Add SNOCVR snow depth python api code to GDASApp

[YoulongXia-NOAA]

This PR is mainly to add snocvr bufr dump snow depth data using python API to replace missing WGOSLID with local station ID to support Land DA task. The snocvr snow depth is new operation product and it did not use before. The dataset includes snow depth from several European countries and US abd Canada (mainly comes from MADIS).

[nicholasesposito]

Just one comment to change 2023 -> 2024.
I asked about snow depth being mm but that's what the user wants, so this is fine with me.
I also asked about units in the argo file being "below" the surface, and got confirmation that the data is indeed below the surface.
The rest looks good. Approved.

[YoulongXia-NOAA]

Thank you, Nick. Changed as suggested.

[emilyhcliu]

Remove the argo python script update.
The code changes look good

[YoulongXia-NOAA]

The ctest "test_gdasapp_setup_cycled_exp" is failing with the automatic github check. However, if I run it on my own Orion machine with my modules, it does not fail. What could be the cause of this? @emilyhcliu @RussTreadon-NOAA

These are the modules I use:

module use /work/noaa/da/eliu/JEDI-GDAS/GDASApp/modulefiles
module load GDAS/orion
#export PATHONPATH=/work/noaa/da/eliu/JEDI-GDAS/GDASapp/ush:$PATHONPATH

I only get a warning when I run from Orion:

test 1666
    Start 1666: test_gdasapp_setup_cycled_exp

1666: Test command: /work2/noaa/da/youlong/gdas-validation/global-workflow/sorc/gdas.cd/test/setup_workflow_exp.sh "/work2/noaa/da/youlong/gdas-validation/global-workflow/sorc/gdas.cd/build" "/work2/noaa/da/youlong/gdas-validation/global-workflow/sorc/gdas.cd"
1666: Test timeout computed to be: 1500
1666: Running global-workflow experiment generation script
1666: ./setup_expt.py:68: UserWarning: User did not provide '--icsdir' to stage initial conditions
1666:   warnings.warn("User did not provide '--icsdir' to stage initial conditions")
1666: EDITED:  /work2/noaa/da/youlong/gdas-validation/global-workflow/sorc/gdas.cd/build/test/testrun/experiments/gdas_test/config.base as per user input.

[YoulongXia-NOAA]

Nick just helped me to do such a test. it passed ctest via ctest -VV -R test_gdasapp_setup_cycled_exp in my build directory.
The following tests passed:
test_gdasapp_setup_cycled_exp

100% tests passed, 0 tests failed out of 1

Total Test time (real) = 8.57 sec

[YoulongXia-NOAA]

@CoryMartin-NOAA, I talked this problem with @emilyhcliu, and lets her see what happened. This issue is not related to my work. I only added one json configure file and one python snowcvr file without changing any other parts. Although I can recreate a feature branch to add these two files, and create a new PR if needed. Could you please give me some instructions and guidance. Thank you

[CoryMartin-NOAA]

@YoulongXia-NOAA my guess is you just needed to merge develop in, let me start the automated tests and see if it passes, if so, I'll approve and merge

[YoulongXia-NOAA]

@thank you, @CoryMartin-NOAA for your help. Next time I will recall to merge develop to my feature and then git push.

[emcbot]

Automated Global-Workflow GDASApp Testing Results:
Machine: orion

Start: Fri Feb  2 08:34:48 CST 2024 on Orion-login-1.HPC.MsState.Edu
---------------------------------------------------
Build:                                 *SUCCESS*
Build: Completed at Fri Feb  2 09:22:47 CST 2024
---------------------------------------------------
Tests:                                 *SUCCESS*
Tests: Completed at Fri Feb  2 09:47:14 CST 2024
Tests: 100% tests passed, 0 tests failed out of 52

[BenjaminRuston]

this looks great,

@CoryMartin-NOAA what do you think about either a fixed yaml or python in a sense demonstration yaml with the set key values from the json are set as defaults?

will re-read but believe that is doable dyt

[CoryMartin-NOAA]

yes that seems reasonable, and just noting that many of these python scripts will probably change as we go to reading directly rather than converting to intermediate IODA files

[BenjaminRuston]

would make the most sense.

think just having demonstration capability is all that is needed, researchers, students, there are going to be cases where people are populating archives there the windowing information, receipt time, characteristics need to be well traced