Adding I/O for Analysis of Significant Wave Height for 3DRTMA

[GangZhao-NOAA]

Significant Wave Height (hereafter as SWH) is one of the standard products provided by the operational (2D)RTMA. To continuously provide the same products in 3DRTMA, the next-generation RTMA, some efforts in GSI code need to be made in order to analyze the SWH in 3DVar of GSI.

The kernel subroutines to assimilate SWH in GSI (such as stphowv.f90, setuphowv.f90, inthowv.f90, gsi_howvOper.f90 and m_howvNode.f90) already had been added for (2D)RTMA years ago by Manuel Pondeca, so for this issue, the code work mainly focus on adding the I/O of SWH in background and analysis fields for 3DRTMA (esp. RRFS-based 3DRTMA), and some necessary modifications in background error, options, variables related to analysis of SWH, etc.

Note:
For RRFS-based 3DRTMA, the SWH data are interpolated to Extended Schmidt Gnomonic (ESG) grid for GSI analysis as same as other FV3-LAM model variables; for HRRR-based 3DRTMA, the SWH data are defined on Lambert Conformal grid as same as other HRRR model variables.

[GangZhao-NOAA]

This issue #601 is linked to working branch "feature/3drtma_howv" in my personal fork of NOAA-EMC/GSI repo.

[GangZhao-NOAA]

• Finished the code work (in my personal fork of EMC/GSI repository). The modified GSI code is in the branch "feature/3drtma_howv".

• The modified GSI code passed the regression tests (all 9 tasks) on Hera and WCOSS2 (Cactus).

  • Brief results from ctest (regression test) with the modified code (on WCOSS2 - Cactus):

[gang.zhao@clogin07:build] (feature/3drtma_howv)$ ctest -N
Test project /lfs/h2/emc/da/save/gang.zhao/WorkDir/WaveHgt/develop/build
Test #1: global_3dvar
Test #2: global_4dvar
Test #3: global_4denvar
Test #4: hwrf_nmm_d2
Test #5: hwrf_nmm_d3
Test #6: rtma
Test #7: rrfs_3denvar_glbens
Test #8: netcdf_fv3_regional
Test #9: global_enkf

Total Tests: 9
Test #1: global_3dvar
[gang.zhao@clogin04:build] (feature/3drtma_howv)$ ctest -R global_3dvar
Test project /lfs/h2/emc/da/save/gang.zhao/WorkDir/WaveHgt/develop/build
Start 1: global_3dvar
1/1 Test #1: global_3dvar ..................... Passed 1631.12 sec

100% tests passed, 0 tests failed out of 1

Total Test time (real) = 1631.14 sec

Test #2: global_4dvar
[gang.zhao@clogin09:build] (feature/3drtma_howv)$ ctest -R global_4dvar
Test project /lfs/h2/emc/da/save/gang.zhao/WorkDir/WaveHgt/develop/build
Start 2: global_4dvar
1/1 Test #2: global_4dvar ..................... Passed 2462.19 sec

100% tests passed, 0 tests failed out of 1

Total Test time (real) = 2462.23 sec

Test #3: global_4denvar
[gang.zhao@clogin04:build] (feature/3drtma_howv)$ ctest -R global_4denvar
Test project /lfs/h2/emc/da/save/gang.zhao/WorkDir/WaveHgt/develop/build
Start 3: global_4denvar
1/1 Test #3: global_4denvar ................... Passed 1922.43 sec

100% tests passed, 0 tests failed out of 1

Total Test time (real) = 1922.46 sec

Test #4: hwrf_nmm_d2
[gang.zhao@clogin09:build] (feature/3drtma_howv)$ ctest -R hwrf_nmm_d2
Test project /lfs/h2/emc/da/save/gang.zhao/WorkDir/WaveHgt/develop/build
Start 4: hwrf_nmm_d2
1/1 Test #4: hwrf_nmm_d2 ...................... Passed 1214.10 sec

100% tests passed, 0 tests failed out of 1

Total Test time (real) = 1214.20 sec

Test #5: hwrf_nmm_d3
[gang.zhao@clogin09:build] (feature/3drtma_howv)$ ctest -R hwrf_nmm_d3
Test project /lfs/h2/emc/da/save/gang.zhao/WorkDir/WaveHgt/develop/build
Start 5: hwrf_nmm_d3
1/1 Test #5: hwrf_nmm_d3 ...................... Passed 736.38 sec

100% tests passed, 0 tests failed out of 1

Total Test time (real) = 736.50 sec

Test #6: rtma
[gang.zhao@clogin05:build] (feature/3drtma_howv)$ ctest -R rtma
Test project /lfs/h2/emc/da/save/gang.zhao/WorkDir/WaveHgt/develop/build
Start 6: rtma
1/1 Test #6: rtma ............................. Passed 1027.01 sec

100% tests passed, 0 tests failed out of 1

Total Test time (real) = 1027.01 sec

Test #7: rrfs_3denvar_glbens
[gang.zhao@clogin06:build] (feature/3drtma_howv)$ ctest -R rrfs_3denvar_glbens
Test project /lfs/h2/emc/da/save/gang.zhao/WorkDir/WaveHgt/develop/build
Start 7: rrfs_3denvar_glbens
1/1 Test #7: rrfs_3denvar_glbens .............. Passed 484.69 sec

100% tests passed, 0 tests failed out of 1

Total Test time (real) = 484.70 sec

Test #8: netcdf_fv3_regional
[gang.zhao@clogin03:build] (feature/3drtma_howv)$ ctest -R netcdf_fv3_regional
Test project /lfs/h2/emc/da/save/gang.zhao/WorkDir/WaveHgt/develop/build
Start 8: netcdf_fv3_regional
1/1 Test #8: netcdf_fv3_regional .............. Passed 483.08 sec

100% tests passed, 0 tests failed out of 1

Total Test time (real) = 483.11 sec

Test #9: global_enkf
[gang.zhao@clogin03:build] (feature/3drtma_howv)$ ctest -R global_enkf
Test project /lfs/h2/emc/da/save/gang.zhao/WorkDir/WaveHgt/develop/build
Start 9: global_enkf
1/1 Test #9: global_enkf ...................... Passed 488.50 sec

100% tests passed, 0 tests failed out of 1

Total Test time (real) = 488.57 sec

• Modified code in GSI:

  1. rapidrefresh_cldsurf_mod.f90: adding a few variables related to the analysis of howv in 3D analysis
  2. gsimod.F90: adding namelist options used for analysis of howv in 3D analysis
  3. m_berror_stats_reg.f90: added some code for the special treatment to the static background error (BE) of howv
  4. read_prepbufr.f90: adding code to decode the observation of howv in prepbufr file when howv is available in firstguess
  5. setuphowv.f90: adding code to use obs of howv when howv is available in firstguess
  6. gsi_rfv3io_mod.f90: adding I/O code to read in howv from firstguess and write out howv into analysis.

• adding the analysis of howv only has very trial influences on the analyses of other variables. Here is the statistics of the differences of other variables (u/v/t/ps/q/t2m/q2m) from the runs of GSI without howv vs. with howv:
  comparing two netcdf files: fcst_fv3lam_hyb_betas/INPUT/fv_core.res.tile1.nc fcst_fv3lam_nodata_noinfo/INPUT/fv_core.res.tile1.nc ...
  Variable Group Count Sum AbsSum Min Max Range Mean StdDev
  u / 602135550 3926.84 25760.8 -0.1026 0.485788 0.588388 6.52152e-06 0.00115817
  v / 620166777 -4891.34 32582.5 -0.835774 0.268402 1.10418 -7.88714e-06 0.00197793
  T / 155987083 178.048 6497.51 -0.0246582 0.0384064 0.0630646 1.14143e-06 0.000218737
  delp / 19559676 -281.532 3008.29 -0.00292969 0.00219727 0.00512695 -1.43935e-05 0.000183727

comparing two netcdf files: fcst_fv3lam_hyb_betas/INPUT/fv_tracer.res.tile1.nc fcst_fv3lam_nodata_noinfo/INPUT/fv_tracer.res.tile1.nc ...
Variable Group Count Sum AbsSum Min Max Range Mean StdDev
sphum / 430707614 0.594287 2.77816 -2.6139e-05 3.1759e-05 5.7898e-05 1.37979e-09 8.03072e-08

comparing two netcdf files: fcst_fv3lam_hyb_betas/INPUT/sfc_data.nc fcst_fv3lam_nodata_noinfo/INPUT/sfc_data.nc ...
Variable Group Count Sum AbsSum Min Max Range Mean StdDev
t2m / 10665000 43.3899 135.095 -0.00152825 0.00686629 0.00839454 4.06844e-06 5.02866e-05
q2m / 10665000 0.0192553 0.124707 -3.1476e-06 1.77554e-05 2.0903e-05 1.80547e-09 5.89657e-08

It could be seen that the differences are trivial and ignorable.

• Brief summary on the results from a testing case: 2023-07-12_14:00:00 UTC for North-American domain
  1. Here is the analysis increment of Significant Wave Height (aka howv hereafter): pure 3dvar, static background error of howv is 0.42 meters, and the de-correlation length scale is 170km.
     
  2. The following figure shows the distribution of howv in the analysis (used obs is in green, rejected in red). Obviously the location of used obs of howv match the area of non-zero analysis increments of howv.
     
  3. The following figure is the analysis increment of howv with hybrid envar analysis (using gdas ensemble 80 members and the ensemble weight is 84%), and the static BE of howv is tuned/inflated. The analysis increments are very similar to the results from pure 3dvar run (see the first figure)
     
  4. The last figure shows the analysis increments of howv with hybrid envar analysis (using gdas ensemble 80 members and the ensemble weight is 84%), but the static BE of howv is NOT tuned. It can be observed that the analysis increments is less than the results from the hybrid run with tuning the static BE of howv. That is because the weight of static BE (16%) reduced the background error of howv (ensemble of howv is not available yet), so the impact of obs is decreased.
     

The code is ready for merging to develop branch of EMC/GSI repository. A pull-request (PR #614) was just created.

[TingLei-NOAA]

@GangZhao-NOAA An important issue approached under this issue title is how the hybrid analysis (including pure ens3dvar )is done for howv when howv ensembles are not available. Could you describe the method and considerations here?

[GangZhao-NOAA]

@TingLei-NOAA
As I replied to your another comment (see #614 (comment)),
even no ensemble of howv, GSI still can run the hybrid analysis. For the B of howv, since there is no contribution from ensemble of howv, so the B of howv is the static B of howv multiplied by the weight of static BE. So in hybrid analysis, the analysis of HOWV is actually the pure variational analysis, with a reduced BE of howv (reduced by the weight).
If to make the analysis of HOWV in hybrid is similar to the analysis of howv in pure 3dvar, we could tune (actually increase) the static BE of howv according the weight of static BE used in hybrid analysis.
Thanks,