataset_default
+        script: monitor/multi_datasets.py
+        plots:
+          zonal_mean_profile:
+            common_cbar: true
+            plot_kwargs:
+              default:
+                cmap: Blues
+
+  plot_zonal_mean_profiles_with_references_hus:
+    description: Plot 2D zonal mean profiles including reference datasets.
+    variables:
+      hus:
+        <<: *time_period
+        mip: Amon
+        preprocessor: zonal_mean
+        additional_datasets:
+          - {project: native6, dataset: ERA5, type: reanaly, version: v1, tier: 3, reference_for_monitor_diags: true}
+    scripts:
+      plot:
+        <<: *plot_multi_dataset_default
+        script: monitor/multi_datasets.py
+        plots:
+          zonal_mean_profile:
+            common_cbar: true
+            plot_kwargs:
+              default:
+                cmap: Blues
+
+  # Time series of global averages (monthly)
+
+  plot_multiple_timeseries:
+    description: Plot time series including reference datasets.
+    variables:
+      tas:
+        <<: *time_period
+        mip: Amon
+        preprocessor: timeseries_regular
+        additional_datasets:
+          - {project: native6, dataset: ERA5, type: reanaly, version: v1, tier: 3, reference_for_monitor_diags: true}
+      clt:
+        <<: *time_period
+        mip: Amon
+        preprocessor: timeseries_regular
+        additional_datasets:
+          - {project: OBS, dataset: ESACCI-CLOUD, type: sat, version: AVHRR-AMPM-fv3.0, tier: 2, reference_for_monitor_diags: true}
+      rsut:
+        <<: *time_period
+        mip: Amon
+        preprocessor: timeseries_regular
+        additional_datasets:
+          - {project: OBS, dataset: CERES-EBAF, type: sat, version: Ed4.1, tier: 2, reference_for_monitor_diags: true}
+      rlut:
+        <<: *time_period
+        mip: Amon
+        preprocessor: timeseries_regular
+        additional_datasets:
+          - {project: OBS, dataset: CERES-EBAF, type: sat, version: Ed4.1, tier: 2, reference_for_monitor_diags: true}
+      rtnt:
+        derive: true
+        force_derivation: true
+        mip: Amon
+        preprocessor: timeseries_regular_ann
+        timerange: '1995/2014'
+      prw:
+        <<: *time_period
+        mip: Amon
+        preprocessor: timeseries_regular
+        # timerange MUST NOT start before 2003 since the observations are not available before 2003
+        additional_datasets:
+          - {project: OBS, dataset: ESACCI-WATERVAPOUR, type: sat, version: CDR2-L3S-05deg_fv3.1, tier: 3, timerange: '2003/2007', reference_for_monitor_diags: true}
+    scripts:
+      plot:
+        <<: *plot_multi_dataset_default
+        group_variables_by: variable_group
+        script: monitor/multi_datasets.py
+        plots:
+          timeseries:
+            annual_mean_kwargs: false
+            plot_kwargs:
+              MPI-ESM1-2-HR:
+                color: C0
+              MPI-ESM1-2-LR:
+                color: C1
+              ERA5:
+                color: black
+              ESACCI-CLOUD:
+                color: black
+              CERES-EBAF:
+                color: black
+              ESACCI-WATERVAPOUR:
+                color: black
+
+  plot_multiple_timeseries_pr:
+    description: Plot time series including reference datasets.
+    variables:
+      pr:
+        <<: *time_period
+        mip: Amon
+        preprocessor: timeseries_regular_pr
+        additional_datasets:
+          - {project: OBS, dataset: GPCP-SG, type: atmos, version: 2.3, tier: 2, reference_for_monitor_diags: true}
+    scripts:
+      plot:
+        <<: *plot_multi_dataset_default
+        script: monitor/multi_datasets.py
+        plots:
+          timeseries:
+            annual_mean_kwargs: false
+            plot_kwargs:
+              MPI-ESM1-2-HR:
+                color: C0
+              MPI-ESM1-2-LR:
+                color: C1
+              GPCP-SG:
+                color: black
diff --git a/esmvaltool/recipes/model_evaluation/recipe_model_evaluation_clouds_clim.yml b/esmvaltool/recipes/model_evaluation/recipe_model_evaluation_clouds_clim.yml
new file mode 100644
index 0000000000..fd2d08781f
--- /dev/null
+++ b/esmvaltool/recipes/model_evaluation/recipe_model_evaluation_clouds_clim.yml
@@ -0,0 +1,226 @@
+# ESMValTool
+---
+documentation:
+  title: Model evaluation with focus on clouds.
+  description: >
+    Plot climatologies several cloud-related variables of multi-year
+    simulations.
+  authors:
+    - bonnet_pauline
+    - lauer_axel
+    - hassler_birgit
+    - schlund_manuel
+  maintainer:
+    - lauer_axel
+
+
+# Note: the following models are just examples
+datasets:
+  - {project: CMIP6, dataset: MPI-ESM1-2-HR, exp: historical, ensemble: r1i1p1f1, grid: gn}
+  - {project: CMIP6, dataset: MPI-ESM1-2-LR, exp: historical, ensemble: r1i1p1f1, grid: gn}
+
+# Note: for some observational datasets, we use preset time ranges due to
+# their limited temporal availability
+timerange_for_models: &time_period
+  timerange: '2005/2014'  # can be specified, this is just an example
+
+
+preprocessors:
+
+  full_climatology: &full_climatology_diag
+    climate_statistics:
+      period: full
+    regrid:
+      target_grid: 2x2
+      scheme:
+        reference: esmf_regrid.schemes:ESMFAreaWeighted
+
+  full_climatology_pr:
+    <<: *full_climatology_diag
+    convert_units:
+      units: mm day-1
+
+  zonal_mean:
+    custom_order: true  # makes preprocessor much faster since input for extract_levels is smaller
+    climate_statistics:
+      period: full
+    extract_levels:
+      levels: {cmor_table: CMIP6, coordinate: plev19}
+      scheme: linear
+      coordinate: air_pressure
+    regrid:
+      scheme:
+        reference: esmf_regrid.schemes:ESMFAreaWeighted
+      target_grid: 2x2
+    zonal_statistics:
+      operator: mean
+
+
+diagnostics:
+
+  plot_clt_maps:
+    description: Plot clt climatology maps including reference datasets.
+    variables:
+      clt:
+        <<: *time_period
+        mip: Amon
+        preprocessor: full_climatology
+        additional_datasets:
+          - {dataset: ESACCI-CLOUD, project: OBS, type: sat, version: AVHRR-AMPM-fv3.0, tier: 2, reference_for_monitor_diags: true}
+    scripts:
+      plot: &plot_multi_dataset_default
+        script: monitor/multi_datasets.py
+        plot_folder: '{plot_dir}'
+        plot_filename: '{plot_type}_{real_name}_{dataset}_{mip}'
+        plots:
+          map:
+            common_cbar: true
+
+  plot_lwcre_maps:
+    description: Plot lwcre climatology maps including reference datasets.
+    variables:
+      lwcre:
+        <<: *time_period
+        mip: Amon
+        preprocessor: full_climatology
+        derive: true
+        additional_datasets:
+          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, timerange: '2001/2010', tier: 1, reference_for_monitor_diags: true}
+    scripts:
+      plot:
+        <<: *plot_multi_dataset_default
+        plots:
+          map:
+            common_cbar: true
+
+  plot_swcre_maps:
+    description: Plot swcre climatology maps including reference datasets.
+    variables:
+      swcre:
+        <<: *time_period
+        mip: Amon
+        preprocessor: full_climatology
+        derive: true
+        additional_datasets:
+          - {dataset: CERES-EBAF, project: obs4MIPs, level: L3B, tier: 1, timerange: '2001/2010', reference_for_monitor_diags: true}
+    scripts:
+      plot:
+        <<: *plot_multi_dataset_default
+        plots:
+          map:
+            common_cbar: true
+
+  plot_lwp_maps:
+    description: Plot lwp climatology maps including reference datasets.
+    variables:
+      lwp:
+        <<: *time_period
+        mip: Amon
+        preprocessor: full_climatology
+        derive: true
+        additional_datasets:
+          - {project: native6, dataset: ERA5, type: reanaly, version: v1, tier: 3, reference_for_monitor_diags: true}
+    scripts:
+      plot:
+        <<: *plot_multi_dataset_default
+        plots:
+          map:
+            common_cbar: true
+            fontsize: 6
+
+  plot_clivi_maps:
+    description: Plot clivi climatology maps including reference datasets.
+    variables:
+      clivi:
+        <<: *time_period
+        mip: Amon
+        preprocessor: full_climatology
+        additional_datasets:
+          - {project: native6, dataset: ERA5, type: reanaly, version: v1, tier: 3, reference_for_monitor_diags: true}
+    scripts:
+      plot:
+        <<: *plot_multi_dataset_default
+        plots:
+          map:
+            common_cbar: true
+
+  plot_prw_maps:
+    description: Plot prw climatology maps including reference datasets.
+    variables:
+      prw:
+        <<: *time_period
+        mip: Amon
+        preprocessor: full_climatology
+        additional_datasets:
+          - {dataset: ESACCI-WATERVAPOUR, project: OBS, type: sat, version: CDR2-L3S-05deg_fv3.1, tier: 3, timerange: '2003/2017', reference_for_monitor_diags: true}
+    scripts:
+      plot:
+        <<: *plot_multi_dataset_default
+        plots:
+          map:
+            common_cbar: true
+
+  plot_pr_maps:
+    description: Plot prw climatology maps including reference datasets.
+    variables:
+      pr:
+        <<: *time_period
+        mip: Amon
+        preprocessor: full_climatology_pr
+        additional_datasets:
+          - {dataset: GPCP-SG, project: OBS, type: atmos, version: 2.3, tier: 2,
+             timerange: '2003/2017', reference_for_monitor_diags: true}
+    scripts:
+      plot:
+        <<: *plot_multi_dataset_default
+        plots:
+          map:
+            common_cbar: true
+
+  plot_clw_profiles:
+    description: Plot clw vertical profiles including reference datasets.
+    variables:
+      clw:
+        <<: *time_period
+        mip: Amon
+        preprocessor: zonal_mean
+        additional_datasets:
+          - {dataset: CLOUDSAT-L2, project: OBS, type: sat, version: P1-R05-gridbox-average-noprecip, timerange: '2006/2017', tier: 3, reference_for_monitor_diags: true}
+    scripts:
+      plot:
+        <<: *plot_multi_dataset_default
+        plots:
+          profile:
+            common_cbar: true
+
+  plot_cli_profiles:
+    description: Plot cli vertical profiles including reference datasets.
+    variables:
+      cli:
+        <<: *time_period
+        mip: Amon
+        preprocessor: zonal_mean
+        additional_datasets:
+          - {dataset: CALIPSO-ICECLOUD, project: OBS, type: sat, version: 1-00, timerange: '2007/2015', tier: 3, reference_for_monitor_diags: true}
+    scripts:
+      plot:
+        <<: *plot_multi_dataset_default
+        plots:
+          profile:
+            common_cbar: true
+
+  plot_cl_profiles:
+    description: Plot cl vertical profiles including reference datasets.
+    variables:
+      cl:
+        <<: *time_period
+        mip: Amon
+        preprocessor: zonal_mean
+        additional_datasets:
+          - {project: native6, dataset: ERA5, type: reanaly, version: v1, tier: 3, reference_for_monitor_diags: true}
+    scripts:
+      plot:
+        <<: *plot_multi_dataset_default
+        plots:
+          profile:
+            common_cbar: true
diff --git a/esmvaltool/recipes/model_evaluation/recipe_model_evaluation_clouds_cycles.yml b/esmvaltool/recipes/model_evaluation/recipe_model_evaluation_clouds_cycles.yml
new file mode 100644
index 0000000000..ed52fd7d3c
--- /dev/null
+++ b/esmvaltool/recipes/model_evaluation/recipe_model_evaluation_clouds_cycles.yml
@@ -0,0 +1,178 @@
+# ESMValTool
+---
+documentation:
+  title: Model evaluation with focus on clouds.
+  description: >
+    Plot annual cycles of several cloud-related variables of multi-year simulations.
+  authors:
+    - lauer_axel
+    - schlund_manuel
+  maintainer:
+    - lauer_axel
+
+
+# Note: the following models are just examples
+datasets:
+  - {project: CMIP6, dataset: MPI-ESM1-2-HR, exp: historical, ensemble: r1i1p1f1, grid: gn}
+  - {project: CMIP6, dataset: MPI-ESM1-2-LR, exp: historical, ensemble: r1i1p1f1, grid: gn}
+
+# Note: for some observational datasets, we use preset time ranges due to
+# their limited temporal availability
+timerange_for_models: &time_period
+  timerange: '2000/2014'  # can be specified, this is just an example
+
+
+preprocessors:
+
+  pp_global: &global_settings
+    area_statistics:
+      operator: mean
+    climate_statistics:
+      period: month
+
+  pp_SEPacific:
+    <<: *global_settings
+    extract_region:
+      start_longitude: 265
+      end_longitude: 275
+      start_latitude: -25
+      end_latitude: -5
+    mask_landsea:
+      mask_out: land
+
+  pp_SouthernOcean:
+    <<: *global_settings
+    extract_region:
+      start_longitude: 0
+      end_longitude: 360
+      start_latitude: -65
+      end_latitude: -30
+    mask_landsea:
+      mask_out: land
+
+  pp_StormTracks:
+    <<: *global_settings
+    extract_region:
+      start_longitude: 0
+      end_longitude: 360
+      start_latitude: 45
+      end_latitude: 60
+
+
+diagnostics:
+
+  anncyc:
+    description: Plot annual cycles including reference datasets.
+    variables:
+      clt_global: &clt_settings
+        <<: *time_period
+        preprocessor: pp_global
+        short_name: clt
+        mip: Amon
+        additional_datasets:
+          - {dataset: ESACCI-CLOUD, project: OBS, type: sat, version: AVHRR-AMPM-fv3.0, tier: 2}
+      clt_tropics:
+        <<: *clt_settings
+      clt_sepacific:
+        <<: *clt_settings
+        preprocessor: pp_SEPacific
+      clt_southerocean:
+        <<: *clt_settings
+        preprocessor: pp_SouthernOcean
+      clt_stormtracks:
+        <<: *clt_settings
+        preprocessor: pp_StormTracks
+      clivi_global: &clivi_settings
+        <<: *time_period
+        preprocessor: pp_global
+        short_name: clivi
+        mip: Amon
+        additional_datasets:
+          - {dataset: ESACCI-CLOUD, project: OBS, type: sat, version: AVHRR-AMPM-fv3.0, tier: 2}
+      clivi_tropics:
+        <<: *clivi_settings
+      clivi_sepacific:
+        <<: *clivi_settings
+        preprocessor: pp_SEPacific
+      clivi_southerocean:
+        <<: *clivi_settings
+        preprocessor: pp_SouthernOcean
+      clivi_stormtracks:
+        <<: *clivi_settings
+        preprocessor: pp_StormTracks
+      lwp_global: &lwp_settings
+        <<: *time_period
+        preprocessor: pp_global
+        short_name: lwp
+        derive: true
+        mip: Amon
+        additional_datasets:
+          - {dataset: ESACCI-CLOUD, project: OBS, type: sat, version: AVHRR-AMPM-fv3.0, tier: 2}
+      lwp_tropics:
+        <<: *lwp_settings
+      lwp_sepacific:
+        <<: *lwp_settings
+        preprocessor: pp_SEPacific
+      lwp_southerocean:
+        <<: *lwp_settings
+        preprocessor: pp_SouthernOcean
+      lwp_stormtracks:
+        <<: *lwp_settings
+        preprocessor: pp_StormTracks
+      swcre_global: &swcre_settings
+        <<: *time_period
+        preprocessor: pp_global
+        short_name: swcre
+        derive: true
+        mip: Amon
+        additional_datasets:
+          - {dataset: CERES-EBAF, project: OBS, type: sat, version: Ed4.1, tier: 2}
+      swcre_tropics:
+        <<: *swcre_settings
+      swcre_sepacific:
+        <<: *swcre_settings
+        preprocessor: pp_SEPacific
+      swcre_southerocean:
+        <<: *swcre_settings
+        preprocessor: pp_SouthernOcean
+      swcre_stormtracks:
+        <<: *swcre_settings
+        preprocessor: pp_StormTracks
+      lwcre_global: &lwcre_settings
+        <<: *time_period
+        preprocessor: pp_global
+        short_name: lwcre
+        derive: true
+        mip: Amon
+        additional_datasets:
+          - {dataset: CERES-EBAF, project: OBS, type: sat, version: Ed4.1, tier: 2}
+      lwcre_tropics:
+        <<: *lwcre_settings
+      lwcre_sepacific:
+        <<: *lwcre_settings
+        preprocessor: pp_SEPacific
+      lwcre_southerocean:
+        <<: *lwcre_settings
+        preprocessor: pp_SouthernOcean
+      lwcre_stormtracks:
+        <<: *lwcre_settings
+        preprocessor: pp_StormTracks
+    scripts:
+      allplots:
+        script: monitor/multi_datasets.py
+        plot_folder: '{plot_dir}'
+        plot_filename: '{plot_type}_{real_name}_{mip}'
+        group_variables_by: variable_group
+        plots:
+          annual_cycle:
+            legend_kwargs:
+              loc: upper right
+            plot_kwargs:
+              MPI-ESM1-2-HR:
+                color: C0
+              MPI-ESM1-2-LR:
+                color: C1
+              ESACCI-CLOUD:
+                color: black
+            pyplot_kwargs:
+              title: '{short_name}'
diff --git a/esmvaltool/recipes/model_evaluation/recipe_model_evaluation_precip_zonal.yml b/esmvaltool/recipes/model_evaluation/recipe_model_evaluation_precip_zonal.yml
new file mode 100644
index 0000000000..6bd1231046
--- /dev/null
+++ b/esmvaltool/recipes/model_evaluation/recipe_model_evaluation_precip_zonal.yml
@@ -0,0 +1,72 @@
+# ESMValTool
+---
+documentation:
+  title: Model evaluation with focus on precipitation.
+  description: >
+    Plot zonal mean plots of precipitation.
+  authors:
+    - lauer_axel
+    - schlund_manuel
+  maintainer:
+    - lauer_axel
+
+
+# Note: the following models are just examples
+datasets:
+  - {project: CMIP6, dataset: MPI-ESM1-2-HR, exp: historical, ensemble: r1i1p1f1, grid: gn}
+  - {project: CMIP6, dataset: MPI-ESM1-2-LR, exp: historical, ensemble: r1i1p1f1, grid: gn}
+
+# Note: for some observational datasets, we use preset time ranges due to
+# their limited temporal availability
+timerange_for_models: &time_period
+  timerange: '2000/2014'  # can be specified, this is just an example
+
+
+preprocessors:
+
+  pp_zonal:
+    regrid:
+      target_grid: 2x2
+      scheme:
+        reference: esmf_regrid.schemes:ESMFAreaWeighted
+    zonal_statistics:
+      operator: mean
+    climate_statistics:
+      operator: mean
+      period: full
+    convert_units:
+      units: mm day-1
+
+
+diagnostics:
+
+  zonal:
+    description: Plot annual cycles including reference datasets.
+    variables:
+      pr:
+        <<: *time_period
+        preprocessor: pp_zonal
+        mip: Amon
+        additional_datasets:
+          - {dataset: ERA5, project: native6, type: reanaly, version: 'v1', tier: 3}
+          - {dataset: GPCP-SG, project: obs4MIPs, level: L3, version: v2.3, tier: 1}
+    scripts:
+      allplots:
+        script: monitor/multi_datasets.py
+        plot_folder: '{plot_dir}'
+        plot_filename: '{plot_type}_{real_name}_{mip}'
+        group_variables_by: variable_group
+        plots:
+          variable_vs_lat:
+            legend_kwargs:
+              loc: upper right
+            plot_kwargs:
+              MPI-ESM1-2-HR:
+                color: C0
+              MPI-ESM1-2-LR:
+                color: C1
+              ERA5:
+                color: black
+                linestyle: dotted
+              GPCP-SG:
+                color: black
diff --git a/esmvaltool/recipes/monitor/recipe_monitor_with_refs.yml b/esmvaltool/recipes/monitor/recipe_monitor_with_refs.yml
index e75cc763da..681277310c 100644
--- a/esmvaltool/recipes/monitor/recipe_monitor_with_refs.yml
+++ b/esmvaltool/recipes/monitor/recipe_monitor_with_refs.yml
@@ -1,7 +1,7 @@
 # ESMValTool
 ---
 documentation:
-  title: Model Monitoring
+  title: Example recipe for model monitoring with reference datasets.
   description: |
     Show plots that include multiple datasets that can be used to monitor
     (ongoing) model simulations.
diff --git a/esmvaltool/recipes/recipe_psyplot.yml b/esmvaltool/recipes/recipe_psyplot.yml
index 4a07f4c558..c34ee203f0 100644
--- a/esmvaltool/recipes/recipe_psyplot.yml
+++ b/esmvaltool/recipes/recipe_psyplot.yml
@@ -2,13 +2,13 @@
 # recipe_psyplot.yml
 ---
 documentation:
-  title: >
-    Create arbitrary Psyplot plots.
+  title: Example recipe for the Psyplot diagnostic.
 
   description: >
     This recipes showcases the use of the Psyplot diagnostic that provides a
     high-level interface to Psyplot for ESMValTool recipes. For each input
-    dataset, an individual plot is created.
+    dataset, an individual plot is created. With the Psyplot diagnostic,
+    arbitrary Psyplot plots can be created.
 
   authors:
     - schlund_manuel
diff --git a/esmvaltool/recipes/recipe_seaborn.yml b/esmvaltool/recipes/recipe_seaborn.yml
index faf0f07085..983efae0be 100644
--- a/esmvaltool/recipes/recipe_seaborn.yml
+++ b/esmvaltool/recipes/recipe_seaborn.yml
@@ -2,14 +2,14 @@
 # recipe_seaborn.yml
 ---
 documentation:
-  title: >
-    Create arbitrary Seaborn plots.
+  title: Example recipe for the Seaborn diagnostic.
 
   description: >
     This recipe showcases the use of the Seaborn diagnostic that provides a
     high-level interface to Seaborn for ESMValTool recipes. For this, the input
     data is arranged into a single `pandas.DataFrame`, which is then used as
-    input for the Seaborn function defined by the option `seaborn_func`.
+    input for the Seaborn function defined by the option `seaborn_func`. With
+    the Seaborn diagnostic, arbitrary Seaborn plots can be created.
 
   authors:
     - schlund_manuel

From baa2001f5cd1805d4a7168d418980b5c2fe0e504 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Fri, 1 Dec 2023 14:10:52 +0000
Subject: [PATCH 86/93] [Condalock] Update Linux condalock file (#3451)

Co-authored-by: valeriupredoi <valeriupredoi@users.noreply.github.com>
---
 conda-linux-64.lock | 96 ++++++++++++++++++++++-----------------------
 1 file changed, 47 insertions(+), 49 deletions(-)

diff --git a/conda-linux-64.lock b/conda-linux-64.lock
index 42d1ec03fc..b4ed02d1d9 100644
--- a/conda-linux-64.lock
+++ b/conda-linux-64.lock
@@ -10,7 +10,7 @@ https://conda.anaconda.org/conda-forge/noarch/cuda-version-11.8-h70ddcb2_2.conda
 https://conda.anaconda.org/conda-forge/noarch/font-ttf-dejavu-sans-mono-2.37-hab24e00_0.tar.bz2#0c96522c6bdaed4b1566d11387caaf45
 https://conda.anaconda.org/conda-forge/noarch/font-ttf-inconsolata-3.000-h77eed37_0.tar.bz2#34893075a5c9e55cdafac56607368fc6
 https://conda.anaconda.org/conda-forge/noarch/font-ttf-source-code-pro-2.038-h77eed37_0.tar.bz2#4d59c254e01d9cde7957100457e2d5fb
-https://conda.anaconda.org/conda-forge/noarch/font-ttf-ubuntu-0.83-hab24e00_0.tar.bz2#19410c3df09dfb12d1206132a1d357c5
+https://conda.anaconda.org/conda-forge/noarch/font-ttf-ubuntu-0.83-h77eed37_1.conda#6185f640c43843e5ad6fd1c5372c3f80
 https://conda.anaconda.org/conda-forge/noarch/kernel-headers_linux-64-2.6.32-he073ed8_16.conda#7ca122655873935e02c91279c5b03c8c
 https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.40-h41732ed_0.conda#7aca3059a1729aa76c597603f10b0dd3
 https://conda.anaconda.org/conda-forge/noarch/libgcc-devel_linux-64-13.2.0-ha9c7c90_103.conda#db8cd1a871a07404d94f7dcc78c21a61
@@ -30,7 +30,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-13.2.0-h807b86a_3.cond
 https://conda.anaconda.org/conda-forge/linux-64/aom-3.5.0-h27087fc_0.tar.bz2#a08150fd2298460cd1fcccf626305642
 https://conda.anaconda.org/conda-forge/linux-64/aws-c-common-0.8.23-hd590300_0.conda#cc4f06f7eedb1523f3b83fd0fb3942ff
 https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hd590300_5.conda#69b8b6202a07720f448be700e300ccf4
-https://conda.anaconda.org/conda-forge/linux-64/c-ares-1.22.1-hd590300_0.conda#8430bd266c7b2cfbda403f7585d5ee86
+https://conda.anaconda.org/conda-forge/linux-64/c-ares-1.23.0-hd590300_0.conda#d459949bc10f64dee1595c176c2e6291
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@@ -457,16 +457,17 @@ https://conda.anaconda.org/conda-forge/linux-64/eccodes-2.30.2-h1f30a5c_0.conda#
 https://conda.anaconda.org/conda-forge/linux-64/esmf-8.4.2-nompi_h20110ff_0.conda#11f5169aeff54ad7277476be8ba19ff7
 https://conda.anaconda.org/conda-forge/linux-64/gdal-3.7.0-py311h281082f_2.conda#fde4fad3c517cc80f32995696f45198d
 https://conda.anaconda.org/conda-forge/linux-64/gtk2-2.24.33-h90689f9_2.tar.bz2#957a0255ab58aaf394a91725d73ab422
-https://conda.anaconda.org/conda-forge/noarch/jupyter_client-8.6.0-pyhd8ed1ab_0.conda#6bd3f1069cdebb44c7ae9efb900e312d
 https://conda.anaconda.org/conda-forge/linux-64/librsvg-2.56.3-h98fae49_0.conda#620e754f4344f4c27259ff460a2b9c50
 https://conda.anaconda.org/conda-forge/linux-64/matplotlib-base-3.8.2-py311h54ef318_0.conda#9f80753bc008bfc9b95f39d9ff9f1694
-https://conda.anaconda.org/conda-forge/noarch/myproxyclient-2.1.0-pyhd8ed1ab_2.tar.bz2#363b0816e411feb0df925d4f224f026a
+https://conda.anaconda.org/conda-forge/noarch/myproxyclient-2.1.1-pyhd8ed1ab_0.conda#bcdbeb2b693eba886583a907840c6421
 https://conda.anaconda.org/conda-forge/noarch/nbformat-5.9.2-pyhd8ed1ab_0.conda#61ba076de6530d9301a0053b02f093d2
 https://conda.anaconda.org/conda-forge/linux-64/netcdf4-1.6.4-nompi_py311h4d7c953_100.conda#c03492d0342e512e58aa2d6c5fdaaa91
 https://conda.anaconda.org/conda-forge/noarch/patsy-0.5.3-pyhd8ed1ab_0.tar.bz2#50ef6b29b1fb0768ca82c5aeb4fb2d96
 https://conda.anaconda.org/conda-forge/noarch/pep8-naming-0.10.0-pyh9f0ad1d_0.tar.bz2#b3c5536e4f9f58a4b16adb6f1e11732d
 https://conda.anaconda.org/conda-forge/noarch/pre-commit-3.5.0-pyha770c72_0.conda#964e3d762e427661c59263435a14c492
-https://conda.anaconda.org/conda-forge/noarch/pylint-plugin-utils-0.7-pyhd8ed1ab_0.tar.bz2#1657976383aee04dbb3ae3bdf654bb58
+https://conda.anaconda.org/conda-forge/noarch/pylint-celery-0.3-py_1.tar.bz2#e29456a611a62d3f26105a2f9c68f759
+https://conda.anaconda.org/conda-forge/noarch/pylint-django-2.5.3-pyhd8ed1ab_0.tar.bz2#00d8853fb1f87195722ea6a582cc9b56
+https://conda.anaconda.org/conda-forge/noarch/pylint-flask-0.6-py_0.tar.bz2#5a9afd3d0a61b08d59eed70fab859c1b
 https://conda.anaconda.org/conda-forge/linux-64/python-stratify-0.3.0-py311h1f0f07a_1.conda#cd36a89a048ad2bcc6d8b43f648fb1d0
 https://conda.anaconda.org/conda-forge/linux-64/r-base-4.1.3-hfabd6f2_9.conda#0ab4cf54fbddc0cc9ff260c6f77f8c84
 https://conda.anaconda.org/conda-forge/linux-64/rasterio-1.3.8-py311h41e4db2_0.conda#b35deb26af1d7e0d98438c8ac5c6b7b2
@@ -479,7 +480,7 @@ https://conda.anaconda.org/conda-forge/linux-64/cartopy-0.22.0-py311h320fe9a_1.c
 https://conda.anaconda.org/conda-forge/noarch/cf_xarray-0.8.6-pyhd8ed1ab_0.conda#2e33e3bdf2b1a79989ad792ac22104d3
 https://conda.anaconda.org/conda-forge/noarch/cmocean-3.0.3-pyhd8ed1ab_0.conda#eec7df83d725696d32c7bf99aff21d82
 https://conda.anaconda.org/conda-forge/noarch/dask-jobqueue-0.8.2-pyhd8ed1ab_0.conda#cc344a296a41369bcb05f7216661cec8
-https://conda.anaconda.org/conda-forge/noarch/esgf-pyclient-0.3.1-pyh1a96a4e_2.tar.bz2#64068564a9c2932bf30e9b4ec567927d
+https://conda.anaconda.org/conda-forge/noarch/esgf-pyclient-0.3.1-pyhca7485f_3.conda#1d43833138d38ad8324700ce45a7099a
 https://conda.anaconda.org/conda-forge/noarch/esmpy-8.4.2-pyhc1e730c_4.conda#ddcf387719b2e44df0cc4dd467643951
 https://conda.anaconda.org/conda-forge/linux-64/fiona-1.9.4-py311hbac4ec9_0.conda#1d3445f5f7fa002a1c149c405376f012
 https://conda.anaconda.org/conda-forge/linux-64/graphviz-8.1.0-h28d9a01_0.conda#33628e0e3de7afd2c8172f76439894cb
@@ -489,11 +490,9 @@ https://conda.anaconda.org/conda-forge/noarch/nbclient-0.8.0-pyhd8ed1ab_0.conda#
 https://conda.anaconda.org/conda-forge/noarch/nc-time-axis-1.4.1-pyhd8ed1ab_0.tar.bz2#281b58948bf60a2582de9e548bcc5369
 https://conda.anaconda.org/conda-forge/linux-64/ncl-6.6.2-hf70af60_47.conda#ee27133164cb9f5e74681bdb8839688f
 https://conda.anaconda.org/conda-forge/linux-64/nco-5.1.6-hd62b316_0.conda#af7780f76ee37325d264327e21a478f5
+https://conda.anaconda.org/conda-forge/noarch/prospector-1.10.3-pyhd8ed1ab_0.conda#f551d4d859a1d70c6abff8310a655481
 https://conda.anaconda.org/conda-forge/linux-64/psyplot-1.4.3-py311h38be061_1.tar.bz2#f0c9a1067c03e8f05e53ef0c5ad5fab3
 https://conda.anaconda.org/conda-forge/linux-64/py-xgboost-1.7.6-cuda118_py311h0be3a32_6.conda#e9989e03af742084940a11c7c3c395a5
-https://conda.anaconda.org/conda-forge/noarch/pylint-celery-0.3-py_1.tar.bz2#e29456a611a62d3f26105a2f9c68f759
-https://conda.anaconda.org/conda-forge/noarch/pylint-django-2.5.3-pyhd8ed1ab_0.tar.bz2#00d8853fb1f87195722ea6a582cc9b56
-https://conda.anaconda.org/conda-forge/noarch/pylint-flask-0.6-py_0.tar.bz2#5a9afd3d0a61b08d59eed70fab859c1b
 https://conda.anaconda.org/conda-forge/noarch/r-abind-1.4_5-r41hc72bb7e_1004.tar.bz2#831186670e5786df30f8ddeb5a623c5a
 https://conda.anaconda.org/conda-forge/linux-64/r-backports-1.4.1-r41h06615bd_1.tar.bz2#9a00c3283f8fb4bce68deffe08fbe09d
 https://conda.anaconda.org/conda-forge/noarch/r-bigmemory.sri-0.1.6-r41hc72bb7e_0.tar.bz2#926471a5be30d287a25f2d10446d6066
@@ -566,7 +565,6 @@ https://conda.anaconda.org/conda-forge/noarch/iris-3.7.0-pyha770c72_0.conda#dccc
 https://conda.anaconda.org/conda-forge/noarch/lime-0.2.0.1-pyhd8ed1ab_1.tar.bz2#789ce01416721a5533fb74aa4361fd13
 https://conda.anaconda.org/conda-forge/noarch/mapgenerator-1.0.7-pyhd8ed1ab_0.conda#d18db96ef2a920b0ecefe30282b0aecf
 https://conda.anaconda.org/conda-forge/noarch/nbconvert-core-7.11.0-pyhd8ed1ab_0.conda#d59e0cb1ca993f8f910cfdf393232acf
-https://conda.anaconda.org/conda-forge/noarch/prospector-1.10.3-pyhd8ed1ab_0.conda#f551d4d859a1d70c6abff8310a655481
 https://conda.anaconda.org/conda-forge/linux-64/psy-simple-1.4.1-py311h38be061_2.tar.bz2#4c9101d329f6bc09c2617a80e3eb9c89
 https://conda.anaconda.org/conda-forge/noarch/py-cordex-0.6.6-pyhd8ed1ab_0.conda#255f9eac03143526c8aed41d1d091c63
 https://conda.anaconda.org/conda-forge/linux-64/pyarrow-12.0.1-py311h39c9aba_7_cpu.conda#d513ab8d10ec5f3ee45b419c836195ec
@@ -604,7 +602,7 @@ https://conda.anaconda.org/conda-forge/noarch/nbconvert-pandoc-7.11.0-pyhd8ed1ab
 https://conda.anaconda.org/conda-forge/noarch/prov-2.0.0-pyhd3deb0d_0.tar.bz2#aa9b3ad140f6c0668c646f32e20ccf82
 https://conda.anaconda.org/conda-forge/noarch/psy-maps-1.4.2-pyhd8ed1ab_0.tar.bz2#3ed13103dfd46f71dc870d188bd0b276
 https://conda.anaconda.org/conda-forge/linux-64/psy-reg-1.4.0-py311h38be061_3.conda#6f7871722c07922028043144e8873b37
-https://conda.anaconda.org/conda-forge/noarch/pyarrow-hotfix-0.5-pyhd8ed1ab_0.conda#a172245c7fdb6696f2ab357501e6d13e
+https://conda.anaconda.org/conda-forge/noarch/pyarrow-hotfix-0.6-pyhd8ed1ab_0.conda#ccc06e6ef2064ae129fab3286299abda
 https://conda.anaconda.org/conda-forge/noarch/python-cdo-1.6.0-pyhd8ed1ab_0.conda#3fd1a0b063c1fbbe4b7bd5a5a7601e84
 https://conda.anaconda.org/conda-forge/linux-64/r-akima-0.6_2.3-r41h92ddd45_0.tar.bz2#bac0b7627ef744c98f4bc48885f52e72
 https://conda.anaconda.org/conda-forge/noarch/r-callr-3.7.3-r41hc72bb7e_0.tar.bz2#af0891cc9b87e2954c9a3c66f144992d
@@ -652,7 +650,7 @@ https://conda.anaconda.org/conda-forge/noarch/r-lintr-3.0.2-r41hc72bb7e_0.tar.bz
 https://conda.anaconda.org/conda-forge/noarch/r-s2dverification-2.10.3-r41hc72bb7e_1.tar.bz2#2253f130c8dab435824d6ddb10a41c73
 https://conda.anaconda.org/conda-forge/noarch/autodocsumm-0.2.6-pyhd8ed1ab_0.tar.bz2#4409dd7e06a62c3b2aa9e96782c49c6d
 https://conda.anaconda.org/conda-forge/noarch/nbsphinx-0.9.3-pyhd8ed1ab_0.conda#0dbaa7d08d3d79b2a1a4dd6a02cc4581
-https://conda.anaconda.org/conda-forge/noarch/pydata-sphinx-theme-0.14.3-pyhd8ed1ab_1.conda#fbe2993dd48f14724b90bf12e92cc164
+https://conda.anaconda.org/conda-forge/noarch/pydata-sphinx-theme-0.14.4-pyhd8ed1ab_0.conda#c79b8443908032263ffb40ee6215e9e4
 https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-applehelp-1.0.7-pyhd8ed1ab_0.conda#aebfabcb60c33a89c1f9290cab49bc93
 https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-devhelp-1.0.5-pyhd8ed1ab_0.conda#ebf08f5184d8eaa486697bc060031953
 https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-htmlhelp-2.0.4-pyhd8ed1ab_0.conda#a9a89000dfd19656ad004b937eeb6828

From 1ed332753e06ee8f943c1d5b59d0a404d54b42f0 Mon Sep 17 00:00:00 2001
From: Lee de Mora <ledm@pml.ac.uk>
Date: Tue, 5 Dec 2023 12:53:01 +0000
Subject: [PATCH 87/93] Adding download_dir to recipe filler. (#3447)

Co-authored-by: Valeriu Predoi <valeriu.predoi@gmail.com>
---
 esmvaltool/utils/recipe_filler.py | 20 ++++++++++++++++++--
 1 file changed, 18 insertions(+), 2 deletions(-)

diff --git a/esmvaltool/utils/recipe_filler.py b/esmvaltool/utils/recipe_filler.py
index 91033a12c8..40f637c6d5 100755
--- a/esmvaltool/utils/recipe_filler.py
+++ b/esmvaltool/utils/recipe_filler.py
@@ -291,16 +291,31 @@ def read_config_user_file(config_file, folder_name, options=None):
 }
 
 
+def _get_download_dir(yamlconf, cmip_era):
+    """Get the Download Directory from user config file."""
+    if 'download_dir' in yamlconf:
+        return os.path.join(yamlconf['download_dir'], cmip_era)
+    return False
+
+
 def _get_site_rootpath(cmip_era):
     """Get site (drs) from config-user.yml."""
     config_yml = get_args().config_file
     with open(config_yml, 'r') as yamf:
         yamlconf = yaml.safe_load(yamf)
     drs = yamlconf['drs'][cmip_era]
-    rootdir = yamlconf['rootpath'][cmip_era]
+
+    download_dir = _get_download_dir(yamlconf, cmip_era)
+    rootdir = [yamlconf['rootpath'][cmip_era], ]
+
+    if download_dir:
+        rootdir.append(download_dir)
     logger.debug("%s root directory %s", cmip_era, rootdir)
     if drs == 'default' and 'default' in yamlconf['rootpath']:
-        rootdir = yamlconf['rootpath']['default']
+        rootdir = [yamlconf['rootpath']['default'], ]
+        if download_dir:
+            rootdir.append(download_dir)
+
         logger.debug("Using drs default and "
                      "default: %s data directory", rootdir)
 
@@ -327,6 +342,7 @@ def _determine_basepath(cmip_era):
         rootpaths = _get_site_rootpath(cmip_era)[1]
     else:
         rootpaths = [_get_site_rootpath(cmip_era)[1]]
+
     basepaths = []
     for rootpath in rootpaths:
         if _get_input_dir(cmip_era) != os.path.sep:

From 06d88128490bd6610162a70167d13f82fc621514 Mon Sep 17 00:00:00 2001
From: Bouwe Andela <b.andela@esciencecenter.nl>
Date: Wed, 6 Dec 2023 10:07:45 +0100
Subject: [PATCH 88/93] Add note about not removing communities and grants from
 .zenodo.json (#3417)

---
 doc/sphinx/source/community/code_documentation.rst | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/doc/sphinx/source/community/code_documentation.rst b/doc/sphinx/source/community/code_documentation.rst
index 82f8c3a8f7..1c211daf39 100644
--- a/doc/sphinx/source/community/code_documentation.rst
+++ b/doc/sphinx/source/community/code_documentation.rst
@@ -442,7 +442,10 @@ name to the list of authors in ``CITATION.cff`` and generate the entry for the
 ::
 
    pip install cffconvert
-   cffconvert --format zenodo --outfile .zenodo.json
+   cffconvert --infile CITATION.cff --format zenodo --outfile .zenodo.json
+
+Presently, this method unfortunately discards entries `communities`
+and `grants` from that file; please restore them manually.
 
 Note that authors of recipes and/or diagnostics also need to be added to the file
 `esmvaltool/config-references.yml <https://github.com/ESMValGroup/ESMValTool/blob/main/esmvaltool/config-references.yml>`__,

From 91ea9b44b46d164064c0e3e12ea8b83c4115149a Mon Sep 17 00:00:00 2001
From: Valeriu Predoi <valeriu.predoi@gmail.com>
Date: Thu, 7 Dec 2023 07:45:58 +0000
Subject: [PATCH 89/93] regenerate Anconda shield/badge not to have ESMValTool
 version hardcoded in image name (#3453)

Co-authored-by: Bouwe Andela <b.andela@esciencecenter.nl>
---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 694dab6a82..4fbe8aa84e 100644
--- a/README.md
+++ b/README.md
@@ -8,7 +8,7 @@
 [![Codacy Badge](https://app.codacy.com/project/badge/Coverage/79bf6932c2e844eea15d0fb1ed7e415c)](https://www.codacy.com/gh/ESMValGroup/ESMValTool?utm_source=github.com&utm_medium=referral&utm_content=ESMValGroup/ESMValTool&utm_campaign=Badge_Coverage)
 [![Codacy Badge](https://app.codacy.com/project/badge/Grade/79bf6932c2e844eea15d0fb1ed7e415c)](https://www.codacy.com/gh/ESMValGroup/ESMValTool?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=ESMValGroup/ESMValTool&amp;utm_campaign=Badge_Grade)
 [![Docker Build Status](https://img.shields.io/docker/cloud/build/esmvalgroup/esmvaltool.svg)](https://hub.docker.com/r/esmvalgroup/esmvaltool/)
-[![Anaconda-Server Badge](https://img.shields.io/badge/Anaconda.org-2.9.0-blue.svg)](https://anaconda.org/conda-forge/esmvaltool)
+[![Anaconda-Server Badge](https://img.shields.io/conda/vn/conda-forge/ESMValTool?color=blue&label=conda-forge&logo=conda-forge&logoColor=white)](https://anaconda.org/conda-forge/esmvaltool)
 ![stand with Ukraine](https://badgen.net/badge/stand%20with/UKRAINE/?color=0057B8&labelColor=FFD700)
 
 ![esmvaltoollogo](https://raw.githubusercontent.com/ESMValGroup/ESMValTool/main/doc/sphinx/source/figures/ESMValTool-logo-2.png)

From aea6b2888aefc0659e3564acc1c0fc403bef3e36 Mon Sep 17 00:00:00 2001
From: Valeriu Predoi <valeriu.predoi@gmail.com>
Date: Thu, 7 Dec 2023 17:04:35 +0000
Subject: [PATCH 90/93] clean up a bit CircleCI configuration (#3450)

---
 .circleci/config.yml | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/.circleci/config.yml b/.circleci/config.yml
index 47e87cf517..91cb7c17d3 100644
--- a/.circleci/config.yml
+++ b/.circleci/config.yml
@@ -27,6 +27,7 @@ commands:
           name: Log versions
           command: |
             . /opt/conda/etc/profile.d/conda.sh
+            conda env export --name base > /logs/base_environment.yml
             conda activate esmvaltool
             esmvaltool version
             dpkg -l > /logs/versions.txt
@@ -40,6 +41,7 @@ commands:
           command: |
             . /opt/conda/etc/profile.d/conda.sh
             conda activate esmvaltool
+            mamba --version
             pytest -n 4 --junitxml=test-reports/report.xml
             esmvaltool version
             esmvaltool -- --help
@@ -265,7 +267,7 @@ jobs:
             # Install prerequisites
             mkdir /logs
             # Install ESMValTool in a new conda environment
-            mamba create -y --name esmvaltool -c conda-forge esmvaltool julia 'python=3.10' >> /logs/conda.txt 2>&1
+            mamba create -y --name esmvaltool -c conda-forge esmvaltool julia 'python=3.11' >> /logs/conda.txt 2>&1
             # Activate the environment
             set +x; conda activate esmvaltool; set -x
             # install the Julia dependencies

From bcb202e06d5420f83ef76c1e2dec5a71e2869aec Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Mon, 11 Dec 2023 12:05:51 +0000
Subject: [PATCH 91/93] [Condalock] Update Linux condalock file (#3458)

Co-authored-by: valeriupredoi <valeriupredoi@users.noreply.github.com>
---
 conda-linux-64.lock | 74 ++++++++++++++++++++++-----------------------
 1 file changed, 37 insertions(+), 37 deletions(-)

diff --git a/conda-linux-64.lock b/conda-linux-64.lock
index b4ed02d1d9..b0facf9382 100644
--- a/conda-linux-64.lock
+++ b/conda-linux-64.lock
@@ -53,7 +53,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libaec-1.1.2-h59595ed_1.conda#12
 https://conda.anaconda.org/conda-forge/linux-64/libbrotlicommon-1.0.9-h166bdaf_9.conda#61641e239f96eae2b8492dc7e755828c
 https://conda.anaconda.org/conda-forge/linux-64/libcrc32c-1.1.2-h9c3ff4c_0.tar.bz2#c965a5aa0d5c1c37ffc62dff36e28400
 https://conda.anaconda.org/conda-forge/linux-64/libdeflate-1.18-h0b41bf4_0.conda#6aa9c9de5542ecb07fdda9ca626252d8
-https://conda.anaconda.org/conda-forge/linux-64/libev-4.33-h516909a_1.tar.bz2#6f8720dff19e17ce5d48cfe7f3d2f0a3
+https://conda.anaconda.org/conda-forge/linux-64/libev-4.33-hd590300_2.conda#172bf1cd1ff8629f2b1179945ed45055
 https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.5.0-hcb278e6_1.conda#6305a3dd2752c76335295da4e581f2fd
 https://conda.anaconda.org/conda-forge/linux-64/libffi-3.4.2-h7f98852_5.tar.bz2#d645c6d2ac96843a2bfaccd2d62b3ac3
 https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-13.2.0-ha4646dd_3.conda#c714d905cdfa0e70200f68b80cc04764
@@ -75,7 +75,7 @@ https://conda.anaconda.org/conda-forge/linux-64/lz4-c-1.9.4-hcb278e6_0.conda#318
 https://conda.anaconda.org/conda-forge/linux-64/lzo-2.10-h516909a_1000.tar.bz2#bb14fcb13341b81d5eb386423b9d2bac
 https://conda.anaconda.org/conda-forge/linux-64/make-4.3-hd18ef5c_1.tar.bz2#4049ebfd3190b580dffe76daed26155a
 https://conda.anaconda.org/conda-forge/linux-64/mbedtls-3.3.0-hcb278e6_0.conda#cc1213f464c357b647cc5dde5cfca881
-https://conda.anaconda.org/conda-forge/linux-64/metis-5.1.0-h59595ed_1007.conda#40ccb8318df2500f83bd868dd8fcd201
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 https://conda.anaconda.org/conda-forge/noarch/jsonschema-specifications-2023.11.2-pyhd8ed1ab_0.conda#73884ca36d6d96cbce498cde99fab40f
-https://conda.anaconda.org/conda-forge/linux-64/jupyter_core-5.5.0-py311h38be061_0.conda#cee83be29258275f75029125e186ab6d
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 https://conda.anaconda.org/conda-forge/linux-64/libspatialite-5.0.1-hca56755_27.conda#918a735059cab21b96fc13a8d04fbcd8
@@ -408,10 +409,9 @@ https://conda.anaconda.org/conda-forge/noarch/python-build-1.0.3-pyhd8ed1ab_0.co
 https://conda.anaconda.org/conda-forge/noarch/rdflib-7.0.0-pyhd8ed1ab_0.conda#44d14ef95495b3d4438f28998e0296a9
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-https://conda.anaconda.org/conda-forge/linux-64/suitesparse-5.10.1-h9e50725_1.tar.bz2#a3a685b5f9aeb890ed874502fe56accf
+https://conda.anaconda.org/conda-forge/linux-64/suitesparse-5.10.1-h3ec001c_2.conda#9b37d27528c5f86ee09bf1fc6834da8e
 https://conda.anaconda.org/conda-forge/linux-64/tiledb-2.13.2-hd532e3d_0.conda#6d97164f19dbd27575ef1899b02dc1e0
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-https://conda.anaconda.org/conda-forge/noarch/virtualenv-20.24.7-pyhd8ed1ab_0.conda#db990278c2c00b268eed778de44f6057
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@@ -420,10 +420,10 @@ https://conda.anaconda.org/conda-forge/linux-64/cftime-1.6.3-py311h1f0f07a_0.con
 https://conda.anaconda.org/conda-forge/noarch/chart-studio-1.1.0-pyh9f0ad1d_0.tar.bz2#acd9a12a35e5a0221bdf39eb6e4811dc
 https://conda.anaconda.org/conda-forge/noarch/colorspacious-1.1.2-pyh24bf2e0_0.tar.bz2#b73afa0d009a51cabd3ec99c4d2ef4f3
 https://conda.anaconda.org/conda-forge/linux-64/contourpy-1.2.0-py311h9547e67_0.conda#40828c5b36ef52433e21f89943e09f33
-https://conda.anaconda.org/conda-forge/noarch/dask-core-2023.11.0-pyhd8ed1ab_0.conda#3bf8f5c3fbab9e0cfffdf5914f021854
+https://conda.anaconda.org/conda-forge/noarch/dask-core-2023.12.0-pyhd8ed1ab_0.conda#95eae0785aed72998493140dc0115382
 https://conda.anaconda.org/conda-forge/noarch/eofs-1.4.0-py_0.tar.bz2#6e166cd37cfeadefcfca1ffe00f222bb
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-https://conda.anaconda.org/conda-forge/noarch/identify-2.5.32-pyhd8ed1ab_0.conda#3ef8e9bab1bfaf900bb0a5db8c0c742c
+https://conda.anaconda.org/conda-forge/noarch/identify-2.5.33-pyhd8ed1ab_0.conda#93c8f8ceb83827d88deeba796f07fba7
 https://conda.anaconda.org/conda-forge/linux-64/imagecodecs-2023.8.12-py311h67b54e4_0.conda#363e5c2f2c67ff69d717aba54422b03d
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@@ -435,8 +435,9 @@ https://conda.anaconda.org/conda-forge/noarch/magics-python-1.5.8-pyhd8ed1ab_1.c
 https://conda.anaconda.org/conda-forge/linux-64/netcdf-fortran-4.6.1-nompi_h4f3791c_100.conda#405c5b3ad4ef53eb0d93043b54206dd7
 https://conda.anaconda.org/conda-forge/linux-64/numba-0.58.1-py311h96b013e_0.conda#06a0313ff3d2ec956a25767ccaf7c9f6
 https://conda.anaconda.org/conda-forge/linux-64/numcodecs-0.12.1-py311hb755f60_0.conda#38a2ff8ea433fe8792279b45e84b3730
-https://conda.anaconda.org/conda-forge/linux-64/pandas-2.1.3-py311h320fe9a_0.conda#3ea3486e16d559dfcb539070ed330a1e
+https://conda.anaconda.org/conda-forge/linux-64/pandas-2.1.4-py311h320fe9a_0.conda#e44ccb61b6621bf3f8053ae66eba7397
 https://conda.anaconda.org/conda-forge/linux-64/pango-1.50.14-heaa33ce_1.conda#cde553e0e32389e26595db4eacf859eb
+https://conda.anaconda.org/conda-forge/noarch/patsy-0.5.4-pyhd8ed1ab_0.conda#1184267eddebb57e47f8e1419c225595
 https://conda.anaconda.org/conda-forge/noarch/pooch-1.8.0-pyhd8ed1ab_0.conda#134b2b57b7865d2316a7cce1915a51ed
 https://conda.anaconda.org/conda-forge/noarch/pylint-plugin-utils-0.7-pyhd8ed1ab_0.tar.bz2#1657976383aee04dbb3ae3bdf654bb58
 https://conda.anaconda.org/conda-forge/noarch/pyopenssl-23.3.0-pyhd8ed1ab_0.conda#7819533e674dbbc51468f3228b9b1bb6
@@ -450,9 +451,9 @@ https://conda.anaconda.org/conda-forge/linux-64/shapely-2.0.1-py311h54d622a_1.co
 https://conda.anaconda.org/conda-forge/noarch/snuggs-1.4.7-py_0.tar.bz2#cb83a3d6ecf73f50117635192414426a
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 https://conda.anaconda.org/conda-forge/linux-64/aws-sdk-cpp-1.10.57-hbc2ea52_17.conda#452c7b08c21eea2ef01f4fd364d6affc
-https://conda.anaconda.org/conda-forge/noarch/bokeh-3.3.1-pyhd8ed1ab_0.conda#682d698da77e896c5e986b334ce8f0a5
+https://conda.anaconda.org/conda-forge/noarch/bokeh-3.3.2-pyhd8ed1ab_0.conda#c02a7e79365121bd3bcc25f1b65f48a9
 https://conda.anaconda.org/conda-forge/linux-64/cf-units-3.2.0-py311h1f0f07a_4.conda#1e105c1a8ea2163507726144b401eb1b
-https://conda.anaconda.org/conda-forge/noarch/distributed-2023.11.0-pyhd8ed1ab_0.conda#a1ee8e3043eee1649f98704ea3e6feae
+https://conda.anaconda.org/conda-forge/noarch/distributed-2023.12.0-pyhd8ed1ab_0.conda#22d620e1079e99c34578cb0c615d2789
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 https://conda.anaconda.org/conda-forge/linux-64/gdal-3.7.0-py311h281082f_2.conda#fde4fad3c517cc80f32995696f45198d
@@ -462,19 +463,19 @@ https://conda.anaconda.org/conda-forge/linux-64/matplotlib-base-3.8.2-py311h54ef
 https://conda.anaconda.org/conda-forge/noarch/myproxyclient-2.1.1-pyhd8ed1ab_0.conda#bcdbeb2b693eba886583a907840c6421
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-https://conda.anaconda.org/conda-forge/noarch/patsy-0.5.3-pyhd8ed1ab_0.tar.bz2#50ef6b29b1fb0768ca82c5aeb4fb2d96
 https://conda.anaconda.org/conda-forge/noarch/pep8-naming-0.10.0-pyh9f0ad1d_0.tar.bz2#b3c5536e4f9f58a4b16adb6f1e11732d
-https://conda.anaconda.org/conda-forge/noarch/pre-commit-3.5.0-pyha770c72_0.conda#964e3d762e427661c59263435a14c492
+https://conda.anaconda.org/conda-forge/noarch/pre-commit-3.6.0-pyha770c72_0.conda#473a7cfca197da0a10cff3f6dded7d4b
 https://conda.anaconda.org/conda-forge/noarch/pylint-celery-0.3-py_1.tar.bz2#e29456a611a62d3f26105a2f9c68f759
 https://conda.anaconda.org/conda-forge/noarch/pylint-django-2.5.3-pyhd8ed1ab_0.tar.bz2#00d8853fb1f87195722ea6a582cc9b56
 https://conda.anaconda.org/conda-forge/noarch/pylint-flask-0.6-py_0.tar.bz2#5a9afd3d0a61b08d59eed70fab859c1b
 https://conda.anaconda.org/conda-forge/linux-64/python-stratify-0.3.0-py311h1f0f07a_1.conda#cd36a89a048ad2bcc6d8b43f648fb1d0
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 https://conda.anaconda.org/conda-forge/linux-64/rasterio-1.3.8-py311h41e4db2_0.conda#b35deb26af1d7e0d98438c8ac5c6b7b2
-https://conda.anaconda.org/conda-forge/linux-64/scikit-learn-1.3.2-py311hc009520_1.conda#6b92d3d0680eae9d1d9860a721f7fb51
+https://conda.anaconda.org/conda-forge/linux-64/scikit-learn-1.3.2-py311hc009520_2.conda#9821f8e497a791858226f535e5e0be62
 https://conda.anaconda.org/conda-forge/noarch/sparse-0.14.0-pyhd8ed1ab_0.conda#ee01b310177a0612554b9d20e537fdbe
-https://conda.anaconda.org/conda-forge/noarch/tifffile-2023.9.26-pyhd8ed1ab_0.conda#d133bea7d8ac17552492a0629229eeb1
-https://conda.anaconda.org/conda-forge/noarch/xarray-2023.11.0-pyhd8ed1ab_0.conda#f445b20bac3db8f604a48592087b2d8f
+https://conda.anaconda.org/conda-forge/linux-64/statsmodels-0.14.0-py311h1f0f07a_2.conda#8f1e772e5430ce48229740ec00a90b61
+https://conda.anaconda.org/conda-forge/noarch/tifffile-2023.12.9-pyhd8ed1ab_0.conda#454bc0aff84f35fa53ba9e0369737a9b
+https://conda.anaconda.org/conda-forge/noarch/xarray-2023.12.0-pyhd8ed1ab_0.conda#e9b31d3ab1b0dd5fd8c24419f6560b90
 https://conda.anaconda.org/conda-forge/noarch/zarr-2.16.1-pyhd8ed1ab_0.conda#59ec835edbee50266b7bdbadab7ba335
 https://conda.anaconda.org/conda-forge/linux-64/cartopy-0.22.0-py311h320fe9a_1.conda#10d1806e20da040c58c36deddf51c70c
 https://conda.anaconda.org/conda-forge/noarch/cf_xarray-0.8.6-pyhd8ed1ab_0.conda#2e33e3bdf2b1a79989ad792ac22104d3
@@ -558,13 +559,12 @@ https://conda.anaconda.org/conda-forge/noarch/r-xmlparsedata-1.0.5-r41hc72bb7e_1
 https://conda.anaconda.org/conda-forge/linux-64/r-yaml-2.3.7-r41h133d619_0.conda#4af88071a607237aa73a3cbd51788a39
 https://conda.anaconda.org/conda-forge/linux-64/scikit-image-0.22.0-py311h320fe9a_2.conda#e94b7f09b52628b89e66cdbd8c3029dd
 https://conda.anaconda.org/conda-forge/noarch/seaborn-base-0.13.0-pyhd8ed1ab_0.conda#082666331726b2438986cfe33ae9a8ee
-https://conda.anaconda.org/conda-forge/linux-64/statsmodels-0.14.0-py311h1f0f07a_2.conda#8f1e772e5430ce48229740ec00a90b61
 https://conda.anaconda.org/conda-forge/linux-64/cdo-2.2.0-he026af2_4.conda#6c00b0a21b3de8a149eee137e83465d3
 https://conda.anaconda.org/conda-forge/linux-64/imagemagick-7.1.1_15-pl5321hf48ede7_0.conda#53c9f7169b61e615d5f41c8d70a72c00
 https://conda.anaconda.org/conda-forge/noarch/iris-3.7.0-pyha770c72_0.conda#dccc1f660bf455c239adaabf56b91dc9
 https://conda.anaconda.org/conda-forge/noarch/lime-0.2.0.1-pyhd8ed1ab_1.tar.bz2#789ce01416721a5533fb74aa4361fd13
 https://conda.anaconda.org/conda-forge/noarch/mapgenerator-1.0.7-pyhd8ed1ab_0.conda#d18db96ef2a920b0ecefe30282b0aecf
-https://conda.anaconda.org/conda-forge/noarch/nbconvert-core-7.11.0-pyhd8ed1ab_0.conda#d59e0cb1ca993f8f910cfdf393232acf
+https://conda.anaconda.org/conda-forge/noarch/nbconvert-core-7.12.0-pyhd8ed1ab_0.conda#4d67c68fd0d130091ada039bc2d81b33
 https://conda.anaconda.org/conda-forge/linux-64/psy-simple-1.4.1-py311h38be061_2.tar.bz2#4c9101d329f6bc09c2617a80e3eb9c89
 https://conda.anaconda.org/conda-forge/noarch/py-cordex-0.6.6-pyhd8ed1ab_0.conda#255f9eac03143526c8aed41d1d091c63
 https://conda.anaconda.org/conda-forge/linux-64/pyarrow-12.0.1-py311h39c9aba_7_cpu.conda#d513ab8d10ec5f3ee45b419c836195ec
@@ -598,7 +598,7 @@ https://conda.anaconda.org/conda-forge/linux-64/r-zoo-1.8_12-r41h133d619_0.conda
 https://conda.anaconda.org/conda-forge/noarch/seaborn-0.13.0-hd8ed1ab_0.conda#ebd31a95a7008b7e164dad9dbbb5bb5a
 https://conda.anaconda.org/conda-forge/noarch/xesmf-0.8.2-pyhd8ed1ab_0.conda#8e765a0eca0ce1cfa889cd9af82a23a8
 https://conda.anaconda.org/conda-forge/linux-64/xgboost-1.7.6-cuda118_py311h0be3a32_6.conda#f061993f8ed8ca90d2bb6a547a47109f
-https://conda.anaconda.org/conda-forge/noarch/nbconvert-pandoc-7.11.0-pyhd8ed1ab_0.conda#51bd005efab7e5c5c2af2570327bd213
+https://conda.anaconda.org/conda-forge/noarch/nbconvert-pandoc-7.12.0-pyhd8ed1ab_0.conda#460d7cac50322a39b61a833885a6a8d5
 https://conda.anaconda.org/conda-forge/noarch/prov-2.0.0-pyhd3deb0d_0.tar.bz2#aa9b3ad140f6c0668c646f32e20ccf82
 https://conda.anaconda.org/conda-forge/noarch/psy-maps-1.4.2-pyhd8ed1ab_0.tar.bz2#3ed13103dfd46f71dc870d188bd0b276
 https://conda.anaconda.org/conda-forge/linux-64/psy-reg-1.4.0-py311h38be061_3.conda#6f7871722c07922028043144e8873b37
@@ -621,8 +621,8 @@ https://conda.anaconda.org/conda-forge/noarch/r-scales-1.2.1-r41hc72bb7e_1.tar.b
 https://conda.anaconda.org/conda-forge/linux-64/r-specsverification-0.5_3-r41ha503ecb_3.conda#2bc51f0d44b98092ba57cf2f8671b490
 https://conda.anaconda.org/conda-forge/linux-64/r-splancs-2.01_43-r41h8da6f51_1.tar.bz2#3a6aad0706541141d10e3b514467a080
 https://conda.anaconda.org/conda-forge/linux-64/r-vctrs-0.6.2-r41ha503ecb_0.conda#1f7610a1863648cab254a9f85bd29dcd
-https://conda.anaconda.org/conda-forge/noarch/dask-2023.11.0-pyhd8ed1ab_0.conda#b77d7b91f78b3c50cceb19eb1611a6cf
-https://conda.anaconda.org/conda-forge/noarch/nbconvert-7.11.0-pyhd8ed1ab_0.conda#e492b36cbea1c83d1663fa73a8abff9b
+https://conda.anaconda.org/conda-forge/noarch/dask-2023.12.0-pyhd8ed1ab_0.conda#5cfc00e93b71fba459bede86419d0f01
+https://conda.anaconda.org/conda-forge/noarch/nbconvert-7.12.0-pyhd8ed1ab_0.conda#364e28ab12477494e72839aaa588073d
 https://conda.anaconda.org/conda-forge/noarch/r-cyclocomp-1.1.0-r41hc72bb7e_1005.tar.bz2#800e1da5bf774be48934b8865dd78d33
 https://conda.anaconda.org/conda-forge/noarch/r-gridextra-2.3-r41hc72bb7e_1004.tar.bz2#71ebed7e976df735ff3443bb88bd154f
 https://conda.anaconda.org/conda-forge/noarch/r-httr-1.4.6-r41hc72bb7e_0.conda#53dbb769c96782db54bf2d414fc9b239

From 8795e6be27107447404d68ce6b7a6f295f109495 Mon Sep 17 00:00:00 2001
From: Romain Beucher <romain.beucher@anu.edu.au>
Date: Mon, 11 Dec 2023 23:10:26 +1100
Subject: [PATCH 92/93] Add note for the NSDIC cmoriser (requires PROJ9.3)
 (#3457)

---
 doc/sphinx/source/input.rst | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/doc/sphinx/source/input.rst b/doc/sphinx/source/input.rst
index ed47c96857..4ff7bbb100 100644
--- a/doc/sphinx/source/input.rst
+++ b/doc/sphinx/source/input.rst
@@ -393,7 +393,7 @@ A list of the datasets for which a CMORizers is available is provided in the fol
 +------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+
 | NOAAGlobalTemp               | tasa (Amon)                                                                                          |   2  | Python          |
 +------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+
-| NSIDC-0116-[nh|sh]           | usi, vsi (day)                                                                                       |   3  | Python          |
+| NSIDC-0116-[nh|sh] [#note4]_ | usi, vsi (day)                                                                                       |   3  | Python          |
 +------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+
 | OceanSODA-ETHZ               | areacello (Ofx), co3os, dissicos, fgco2, phos, spco2, talkos (Omon)                                  |   2  | Python          |
 +------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+
@@ -433,6 +433,10 @@ A list of the datasets for which a CMORizers is available is provided in the fol
             can be found in the corresponding section of `recipe_check_obs.yml
             <https://github.com/ESMValGroup/ESMValTool/blob/main/esmvaltool/recipes/examples/recipe_check_obs.yml>`__.
 
+.. [#note4] The cmoriser requires PROJ>=9.3. Previous version of PROJ will return an error:
+            ``Internal Proj Error: proj_create: unhandled axis direction: UNKNOWN)``
+            You can check the version of PROJ in your conda environment by running:
+            ``conda list PROJ``.
 
 .. _inputdata_native_datasets:
 

From b3e73c9b03fe65b150815288d8dd48c475f5d50c Mon Sep 17 00:00:00 2001
From: Valeriu Predoi <valeriu.predoi@gmail.com>
Date: Tue, 12 Dec 2023 13:23:22 +0000
Subject: [PATCH 93/93] [CircleCI] allow for medium (vs small, previously)
 resources for build documentation test (#3459)

---
 .circleci/config.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.circleci/config.yml b/.circleci/config.yml
index 91cb7c17d3..5be43d58c6 100644
--- a/.circleci/config.yml
+++ b/.circleci/config.yml
@@ -234,7 +234,7 @@ jobs:
     # Test building documentation
     docker:
       - image: condaforge/mambaforge:latest
-    resource_class: small
+    resource_class: medium
     steps:
       - checkout
       - run: