Adding Mixed Layer Depth Diagnostic #87
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- Mixed Layer depth diagnostic code added for analyzing model output - Takes MLD_003, MLD_EN1, MLD_EN2, OR MLD_EN3 as inputs. - Creates map of input (either min or max of monthly means) - Compares to similar field from obs (usually Argo based).
jkrasting
requested changes
Oct 25, 2021
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@breichl - Looks really good. Mostly a few minor nits.
Major comments:
- Please apply the black code formatter to your .py files
- Consider whether or not using xESMF for regridding would work better for this diagnostic
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| obs_lat = np.copy(ds_obs["Lat"]) | ||
| obs_lon = np.copy(ds_obs["Lon"]) |
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Copying in general increases the memory footprint. You can access the underlying NumPy arrays by using the .values method, e.g.
obs_lat = ds_obs["Lat"].values
| # Gridding obs data to common grid. While obs data is already on the common grid, | ||
| # it may need shuffled if crossing periodic longitude boundary. This is an easy | ||
| # way to ensure that happens correctly. | ||
| obs = griddata((obs_lat.flatten(),obs_lon.flatten()), |
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In general, there is a lot of code here to implement regridding functionality. I wonder if using xESMF would be more streamlined?
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I agree xesmf should be used instead of griddata, there is a function in om4common to regrid data
raphaeldussin
requested changes
Oct 27, 2021
| # Gridding obs data to common grid. While obs data is already on the common grid, | ||
| # it may need shuffled if crossing periodic longitude boundary. This is an easy | ||
| # way to ensure that happens correctly. | ||
| obs = griddata((obs_lat.flatten(),obs_lon.flatten()), |
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I agree xesmf should be used instead of griddata, there is a function in om4common to regrid data
added 6 commits
October 27, 2021 09:48
- CLim -> cbar_lim - Dim -> dim
…o user/bgr/MLD_diag
|
This PR is replaced by #111 |
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Potential Issues:
Command to test:
om4labs mld --grid global --method max --mldvar MLD_EN1 -s /archive/bgr/FMS2019.01.03_mom6_20201020/OM4p25_JRA55do1.5_ePBLRL19_BBL01_VS_JHLtol/gfdl.ncrc4-intel18-prod/pp/ocean_monthly/ocean_monthly.static.nc /archive/bgr/FMS2019.01.03_mom6_20201020/OM4p25_JRA55do1.5_ePBLRL19_BBL01_VS_JHLtol/gfdl.ncrc4-intel18-prod/pp/ocean_monthly/ts/monthly/5yr/ocean_monthly.199801-200212.MLD_EN1.nc /archive/bgr/FMS2019.01.03_mom6_20201020/OM4p25_JRA55do1.5_ePBLRL19_BBL01_VS_JHLtol/gfdl.ncrc4-intel18-prod/pp/ocean_monthly/ts/monthly/5yr/ocean_monthly.200301-200712.MLD_EN1.nc /archive/bgr/FMS2019.01.03_mom6_20201020/OM4p25_JRA55do1.5_ePBLRL19_BBL01_VS_JHLtol/gfdl.ncrc4-intel18-prod/pp/ocean_monthly/ts/monthly/5yr/ocean_monthly.200801-201212.MLD_EN1.nc