Merge branch 'main' into update_cru_cmorizer

.circleci/config.yml

@@ -258,7 +258,7 @@ jobs:
     # Test conda package installation
     docker:
       - image: condaforge/mambaforge:latest
-    resource_class: medium
+    resource_class: large
     steps:
       - run:
           command: |

doc/sphinx/source/recipes/recipe_clouds.rst

@@ -30,6 +30,9 @@ Four recipes are available to evaluate cloud climatologies from CMIP models.
    estimated as the relative temporal standard deviation from multi-year timeseries
    of data with the temporal standard deviations calculated from monthly anomalies
    after subtracting the climatological mean seasonal cycle.
+   Note that the satellite observations used in the original recipe (UWisc) is not
+   maintained anymore and has been superseeded by MAC-LWP (`Elsaesser et al., 2017`_).
+   We recommend using MAC-LWP.
 
 4) Recipe family recipe_lauer22jclim_*.yml is an extension of
    recipe_lauer13jclim.yml for evaluation of cloud radiative forcing
@@ -49,6 +52,7 @@ Four recipes are available to evaluate cloud climatologies from CMIP models.
 .. _`Flato et al., 2013`: https://www.ipcc.ch/site/assets/uploads/2018/02/WG1AR5_Chapter09_FINAL.pdf
 .. _`Lauer and Hamilton (2013)`: https://journals.ametsoc.org/view/journals/clim/26/11/jcli-d-12-00451.1.xml
 .. _`Lauer et al. (2023)`: https://journals.ametsoc.org/view/journals/clim/36/2/JCLI-D-22-0181.1.xml
+.. _`Elsaesser et al., 2017`: https://journals.ametsoc.org/view/journals/clim/30/24/jcli-d-16-0902.1.xml
 
 
 Available recipes and diagnostics

esmvaltool/diag_scripts/monitor/multi_datasets.py

@@ -946,15 +946,24 @@ def _add_stats(self, plot_type, axes, dim_coords, dataset,
                 mean.data,
                 dataset['units'],
             )
-        axes.text(x_pos, y_pos, f"{mean.data:.2f}{cube.units}",
-                  fontsize=fontsize, transform=axes.transAxes)
+        if np.abs(mean.data) >= 0.1:
+            mean_val = f"{mean.data:.2f} {cube.units}"
+        else:
+            mean_val = f"{mean.data:.2e} {cube.units}"
+        axes.text(
+            x_pos, y_pos, mean_val, fontsize=fontsize, transform=axes.transAxes
+        )
         if ref_cube is None:
             return
 
         # Weighted RMSE
         rmse = (cube - ref_cube).collapsed(dim_coords, iris.analysis.RMS,
                                            weights=weights)
-        axes.text(x_pos_bias, y_pos, f"RMSE={rmse.data:.2f}{cube.units}",
+        if np.abs(rmse.data) >= 0.1:
+            rmse_val = f"{rmse.data:.2f} {cube.units}"
+        else:
+            rmse_val = f"{rmse.data:.2e} {cube.units}"
+        axes.text(x_pos_bias, y_pos, f"RMSE={rmse_val}",
                   fontsize=fontsize, transform=axes.transAxes)
         logger.info(
             "Area-weighted RMSE of %s for %s = %f%s",
@@ -1193,8 +1202,7 @@ def _plot_map_with_ref(self, plot_func, dataset, ref_dataset):
                             ref_dataset)
 
             # Customize plot
-            fig.suptitle(f"{dataset['long_name']} ({dataset['start_year']}-"
-                         f"{dataset['end_year']})")
+            fig.suptitle(dataset['long_name'])
             self._process_pyplot_kwargs(plot_type, dataset)
 
             # Rasterization
@@ -1249,8 +1257,7 @@ def _plot_map_without_ref(self, plot_func, dataset):
 
             # Customize plot
             axes.set_title(self._get_label(dataset))
-            fig.suptitle(f"{dataset['long_name']} ({dataset['start_year']}-"
-                         f"{dataset['end_year']})")
+            fig.suptitle(dataset['long_name'])
             self._process_pyplot_kwargs(plot_type, dataset)
 
             # Rasterization
@@ -1351,8 +1358,7 @@ def _plot_zonal_mean_profile_with_ref(self, plot_func, dataset,
                             ref_dataset)
 
             # Customize plot
-            fig.suptitle(f"{dataset['long_name']} ({dataset['start_year']}-"
-                         f"{dataset['end_year']})")
+            fig.suptitle(dataset['long_name'])
             self._process_pyplot_kwargs(plot_type, dataset)
 
             # Rasterization
@@ -1404,8 +1410,7 @@ def _plot_zonal_mean_profile_without_ref(self, plot_func, dataset):
 
             # Customize plot
             axes.set_title(self._get_label(dataset))
-            fig.suptitle(f"{dataset['long_name']} ({dataset['start_year']}-"
-                         f"{dataset['end_year']})")
+            fig.suptitle(dataset['long_name'])
             axes.set_xlabel('latitude [°N]')
             z_coord = cube.coord(axis='Z')
             axes.set_ylabel(f'{z_coord.long_name} [{z_coord.units}]')
@@ -1463,8 +1468,7 @@ def _plot_hovmoeller_z_vs_time_without_ref(self, plot_func, dataset):
 
             # Customize plot
             axes.set_title(self._get_label(dataset))
-            fig.suptitle(f"{dataset['long_name']} ({dataset['start_year']}-"
-                         f"{dataset['end_year']})")
+            fig.suptitle(dataset['long_name'])
             z_coord = cube.coord(axis='Z')
             axes.set_ylabel(f'{z_coord.long_name} [{z_coord.units}]')
             if self.plots[plot_type]['log_y']:
@@ -1590,8 +1594,7 @@ def _plot_hovmoeller_z_vs_time_with_ref(self, plot_func, dataset,
                             ref_dataset)
 
             # Customize plot
-            fig.suptitle(f"{dataset['long_name']} ({dataset['start_year']}-"
-                         f"{dataset['end_year']})")
+            fig.suptitle(dataset['long_name'])
             self._process_pyplot_kwargs(plot_type, dataset)
 
             # Rasterization
@@ -1699,8 +1702,7 @@ def _plot_hovmoeller_time_vs_lat_or_lon_with_ref(self, plot_func, dataset,
             cbar_bias.ax.tick_params(labelsize=fontsize)
 
             # Customize plot
-            fig.suptitle(f"{dataset['long_name']} ({dataset['start_year']}-"
-                         f"{dataset['end_year']})")
+            fig.suptitle(dataset['long_name'])
             self._process_pyplot_kwargs(plot_type, dataset)
 
             # Rasterization
@@ -1752,8 +1754,7 @@ def _plot_hovmoeller_time_vs_lat_or_lon_without_ref(self, plot_func,
 
             # Customize plot
             axes.set_title(self._get_label(dataset))
-            fig.suptitle(f"{dataset['long_name']} ({dataset['start_year']}-"
-                         f"{dataset['end_year']})")
+            fig.suptitle(dataset['long_name'])
             if 'latitude' in dim_coords_dat:
                 axes.set_xlabel('latitude [°N]')
             elif 'longitude' in dim_coords_dat:
@@ -1842,7 +1843,7 @@ def _get_multi_dataset_facets(datasets):
         multi_dataset_facets = {}
         for key in all_keys:
             if all(d.get(key) == datasets[0].get(key) for d in datasets):
-                multi_dataset_facets[key] = datasets[0][key]
+                multi_dataset_facets[key] = datasets[0].get(key)
             else:
                 multi_dataset_facets[key] = f'ambiguous_{key}'
         return multi_dataset_facets
@@ -2058,8 +2059,7 @@ def create_map_plot(self, datasets):
                 )
                 caption = (
                     f"Map plot of {dataset['long_name']} of dataset "
-                    f"{dataset['dataset']} (project {dataset['project']}) "
-                    f"from {dataset['start_year']} to {dataset['end_year']}."
+                    f"{dataset['dataset']} (project {dataset['project']})."
                 )
             else:
                 (plot_path, netcdf_paths) = (
@@ -2069,8 +2069,7 @@ def create_map_plot(self, datasets):
                     f"Map 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']}."
+                    f"(project {ref_dataset['project']})."
                 )
                 ancestors.append(ref_dataset['filename'])
 
@@ -2135,8 +2134,7 @@ def create_zonal_mean_profile_plot(self, datasets):
                 )
                 caption = (
                     f"Zonal mean profile of {dataset['long_name']} of dataset "
-                    f"{dataset['dataset']} (project {dataset['project']}) "
-                    f"from {dataset['start_year']} to {dataset['end_year']}."
+                    f"{dataset['dataset']} (project {dataset['project']})."
                 )
             else:
                 (plot_path, netcdf_paths) = (
@@ -2147,8 +2145,7 @@ def create_zonal_mean_profile_plot(self, datasets):
                     f"Zonal mean profile 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']}."
+                    f"(project {ref_dataset['project']})."
                 )
                 ancestors.append(ref_dataset['filename'])
 
@@ -2390,8 +2387,8 @@ def create_hovmoeller_z_vs_time_plot(self, datasets):
                 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']}.")
+                    f"{dataset['dataset']} (project {dataset['project']})."
+                )
             else:
                 (plot_path,
                  netcdf_paths) = (self._plot_hovmoeller_z_vs_time_with_ref(
@@ -2401,8 +2398,8 @@ def create_hovmoeller_z_vs_time_plot(self, datasets):
                     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']}.")
+                    f"(project {ref_dataset['project']})."
+                )
                 ancestors.append(ref_dataset['filename'])
 
             # If statistics are shown add a brief description to the caption
@@ -2467,8 +2464,7 @@ def create_hovmoeller_time_vs_lat_or_lon_plot(self, datasets):
                 )
                 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']}."
+                    f"{dataset['dataset']} (project {dataset['project']})."
                 )
             else:
                 (plot_path, netcdf_paths) = (
@@ -2479,8 +2475,7 @@ def create_hovmoeller_time_vs_lat_or_lon_plot(self, datasets):
                     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']}."
+                    f"(project {ref_dataset['project']})."
                 )
                 ancestors.append(ref_dataset['filename'])
 

esmvaltool/diag_scripts/seaice_drift/seaice_drift.py

@@ -540,7 +540,8 @@ def __init__(self, polygon=None, lat=None, lon=None):
 
         polygon.append(polygon[0])
         self.transformer = Transformer.from_crs("WGS84",
-                                                "North_Pole_Stereographic")
+                                                "North_Pole_Stereographic",
+                                                always_xy=True)
 
         transformed = []
         for lon_val, lat_val in polygon:

esmvaltool/recipes/clouds/recipe_lauer13jclim.yml

@@ -142,6 +142,13 @@ diagnostics:
         mip: Amon
         derive: true
     additional_datasets:
+        # The original recipe uses the UWisc dataset that is not 
+        # maintained anymore by the authors and has been supersided
+        # by MAC-LWP (Elsaesser et al., 2017)
+        # https://doi.org/10.1175/JCLI-D-16-0902.1
+        # We recommend using MAC-LWP
+      #- {dataset: MAC-LWP, project: OBS, type: sat, version: v1,
+      #   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:

esmvaltool/recipes/model_evaluation/recipe_model_evaluation_clouds_clim.yml

@@ -3,8 +3,8 @@
 documentation:
   title: Model evaluation with focus on clouds.
   description: >
-    Plot climatologies several cloud-related variables of multi-year
-    simulations.
+    Plot climatologies and zonal mean profiles of several cloud-related
+    variables of multi-year simulations.
   authors:
     - bonnet_pauline
     - lauer_axel

esmvaltool/recipes/model_evaluation/recipe_model_evaluation_clouds_cycles.yml

@@ -3,7 +3,8 @@
 documentation:
   title: Model evaluation with focus on clouds.
   description: >
-    Plot annual cycles of several cloud-related variables of multi-year simulations.
+    Plot annual cycles of several cloud-related variables of multi-year
+    simulations.
   authors:
     - lauer_axel
     - schlund_manuel

esmvaltool/recipes/model_evaluation/recipe_model_evaluation_precip_zonal.yml

@@ -3,7 +3,7 @@
 documentation:
   title: Model evaluation with focus on precipitation.
   description: >
-    Plot zonal mean plots of precipitation.
+    Plot zonal mean precipitation.
   authors:
     - lauer_axel
     - schlund_manuel

esmvaltool/recipes/recipe_autoassess_landsurface_surfrad.yml

@@ -42,15 +42,15 @@ diagnostics:
         force_derivation: false
         mip: Amon
         additional_datasets:
-          - {dataset: CERES-EBAF,  project: obs4MIPs,  level: L3B,  version: Ed2-7,  start_year: 2001,  end_year: 2012, tier: 1}
+          - {dataset: CERES-EBAF,  project: obs4MIPs,  level: L3B,  start_year: 2001,  end_year: 2012, tier: 1}
       sftlf:
         mip: fx
       rlns: # Surf LW net all sky
         derive: true
         force_derivation: false
         mip: Amon
         additional_datasets:
-          - {dataset: CERES-EBAF,  project: obs4MIPs,  level: L3B,  version: Ed2-7,  start_year: 2001,  end_year: 2012, tier: 1}
+          - {dataset: CERES-EBAF,  project: obs4MIPs,  level: L3B,  start_year: 2001,  end_year: 2012, tier: 1}
       sftlf:
         mip: fx
     scripts: