Update a diagnostic to new Iris version

[katjaweigel]

Description

Recipe recipe_flato13ipcc.yml crashes due to a new IRIS version:
2021-10-28 11:31:58,651 [5412] INFO esmvaltool.diag_scripts.shared._base,550 Creating /work/bd1083/b380216/output/recipe_flato13ipcc_20211028_100738/plots/fig09-14/fig09-14
Traceback (most recent call last):
File "/mnt/lustre02/work/bd1083/b380216/CORE202102/ESMValTool/esmvaltool/diag_scripts/ipcc_ar5/ch09_fig09_14.py", line 407, in
main(cfg)
File "/mnt/lustre02/work/bd1083/b380216/CORE202102/ESMValTool/esmvaltool/diag_scripts/ipcc_ar5/ch09_fig09_14.py", line 396, in main
plot_path = produce_plots(config, data)
File "/mnt/lustre02/work/bd1083/b380216/CORE202102/ESMValTool/esmvaltool/diag_scripts/ipcc_ar5/ch09_fig09_14.py", line 351, in produce_plots
lines, labels = plot_zonal_mean_errors_ensemble(
File "/mnt/lustre02/work/bd1083/b380216/CORE202102/ESMValTool/esmvaltool/diag_scripts/ipcc_ar5/ch09_fig09_14.py", line 259, in plot_zonal_mean_errors_ensemble
cube_list = multi_model_merge(zonal_mean_errors)
File "/mnt/lustre02/work/bd1083/b380216/CORE202102/ESMValTool/esmvaltool/diag_scripts/ipcc_ar5/ch09_fig09_14.py", line 177, in multi_model_merge
equalise_attributes(cube_list)
File "/work/bd0854/b380216/anaconda3/envs/esmvaltool202106/lib/python3.9/site-packages/iris/experimental/equalise_cubes.py", line 30, in equalise_attributes
raise Exception(emsg)
Exception: The function "iris.experimental.equalise_cubes.equalise_attributes" has been moved.
Please replace "iris.experimental.equalise_cubes.equalise_attributes()" with "iris.util.equalise_attributes()".

It should be easy to fix with changing:
from iris.experimental.equalise_cubes import equalise_attributes
to
from iris.util import equalise_attributes
This new line is already used in ESMValCore/esmvalcore/preprocessor/_multimodel.py

I make this a draft first because I want to check if it runs (it did not the first time but that could have been caused by other issues.)

• Closes #issue_number
• Link to documentation:

---

Checklist

It is the responsibility of the author to make sure the pull request is ready to review. The icons indicate whether the item will be subject to the 🛠 Technical or 🧪 Scientific review.

• 🛠 This pull request has a descriptive title
• 🛠 Code is written according to the code quality guidelines
• 🛠 Documentation is available
• 🛠 Tests run successfully
• 🛠 The list of authors is up to date
• 🛠 Any changed dependencies have been added or removed correctly
• 🛠 All checks below this pull request were successful

New or updated recipe/diagnostic

• 🧪 Recipe runs successfully
• 🧪 Recipe is well documented
• 🧪 Figure(s) and data look as expected from literature
• 🛠 Provenance information has been added

---

To help with the number of pull requests:

• 🙏 We kindly ask you to review two other open pull requests in this repository

[zklaus]

Nice and clean.

[katjaweigel]

Sorry, that I'm to slow with the tests, but recipe_flato13ipcc.yml still doesn't run. That is probably not caused by that line but related: In addition to equalise_attributes the diagnostic removes several possible the auxiliary coordinates for time to allow for the multi model mean with:

equalise_attributes(cube_list)
for cube in cube_list:
    cube.cell_methods = tuple()
    for coord in ['day_of_month', 'month_number', 'year']:
        try:
            cube.remove_coord(coord)
        except CoordinateNotFoundError:
            pass

Now it looks as there is a new one in one of the data sets, which is not included, yet. I get the error:

iris.exceptions.MergeError: failed to merge into a single cube.
Coordinates in cube.aux_coords (scalar) differ: time.

(I also had to remove several data sets from the recipe to come to that point because I didn't want to check the new download tool.)
I try to find the aux_coord name or data set which causes that and will open a new PR if removing an additional aux_coord helps.
The best is probably to use (or mimic) the complete function used for a similar purpose in the preprocessor (esmvalcore/preprocessor/_multimodel.py)?

def _combine(cubes):
"""Merge iris cubes into a single big cube with new dimension.

This assumes that all input cubes have the same shape.
"""
equalise_attributes(cubes)  # in-place

for i, cube in enumerate(cubes):
    concat_dim = iris.coords.AuxCoord(i, var_name=CONCAT_DIM)

    cube.add_aux_coord(concat_dim)

    # Clear some metadata that can cause merge to fail
    # https://scitools-iris.readthedocs.io/en/stable/userguide/
    #    merge_and_concat.html#common-issues-with-merge-and-concatenate

    remove_fx_variables(cube)
    cube.cell_methods = None

    for coord in cube.coords():
        coord.long_name = None
        coord.attributes = None

cubes = iris.cube.CubeList(cubes)

merged_cube = cubes.merge_cube()

return merged_cube