`recipe_perfmetrics_land_CMIP5` fails in `multi_model_statistics` step

[schlunma]

Describe the bug

recipe_perfmetrics_land_CMIP5 currently fails in the mulit_model_statistics step:

Traceback (most recent call last):
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/esmvalcore/_main.py", line 499, in run
    fire.Fire(ESMValTool())
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/fire/core.py", line 141, in Fire
    component_trace = _Fire(component, args, parsed_flag_args, context, name)
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/fire/core.py", line 466, in _Fire
    component, remaining_args = _CallAndUpdateTrace(
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/fire/core.py", line 681, in _CallAndUpdateTrace
    component = fn(*varargs, **kwargs)
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/esmvalcore/_main.py", line 443, in run
    process_recipe(recipe_file=recipe, config_user=cfg)
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/esmvalcore/_main.py", line 124, in process_recipe
    recipe.run()
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/esmvalcore/_recipe.py", line 1882, in run
    self.tasks.run(max_parallel_tasks=self._cfg['max_parallel_tasks'])
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/esmvalcore/_task.py", line 723, in run
    self._run_sequential()
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/esmvalcore/_task.py", line 734, in _run_sequential
    task.run()
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/esmvalcore/_task.py", line 259, in run
    input_files.extend(task.run())
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/esmvalcore/_task.py", line 259, in run
    input_files.extend(task.run())
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/esmvalcore/_task.py", line 263, in run
    self.output_files = self._run(input_files)
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/esmvalcore/preprocessor/__init__.py", line 592, in _run
    self.products = _apply_multimodel(self.products, step,
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/esmvalcore/preprocessor/__init__.py", line 506, in _apply_multimodel
    result = preprocess(products - exclude, step, **settings)
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/esmvalcore/preprocessor/__init__.py", line 342, in preprocess
    result.append(_run_preproc_function(function, items, settings,
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/esmvalcore/preprocessor/__init__.py", line 302, in _run_preproc_function
    return function(items, **kwargs)
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/esmvalcore/preprocessor/_multimodel.py", line 505, in multi_model_statistics
    group_statistics = _multiproduct_statistics(
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/esmvalcore/preprocessor/_multimodel.py", line 407, in _multiproduct_statistics
    statistics_cubes = _multicube_statistics(cubes=cubes,
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/esmvalcore/preprocessor/_multimodel.py", line 388, in _multicube_statistics
    result_cube = _compute_eager(aligned_cubes,
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/esmvalcore/preprocessor/_multimodel.py", line 324, in _compute_eager
    combined_slice = _combine(single_model_slices)
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/esmvalcore/preprocessor/_multimodel.py", line 293, in _combine
    merged_cube = cubes.merge_cube()
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/iris/cube.py", line 402, in merge_cube
    proto_cube.register(cube, error_on_mismatch=True)
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/iris/_merge.py", line 1361, in register
    match = coord_payload.match_signature(
  File "/work/bd0854/b309192/soft/miniconda3/envs/core_rc4/lib/python3.10/site-packages/iris/_merge.py", line 284, in match_signature
    raise iris.exceptions.MergeError(msgs)
iris.exceptions.MergeError: failed to merge into a single cube.
  Coordinates in cube.dim_coords differ: longitude.

Please attach

• The main_log_debug.txt file, this can also be found in the run directory in the output directory: https://esmvaltool.dkrz.de/shared/esmvaltool/v2.5.0-test-rc4/recipe_perfmetrics_land_CMIP5_20220303_185908/run/main_log_debug.txt

[valeriupredoi]

it's always good to assign peeps, Manu, even if they won't send you Xmas cards anymore 😁

[Peter9192]

So apparently the longitude coordinates of some datasets differ. From the debug log it's not clear which one is causing the problem... I think multi-model stats is behaving as expected and the problem is with the data.

I suppose this message could be more helpful though:

2022-03-03 20:36:30,252 UTC [31230] ERROR   esmvalcore.preprocessor:327 Failed to run preprocessor function 'multi_model_statistics' on the data
PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_HadGEM2-CC_Omon_historical_r1i1p1_fgco2_1980-1999.nc,
 PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_GFDL-ESM2M_Omon_historical_r1i1p1_fgco2_1980-1999.nc,
 PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_MIROC-ESM-CHEM_Omon_historical_r1i1p1_fgco2_1980-1999.nc,
 PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_CanESM2_Omon_historical_r1i1p1_fgco2_1980-1999.nc]
(and 16 further argument(s) not shown here; refer to the debug log for a full list)

NB: this is the debug log

[schlunma]

The full message is one line above the error:

2022-03-03 20:36:29,683 UTC [31230] DEBUG   esmvalcore.preprocessor:297 Running preprocessor function 'multi_model_statistics' on the data
{PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_CNRM-CM5_Omon_historical_r1i1p1_fgco2_1980-1999.nc,
 PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_CMCC-CESM_Omon_historical_r1i1p1_fgco2_1980-1999.nc,
 PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_GFDL-ESM2G_Omon_historical_r1i1p1_fgco2_1980-1999.nc,
 PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_CanESM2_Omon_historical_r1i1p1_fgco2_1980-1999.nc,
 PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_CESM1-BGC_Omon_historical_r1i1p1_fgco2_1980-1999.nc,
 PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_MIROC-ESM_Omon_historical_r1i1p1_fgco2_1980-1999.nc,
 PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_MPI-ESM-MR_Omon_historical_r1i1p1_fgco2_1980-1999.nc,
 PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_GFDL-ESM2M_Omon_historical_r1i1p1_fgco2_1980-1999.nc,
 PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_GISS-E2-H-CC_Omon_historical_r1i1p1_fgco2_1980-1999.nc,
 PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_MIROC-ESM-CHEM_Omon_historical_r1i1p1_fgco2_1980-1999.nc,
 PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_HadGEM2-CC_Omon_historical_r1i1p1_fgco2_1980-1999.nc,
 PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_NorESM1-ME_Omon_historical_r1i1p1_fgco2_1980-1999.nc,
 PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_MPI-ESM-LR_Omon_historical_r1i1p1_fgco2_1980-1999.nc,
 PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_MRI-ESM1_Omon_historical_r1i1p1_fgco2_1980-1999.nc,
 PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_IPSL-CM5A-LR_Omon_historical_r1i1p1_fgco2_1980-1999.nc,
 PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_GISS-E2-R-CC_Omon_historical_r1i1p1_fgco2_1980-1999.nc,
 PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_IPSL-CM5B-LR_Omon_historical_r1i1p1_fgco2_1980-1999.nc,
 PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_IPSL-CM5A-MR_Omon_historical_r1i1p1_fgco2_1980-1999.nc,
 PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_HadGEM2-ES_Omon_historical_r1i1p1_fgco2_1980-1999.nc,
 PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_inmcm4_Omon_historical_r1i1p1_fgco2_1980-1999.nc}
with function argument(s)
span = 'overlap',
statistics = ['mean', 'median'],
output_products = defaultdict(<class 'dict'>,
            {'': {'mean': PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_MultiModelMean_historical_Omon_fgco2_1980-1999.nc,
                  'median': PreprocessorFile: /mnt/lustre02/work/bd0854/b309192/recipe_testing_v2p5_rc4/esmvaltool_output/recipe_perfmetrics_land_CMIP5_20220303_185908/preproc/fgco2/fgco2/CMIP5_MultiModelMedian_historical_Omon_fgco2_1980-1999.nc}})

Since the datasets are regridded before calculating the multi-model statistics, I guess it's rather an issue in regrid, not in an input file.

Unfortunately it's not trivial to find out which dataset is causing the problem, since the error message of iris is not really helpful in that case...

[valeriupredoi]

I think a restricted run with only those datasets listed and only the preprocessor that is assigned to that task, and save intermediary cubes would do the trick, I can try it on JASMIN

[valeriupredoi]

OK I reproduced the bugger with this:

---
documentation:
  title: Performance metrics for essential climate variables in CMIP5

  description: |
    Recipe for plotting the performance metrics for the CMIP5 datasets,
    including the standard ECVs as in Gleckler et al., and some additional
    variables (like ozone, sea-ice, aerosol...)

  authors:
    - frank_franziska
    - righi_mattia
    - eyring_veronika

  maintainer:
    - righi_mattia

  references:
    - gleckler08jgr

  projects:
    - esmval
    - embrace

preprocessors:
  ppNOLEV:
    regrid:
      target_grid: 1x1
      scheme: linear
    mask_fillvalues:
      threshold_fraction: 0.95
    multi_model_statistics:
      span: overlap
      statistics: [mean, median]

diagnostics:
  sm:
    description: Soil moisture
    themes:
      - phys
    realms:
      - land
    variables:
      fgco2:
        short_name: fgco2
        preprocessor: ppNOLEV
        mip: Omon
        project: CMIP5
        exp: historical
        ensemble: r1i1p1
        start_year: 1998
        end_year: 1999
    additional_datasets:
      - {dataset: CanESM2}
      - {dataset: CESM1-BGC}
      - {dataset: CMCC-CESM}
      - {dataset: CNRM-CM5}
      - {dataset: GFDL-ESM2G}
      - {dataset: GFDL-ESM2M}
      - {dataset: GISS-E2-H-CC}
      - {dataset: GISS-E2-R-CC}
      - {dataset: HadGEM2-CC}
      - {dataset: HadGEM2-ES}
      - {dataset: inmcm4}
      - {dataset: IPSL-CM5A-LR}
      - {dataset: IPSL-CM5A-MR}
      - {dataset: IPSL-CM5B-LR}
      - {dataset: MIROC-ESM}
      - {dataset: MIROC-ESM-CHEM}
      - {dataset: MPI-ESM-LR}
      - {dataset: MPI-ESM-MR}
      - {dataset: MRI-ESM1}
      - {dataset: NorESM1-ME}
    scripts: null

I am trying now to save the intermediary files, see which one is causing it, but I suspect I am going to run out of disk quota on JASMIN - if I do, at least you have a simplified small-scale recipe that can help find out which one is the party pooper

[valeriupredoi]

OK found it! Bl**dy Russkies:

the 07_regrid.nc regridded cube from CMIP5_inmcm4_Omon_historical_r1i1p1_fgco2_1998-1999

looks like this

surface_downward_mass_flux_of_carbon_dioxide_expressed_as_carbon / (kg m-2 s-1) (time: 24; -- : 180; -- : 360)
    Dimension coordinates:
        time                                                                         x        -         -
    Cell methods:
        mean                                                                    time (1 month)
        where sea                                                               area
    Attributes:
        Conventions                                                             CF-1.7
        associated_files                                                        baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_fx_inmcm4_historical_r0i0p0.nc...
        branch_time                                                             0.0
        cmor_version                                                            2.0.0
        contact                                                                 Evgeny Volodin, volodin@inm.ras.ru,INM RAS, Gubkina 8, Moscow, 119333 ...
        experiment                                                              Historical
        experiment_id                                                           historical
        forcing                                                                 N/A
        frequency                                                               mon
        initialization_method                                                   1
        institute_id                                                            INM
        institution                                                             INM (Institute for Numerical Mathematics,  Moscow, Russia)
        model_id                                                                inmcm4
        modeling_realm                                                          ocnBgchem
        original_name                                                           fgco2
        parent_experiment                                                       pre-industrial control
        parent_experiment_id                                                    piControl
        physics_version                                                         1
        product                                                                 output
        project_id                                                              CMIP5
        realization                                                             1
        references                                                              Volodin, Diansky, Gusev 2010. Climate model INMCM4.0. Izvestia RAS. Atmospheric...
        source                                                                  inmcm4 (2009)
        table_id                                                                Table Omon (12 May 2010) f2afe576fb73a3a11aaa3cc8f2e62cf3
        title                                                                   inmcm4 model output prepared for CMIP5 Historical

and it lacks any lon or lat naming:

printing its cube.coords() loks like this:

[DimCoord(array([54035.5, 54065. , 54094.5, 54125. , 54155.5, 54186. , 54216.5,
       54247.5, 54278. , 54308.5, 54339. , 54369.5, 54400.5, 54430. ,
       54459.5, 54490. , 54520.5, 54551. , 54581.5, 54612.5, 54643. ,
       54673.5, 54704. , 54734.5]), bounds=array([[54020., 54051.],
       [54051., 54079.],
       [54079., 54110.],
       [54110., 54140.],
       [54140., 54171.],
       [54171., 54201.],
       [54201., 54232.],
       [54232., 54263.],
       [54263., 54293.],
       [54293., 54324.],
       [54324., 54354.],
       [54354., 54385.],
       [54385., 54416.],
       [54416., 54444.],
       [54444., 54475.],
       [54475., 54505.],
       [54505., 54536.],
       [54536., 54566.],
       [54566., 54597.],
       [54597., 54628.],
       [54628., 54658.],
       [54658., 54689.],
       [54689., 54719.],
       [54719., 54750.]]), standard_name='time', units=Unit('days since 1850-1-1 00:00:00', calendar='365_day'), long_name='time', var_name='time')]

-> time only!

whereas all others are nicely T-X-Y:

surface_downward_mass_flux_of_carbon_dioxide_expressed_as_carbon / (kg m-2 s-1) (time: 24; latitude: 180; longitude: 360)
    Dimension coordinates:
        time                                                                         x             -               -
        latitude                                                                     -             x               -
        longitude                                                                    -             -               x
    Cell methods:
        mean                                                                    time (30 minutes)
        where sea                                                               area
    Attributes:
        Conventions                                                             CF-1.7
        associated_files                                                        baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_ocnBgchem_fx_IPSL-CM5A-MR_historical_r0i0p0.nc...
        branch_time                                                             1850.0
        cmor_version                                                            2.7.1
        contact                                                                 ipsl-cmip5 _at_ ipsl.jussieu.fr Data manager : Sebastien Denvil
        experiment                                                              historical
        experiment_id                                                           historical
        forcing                                                                 Nat,Ant,GHG,SA,Oz,LU,SS,Ds,BC,MD,OC,AA
        frequency                                                               mon
        initialization_method                                                   1
        institute_id                                                            IPSL
        institution                                                             IPSL (Institut Pierre Simon Laplace, Paris, France)
        model_id                                                                IPSL-CM5A-MR
        modeling_realm                                                          ocnBgchem
        original_name                                                           Cflx
        parent_experiment                                                       pre-industrial control
        parent_experiment_id                                                    piControl
        parent_experiment_rip                                                   r1i1p1
        physics_version                                                         1
        product                                                                 output
        project_id                                                              CMIP5
        realization                                                             1
        references                                                              Model documentation and further reference available here : http://icmc...
        source                                                                  IPSL-CM5A-MR (2010) : atmos : LMDZ4 (LMDZ4_v5, 144x143x39); ocean : ORCA2...
        table_id                                                                Table Omon (31 January 2011) d2d6beec2b8fea5bbed33920a6e08bbe
        title                                                                   IPSL-CM5A-MR model output prepared for CMIP5 historical

why this is happening? Something is happening after step 6 of the preproc (add_fx_variables) namely in regrid, since before regrid the Russ cube looks like this:

surface_downward_mass_flux_of_carbon_dioxide_expressed_as_carbon / (kg m-2 s-1) (time: 24; grid_latitude: 340; grid_longitude: 360)
    Dimension coordinates:
        time                                                                         x                  -                    -
        grid_latitude                                                                -                  x                    -
        grid_longitude                                                               -                  -
    Auxiliary coordinates:
        latitude                                                                     -                  x                    x
        longitude                                                                    -                  x                    x
    Cell methods:
        mean                                                                    time (1 month)
        where sea
...

whereas the others look like:

surface_downward_mass_flux_of_carbon_dioxide_expressed_as_carbon / (kg m-2 s-1) (time: 24; cell index along second dimension: 149; cell index along first dimension: 182)
    Dimension coordinates:
        time                                                                         x                                      -                                      -
        cell index along second dimension                                            -                                      x                                      -
        cell index along first dimension                                             -                                      -                                      x
    Auxiliary coordinates:
        latitude                                                                     -                                      x                                      x
        longitude                                                                    - 
    Cell methods:
        mean                                                                    time (1 month)
        where sea                                                               area

...

I am not a specialist of ocean/land data so I am not sure what the heck's up in here, but at least this can be a good clue for you or @zklaus to understand what's the hap. Incidentally, what's where sea? That's not a cell method in me books?

[zklaus]

Re where sea, update your book: http://cfconventions.org/Data/cf-conventions/cf-conventions-1.9/cf-conventions.html#statistics-applying-portions

[valeriupredoi]

Haha, cheers, Klaus, my book's ye olde. Note that iris is complaining about that too, so its book is ye olde too. Can you make any sense of the inmcm4 data tho? Dr Valeriu Predoi. Computational scientist NCAS-CMS University of Reading Department of Meteorology Reading RG6 6BB United Kingdom

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On Mon, 14 Mar 2022, 17:56 Klaus Zimmermann, ***@***.***> wrote: Re where sea, update your book: http://cfconventions.org/Data/cf-conventions/cf-conventions-1.9/cf-conventions.html#statistics-applying-portions — Reply to this email directly, view it on GitHub <#2594 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AG5EFI5B23UFFPYB4UEORI3U754VBANCNFSM5QQHEPYA> . Triage notifications on the go with GitHub Mobile for iOS <https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675> or Android <https://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub>. You are receiving this because you commented.Message ID: ***@***.***>