Comments (2)
This can be a source of confusion for derived
variables, and must be treated with caution. If we do not use cmor names in the derivation, we might face some complication when looking for variables within the file. Conversely, it is clumsy to creation expression based on cmor variables.
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I have just realized that this can be easily done using the derived
keys.
tas:
derived: '2t'
varnname: '2m Temperature'
filetype: atm2d
Some rearrangement of the file loading is currently being developed in #59, but this can be easily exploited!
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Related Issues (20)
- ECmean4 not running with python 3.11 HOT 3
- Including sea ice area in global mean HOT 2
- Refactor of global mean HOT 5
- Correct the parsing of the global_mean() and performance_indices()
- Interpolation with CDO to replace xESMF HOT 3
- Revisiting the file-handling functions HOT 1
- Revisiting the `component` and its files in the interface YAML files HOT 1
- Coherence and alignment of `global_mean` and `performance_indices` HOT 1
- global mean with no standard deviation does not show up in the figure HOT 1
- Coverage is not considering the call to `subprocess.run()`
- variables that cannot be processed HOT 1
- Installing from PyPI causes dependency errors HOT 8
- oceanic mask HOT 1
- Midlat regions are misleading
- Global Mean for `tas`: CRU data does not include Antarctica
- Evaporation has a flipped sign in EC-Earth4 data
- Coverage is changing results and taking foreever
- Matplotlib 3.8.0 and seaborn 1.12.2 does not plot annotations in heatmap HOT 1
- Slow down of the `performance_indices` due to `xesmf>=0.8` version HOT 1
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