generate_wombat_ic.py: Add support for WOMBATmid initial conditions#125
generate_wombat_ic.py: Add support for WOMBATmid initial conditions#125dougiesquire merged 2 commits intomainfrom
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Actually, maybe hold off on reviewing this @anton-seaice. We'd like to download the annual WOA23 data and use that to fill in values at depth |
Ok @anton-seaice I think this is ready for a look. I've updated the PR description since opening. |
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The data here appears to be kept on it's native grid(s)? And then is there a second step to regrid onto the OM3 grid ? Should there be a description in the global attributes of what the file is ? It looks like there are some variable attributes referring to things which don't exist: |
Nah, MOM can read the native data directly. So we'll only have one file for all resolutions
Sure, I'll add it
Yeah ok, I'll remove these and fix up the easy cf-compliance issues |
Oh cool - should there be some more information on what the grids are then ? (is it confusing having multiple lats & lons for different grids in the same file ?) |
Well it's not really intended to be a file that people use. I already add the |
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With the most recent change: lite mid |
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I think this is ready for you again @anton-seaice. Unless you want me to add something more in response to this:
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Thanks Dougie
Approving based on the agreement in ACCESS-NRI/GFDL-generic-tracers#111 and having checked that output has metadata and the code looks well structured and clear.
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Thanks @anton-seaice. I'm going to squash the last N-1 commits so may require another approval |
This PR replaces
generate_wombatlite_ic.pywith a unifiedgenerate_wombat_ic.pythat supports both WOMBATlite and WOMBATmid via a--wombat-version=<lite|mid>argument.The script now generates all required initial conditions, whereas previously we initialised some variables from other files. Initial conditions are constructed as follows:
no3: From WOA23. Use Jan average with depths below 800m filled in from annual datao2: From WOA23. Use Jan average with depths below 1500m filled in from annual datasil: From WOA23. Use Jan average with depths below 800m filled in from annual datan2o: Calculated from WOA23 T and S. Use Jan average with depths below 1500m filled in from annual data.alk: From GLODAPv2 mapped fieldsdic: From GLODAPv2 mapped fieldsfe: From Huang 2022 (zenodo.org/records/6994318)Missing ocean regions are in-filled using the harmonic interpolation routine I used for SW chl. All other variables are initialised as constants on the WOA23 no3 1deg grid or derived from the above variables. Discussion of which datasets/values to use, including summary plots, can be found in this issue.
Example output can be found here:
This will change answers for WOMBAT tracers in OM3 since it changes the initial conditions. I've checked that OM3 runs with the new initial conditions.
This also changes the answers produced by the
chlorophyll/chl_climatology_and_fill.py. While refactoring the shared code, I noticed that I was incorrectly assuming a tripolar grid when doing the in-filling of these data. The difference is unlikely to have any noticeable impact, but configurations will need to be updated.Still to doNow done@joshuatorrance is currently helping me get some of the required data into
/g/data/av17. For now the script uses my own downloads, but it will need to be updated once the data is in/g/data/av17: