Update ESACCI-SST cmorizer to v3.0

doc/sphinx/source/input.rst

@@ -310,7 +310,7 @@ A list of the datasets for which a CMORizers is available is provided in the fol
 +------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+
 | ESACCI-SOILMOISTURE          | dos, dosStderr, sm, smStderr (Lmon)                                                                  |   2  | NCL             |
 +------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+
-| ESACCI-SST                   | ts, tsStderr (Amon)                                                                                  |   2  | NCL             |
+| ESACCI-SST                   | tos, tosStderr (Omon, Oday)                                                                          |   3  | Python          |
 +------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+
 | ESACCI-WATERVAPOUR           | prw (Amon)                                                                                           |   3  | Python          |
 +------------------------------+------------------------------------------------------------------------------------------------------+------+-----------------+

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

@@ -1,29 +1,29 @@
 ---
 # Common global attributes for Cmorizer output
-filename: '{year}{month}15_regridded_sst.nc'
 attributes:
   dataset_id: ESACCI-SST
-  version: '2.2'
-  tier: 2
+  version: '3.0-L4-analysis'
+  tier: 3
   modeling_realm: sat
-  project_id: OBS
-  source: 'http://surftemp.net/regridding/index.html'
-  reference: ["esacci-sst", "esacci-sst-bias-correction"]
+  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 prefix)
+# Variables to cmorize (here use only filename ending)
 variables:
-  ts:
-    mip: Amon
-    raw: sst
-    file: ESACCI-SST_sat_L4-GHRSST-SSTdepth-OSTIA-GLOB
-  tsStderr:
-    mip: Amon
-    raw: sst_uncertainty
-    file: ESACCI-SST_sat_L4-GHRSST-SSTdepth-OSTIA-GLOB
+  tos:
+    mip: [Oday, Omon]
+    raw: analysed_sst
+    frequency: day
+    filename: ESACCI-L4_GHRSST-SSTdepth-OSTIA-GLOB_CDR3.0-v02.0-fv01.0.nc
+    start_year: 1980
+    end_year: 2023
 
-# uncomment this part to produce sst cmorized data for ocean realm (Omon, tos)
-#  tos:
-#    mip: Omon
-#    raw: sst
-#    file: ESACCI-SST_sat_L4-GHRSST-SSTdepth-OSTIA-GLOB
+  tosStderr:
+    mip: [Oday]
+    raw: analysed_sst_uncertainty
+    frequency: day
+    filename: ESACCI-L4_GHRSST-SSTdepth-OSTIA-GLOB_CDR3.0-v02.0-fv01.0.nc
+    start_year: 1980
+    end_year: 2023

esmvaltool/cmorizers/data/datasets.yml

@@ -549,12 +549,12 @@ datasets:
       Put all files under a single directory (no subdirectories with years).
 
   ESACCI-SST:
-    tier: 2
-    source: ftp://anon-ftp.ceda.ac.uk/neodc/esacci/sst/data/
-    last_access: 2019-02-01
+    tier: 3
+    source: ftp3.ceda.ac.uk/neodc/eocis/data/global_and_regional/sea_surface_temperature/
+    last_access: 2024-07-01
     info: |
       Download the data from:
-        lt/Analysis/L4/v01.1/
+        CDR_v3/Analysis/L4/v3.0.1/ 
       Put all files under a single directory (no subdirectories with years).
 
   ESACCI-WATERVAPOUR:

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

@@ -0,0 +1,74 @@
+"""Script to download ESACCI-SST."""
+# Import required python modules
+import logging
+import os
+
+from datetime import datetime
+
+from dateutil import relativedelta
+
+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
+    """
+    if start_date is None:
+        start_date = datetime(2004, 1, 1)
+    if end_date is None:
+        end_date = datetime(2007, 12, 31)
+
+    loop_date = start_date
+
+    user = os.environ.get("ceda-user")
+    if user is None:
+        user = str(input("CEDA user name? "))
+        if user == "":
+            errmsg = ("A CEDA account is required to download CCI SST data."
+                      " Please visit https://services.ceda.ac.uk/cedasite/"
+                      "register/info/ to create an account at CEDA if needed.")
+            logger.error(errmsg)
+            raise ValueError
+
+    passwd = os.environ.get("ceda-passwd")
+    if passwd is None:
+        passwd = str(input("CEDA-password? "))
+
+    downloader = FTPDownloader(
+        config=config,
+        server='ftp3.ceda.ac.uk',
+        dataset=dataset,
+        dataset_info=dataset_info,
+        overwrite=overwrite,
+        user=user,
+        passwd=passwd,
+    )
+
+    downloader.connect()
+    downloader.set_cwd('neodc/eocis/data/global_and_regional/'
+                       'sea_surface_temperature/CDR_v3/Analysis/L4/v3.0.1/')
+
+    while loop_date <= end_date:
+        year = loop_date.year
+        month = loop_date.strftime("%m")
+        day = loop_date.strftime("%d")
+        downloader.download_folder(f'./{year}/{month}/{day}/')
+        loop_date += relativedelta.relativedelta(days=1)

esmvaltool/cmorizers/data/downloaders/ftp.py

@@ -35,16 +35,22 @@ class FTPDownloader(BaseDownloader):
     overwrite : bool
         Overwrite already downloaded files
     """
-    def __init__(self, config, server, dataset, dataset_info, overwrite):
+    def __init__(self, config, server, dataset, dataset_info, overwrite,
+                 user=None, passwd=None):
         super().__init__(config, dataset, dataset_info, overwrite)
         self._client = None
         self.server = server
+        self.user = user
+        self.passwd = passwd
 
     def connect(self):
         """Connect to the FTP server."""
         self._client = ftplib.FTP(self.server)
         logger.info(self._client.getwelcome())
-        self._client.login()
+        if self.user is None:
+            self._client.login()
+        else:
+            self._client.login(user=self.user, passwd=self.passwd)
 
     def set_cwd(self, path):
         """Set current working directory in the remote.

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

@@ -1,41 +1,36 @@
 """ESMValTool CMORizer for ESACCI-SST data.
 
 Tier
-   Tier 2: other freely-available dataset.
+   Tier 3: need to register at CEDA
 
 Source
-   http://surftemp.net/regridding/index.html
+   https://catalogue.ceda.ac.uk/uuid/4a9654136a7148e39b7feb56f8bb02d2
 
 Last access
-   20201214
+   20240628
 
 Download and processing instructions
-   Download the following files:
-     Go to http://surftemp.net/regridding/index.html
-     and request regridded data with the following options:
-       Time Resolution: monthly
-       Longitude Resolution: 0.5
-       Latitude Resolution: 0.5
-       Start Date: 1982-01-01
-       End Date: 2019-12-31
-       Exclude data above sea ice threshold: True
-         (Threshold: 100 %)
-       Include post-hoc SST bias adjustments: True
-       Output Absolute or Anomaly SST: absolute
-       Generate Sea Ice Fraction: True
-       Error Correlation in Time (Days): 7
-       Error Correlation In Space (Degrees): 3.0
+   A donwnloader is provided by ESMValTool. First you need
+   to register.
+   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 glob
 import logging
 import os
 
 import iris
+from datetime import datetime
+from esmvalcore.cmor.fixes import get_time_bounds
+from esmvalcore.preprocessor import regrid
+from esmvaltool.cmorizers.data import utilities as utils
 from esmvalcore.preprocessor import concatenate
 
 from ...utilities import (
@@ -49,23 +44,68 @@
 logger = logging.getLogger(__name__)
 
 
-def extract_variable(var_info, raw_info, attrs, year):
+def extract_variable(raw_info, year):
     """Extract to all vars."""
     rawvar = raw_info['name']
     constraint = iris.NameConstraint(var_name=rawvar)
-    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
+    if rawvar == 'analysed_sst_uncertainty':
+        tmp_cube = iris.load_cube(raw_info['file'],
+                                  iris.NameConstraint(var_name='analysed_sst'))
+        ancillary_var = tmp_cube.ancillary_variable('sea_water_temperature'
+                                                    ' standard_error')
+        cube = tmp_cube.copy(ancillary_var.core_data())
+    else:
+        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
 
+    # Remove ancillary data
+    for ancillary_variable in cube.ancillary_variables():
+        cube.remove_ancillary_variable(ancillary_variable)
+    ## regridding from 0.05x0.05 to 0.5x0.5
+    #cube = regrid(cube, target_grid='0.5x0.5', scheme='area_weighted')
+    return cube
+
+
+def get_monthly_cube(var, vals, raw_info, var_info, attrs,
+                     inpfile_pattern, year, month):
+    data_cubes = []
+    month_inpfile_pattern = inpfile_pattern.format(
+                            year=str(year)+"{:02}".format(month))
+    logger.info("Pattern: %s", month_inpfile_pattern)
+    inpfiles = sorted(glob.glob(month_inpfile_pattern))
+    if inpfiles == []:
+        logger.error("Could not find any files with this"
+                     " pattern %s", month_inpfile_pattern)
+        raise ValueError
+    logger.info("Found input files: %s", inpfiles)
+
+    for inpfile in inpfiles:
+        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))
+
+    cube = concatenate(data_cubes)
+
+    # regridding from 0.05x0.05 to 0.5x0.5
+    cube = regrid(cube, target_grid='0.5x0.5', scheme='area_weighted')
+    # Fix dtype
+    utils.fix_dtype(cube)
     # Fix cube
     fix_var_metadata(cube, var_info)
     convert_timeunits(cube, year)
-    fix_coords(cube)
+    fix_coords(cube, overwrite_time_bounds=False)
     set_global_atts(cube, attrs)
-    return cube
+    # Fix monthly time bounds
+    time = cube.coord('time')
+    time.bounds = get_time_bounds(time, vals['frequency'])
 
+    return cube
+
 
 def cmorization(in_dir, out_dir, cfg, cfg_user, start_date, end_date):
     """Cmorization func call."""
@@ -74,24 +114,46 @@ def cmorization(in_dir, out_dir, cfg, cfg_user, start_date, end_date):
 
     # run the cmorization
     for var, vals in cfg['variables'].items():
-        var_info = cmor_table.get_variable(vals['mip'], var)
-        glob_attrs['mip'] = vals['mip']
-        raw_info = {'name': vals['raw'], 'file': vals['file']}
-        inpfile = os.path.join(in_dir, cfg['filename'])
-        logger.info("CMORizing var %s from file type %s", var, inpfile)
-        years = range(1982, 2020)
-        months = ["0" + str(mo) for mo in range(1, 10)] + ["10", "11", "12"]
-        for year in years:
-            monthly_cubes = []
-            for month in months:
-                raw_info['file'] = inpfile.format(year=year, month=month)
-                logger.info("CMORizing var %s from file type %s", var,
-                            raw_info['file'])
-                cube = extract_variable(var_info, raw_info, glob_attrs, year)
-                monthly_cubes.append(cube)
-            yearly_cube = concatenate(monthly_cubes)
-            save_variable(yearly_cube,
-                          var,
-                          out_dir,
-                          glob_attrs,
-                          unlimited_dimensions=['time'])
+        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, inpfile_pattern,
+                                                year, month)
+                # Save daily data
+                save_variable(monthly_cube,
+                              var,
+                              out_dir,
+                              glob_attrs,
+                              unlimited_dimensions=['time'])
+                # Calculate monthly mean
+                if 'Stderr' not in var:
+                    logger.info("Calculating monthly mean")
+                    iris.coord_categorisation.add_month_number(monthly_cube,
+                                                               'time')
+                    iris.coord_categorisation.add_year(monthly_cube, 'time')
+                    monthly_cube = monthly_cube.aggregated_by(['month_number',
+                                    'year'], iris.analysis.MEAN)
+                    monthly_cube.remove_coord('month_number')
+                    monthly_cube.remove_coord('year')
+                    mon_cubes.append(monthly_cube)
+            # Save monthly data
+            if 'Stderr' not in var:
+                yearly_cube = concatenate(mon_cubes)
+                glob_attrs['mip'] = vals['mip'][1]
+                save_variable(yearly_cube,
+                              var,
+                              out_dir,
+                              glob_attrs,
+                              unlimited_dimensions=['time'])
+                mon_cubes.clear()

esmvaltool/recipes/examples/recipe_check_obs.yml

@@ -311,12 +311,13 @@ diagnostics:
   ESACCI-SST:
     description: ESACCI-SST check
     variables:
-      ts:
-      tsStderr:
+      tos:
+      tosStderr:
     additional_datasets:
-      - {dataset: ESACCI-SST, project: OBS, mip: Amon, tier: 2,
-         type: sat, version: 2.2,
-         start_year: 1982, end_year: 2019}
+      - {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'}
     scripts: null