changes regarding the review

esmvaltool/cmorizers/data/cmor_config/ESACCI-SST.yml

@@ -1,14 +1,14 @@
 ---
 # Common global attributes for Cmorizer output
+
 attributes:
   dataset_id: ESACCI-SST
-  version: '3.0-L4-analysis'
+  version: 3.0-L4-analysis
   tier: 3
   modeling_realm: sat
   project_id: OBS6
   source: 'dx.doi.org/10.5285/4a9654136a7148e39b7feb56f8bb02d2'
   reference: ["esacci-sst"]
-  comment: "Note that the variable tsStderr is an uncertainty not a standard error."
 
 # Variables to cmorize (here use only filename ending)
 variables:

esmvaltool/cmorizers/data/formatters/datasets/esacci_sst.py

@@ -15,13 +15,9 @@
    Go to https://services.ceda.ac.uk/cedasite/register/info/
    and create an account at CEDA if needed.
 
-Modification history
-   20240618-bock_lisa: update for v3.0
-   20201204-roberts_charles: written.
-   20201214-predoi_valeriu: approved.
-   20201214-lauer_axel: approved.
 """
 
+import copy
 import glob
 import logging
 import os
@@ -44,7 +40,7 @@
 logger = logging.getLogger(__name__)
 
 
-def extract_variable(raw_info, year):
+def extract_variable(raw_info):
     """Extract to all vars."""
     rawvar = raw_info['name']
     constraint = iris.NameConstraint(var_name=rawvar)
@@ -58,16 +54,16 @@ def extract_variable(raw_info, year):
         try:
             cube = iris.load_cube(raw_info['file'], constraint)
         except iris.exceptions.ConstraintMismatchError as constraint_error:
-            raise ValueError(f"No data available for variable {rawvar}"
-                             f" and year {year}") from constraint_error
+            raise ValueError(f"No data available for variable {rawvar} in file"
+                             f" {raw_info['file']}") from constraint_error
 
     # Remove ancillary data
     for ancillary_variable in cube.ancillary_variables():
         cube.remove_ancillary_variable(ancillary_variable)
     return cube
 
 
-def get_monthly_cube(var, vals, raw_info, var_info, attrs,
+def get_monthly_cube(cfg, var, vals, raw_info, attrs,
                      inpfile_pattern, year, month):
     data_cubes = []
     month_inpfile_pattern = inpfile_pattern.format(
@@ -84,50 +80,62 @@ def get_monthly_cube(var, vals, raw_info, var_info, attrs,
         raw_info['file'] = inpfile
         logger.info("CMORizing var %s from file type %s", var,
                     raw_info['file'])
-        data_cubes.append(
-            extract_variable(raw_info, year))
+        data_cubes.append(extract_variable(raw_info))
 
     cube = concatenate(data_cubes)
 
     # regridding from 0.05x0.05 to 0.5x0.5
     cube = regrid(cube, target_grid='0.5x0.5', scheme='area_weighted')
+
+    #if var == 'tos': cube.attributes.pop('comment', None)
+
     # Fix dtype
     utils.fix_dtype(cube)
-    # Fix cube
-    fix_var_metadata(cube, var_info)
-    convert_timeunits(cube, year)
-    fix_coords(cube, overwrite_time_bounds=False)
-    set_global_atts(cube, attrs)
+    # Fix units
+    cmor_info = cfg['cmor_table'].get_variable(vals['mip'][0], var)
+    cube.convert_units(cmor_info.units)
+    # Fix metadata
+    fix_var_metadata(cube, cmor_info)
+    # Fix coordinates
+    #convert_timeunits(cube, year)
+    #fix_coords(cube, overwrite_time_bounds=False)
+    fix_coords(cube)
+    cube.coord('time').long_name = 'time'
+    cube.coord('latitude').long_name = 'latitude'
+    cube.coord('longitude').long_name = 'longitude'
     # Fix monthly time bounds
     time = cube.coord('time')
     time.bounds = get_time_bounds(time, vals['frequency'])
 
+    # set global attributes
+    set_global_atts(cube, attrs)
+
     return cube
 
 
 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']
+    glob_attrs = copy.deepcopy(cfg['attributes'])
 
     # run the cmorization
     for var, vals in cfg['variables'].items():
         if not start_date:
             start_date = datetime(vals['start_year'], 1, 1)
         if not end_date:
             end_date = datetime(vals['end_year'], 12, 31)
-        var_info = cmor_table.get_variable(vals['mip'][0], var)
-        glob_attrs['mip'] = vals['mip'][0]
         raw_info = {'name': vals['raw']}
         inpfile_pattern = os.path.join(in_dir, '{year}*' + vals['filename'])
         logger.info("CMORizing var %s from file type %s", var, inpfile_pattern)
         mon_cubes = []
         for year in range(start_date.year, end_date.year + 1):
             logger.info("Processing year %s", year)
-            for month in range(1, 13):
-                monthly_cube = get_monthly_cube(var, vals, raw_info, var_info,
+            glob_attrs['mip'] = vals['mip'][0]
+            for month in range(start_date.month, end_date.month + 1):
+                monthly_cube = get_monthly_cube(cfg, var, vals, raw_info,
                                                 glob_attrs, inpfile_pattern,
                                                 year, month)
+                logger.info(glob_attrs)
+                #set_global_atts(monthly_cube, glob_attrs)
                 # Save daily data
                 save_variable(monthly_cube,
                               var,

esmvaltool/recipes/examples/recipe_check_obs.yml

@@ -312,12 +312,13 @@ diagnostics:
     description: ESACCI-SST check
     variables:
       tos:
+        additional_datasets:
+          - {dataset: ESACCI-SST, project: OBS6, mip: Omon, tier: 3,
+             type: sat, version: 3.0-L4-analysis, timerange: '200301/200312'}
       tosStderr:
     additional_datasets:
-      - {dataset: ESACCI-SST, project: OBS6, mip: Omon, tier: 3,
-         type: sat, version: 3.0-L4-analysis, timerange: '200401/200412'}
       - {dataset: ESACCI-SST, project: OBS6, mip: Oday, tier: 3,
-         type: sat, version: 3.0-L4-analysis, timerange: '200401/200412'}
+         type: sat, version: 3.0-L4-analysis, timerange: '200301/200312'}
     scripts: null