Station Air-Sea Fluxes demonstration case

Last successful test done with NEMOGCM branch: NEMO/branches/2020/dev_r13648_ASINTER-04_laurent_bulk_ice, revision 13806

Author: Laurent Brodeau, 2020

Objectives

STATION_ASF is a demonstration test-case that mimics a (static) in-situ station (buoy, platform) dedicated to the estimation of surface air-sea fluxes by means of widely-measured (bulk) meteorological surface parameters.

STATION_ASF has been constructed by merging the single column and the standalone surface module configurations of NEMO. In short, it can be defined as "SAS meets C1D". As such, the spatial domain of STATION_ASF is punctual (1D, well actually 3 x 3 as in C1D).

STATION_ASF is therefore a versatile tool, and extremely lightweight in terms of computing requirements, to test the different bulk algorithms and cool-skin/warm-layer parameterization options included in NEMO.

As input STATION_ASF will require the traditional bulk sea surface parameters:

• Bulk sea surface temperature (SST) at z_SST meters below the surface
• Surface current vector
• Sea surface salinity

as well as the usual surface atmospheric state:

• air temperature at z_t meters above the surface
• air humidity at z_t meters above the surface (specific humidity or relative humidity or dew-point temperature)
• wind speed vector at z_u meters above the surface
• Sea level atmospheric pressure (SLP)
• Downwelling solar radiation
• Downwelling longwave radiation

Example of diagnostics with STATION_ASF

(Generated with script ./EXPREF/plot_station_asf_simple.py)

Physical description

Important namelist parameters specific to STATION_ASF

• rn_dept1@namusr_def: depth (m) at which the prescribed SST is taken (i.e. depth of first T-point); important due to impact on warm-layer estimate, the deeper, the more pronounced!

• rn_lat1d,rn_lon1d@namc1d: fixed coordinates of the location of the station (buoy, platform, etc).

• namsbc_blk: to be filled carefully, just as for "C1D", the prescribed surface ATMOSPHERIC state (files) are time series of shape 3x3 in space

• namsbc_sas: to be filled carefully, just as for "C1D", the prescribed surface OCEAN state (files) are time series of shape 3x3 in space

Testing the sanity of the SBCBLK (bulk atmospheric forcing) interface of NEMO

STATION_ASF can be used to perform a sanity test of the SBCBLK interface of NEMO. It will test all the bulk-parameterization algorithms using an idealized forcing that includes a wide range of SSX / surface atmospheric state conditions to detect potential error / inconsistencies. Both a short report and boolean output: passed or failed is provided as an output.

How is the validation test performed ?

Turbulent fluxes and transfer coefficients computed by NEMO with all different bulk parameterizations (via STATION_ASF), in all these idealized possible air-sea meteorological states, must be checked against a supposedly trustable reference solution, plus/minus a tolerance range not to deviate from (to allow the deviation from the reference inherent to each tested bulk parameterization). This reference solution, and this tolerance, are constructed independently and outside of NEMO. They are based on the mean, and twice the standard deviation, respectively, across all the members (1 member = 1 bulk parameterizations, N=5). This reference solution and tolerance range, just as the idealized input atmospheric and sea-surface forcings, are provided in the same NetCDF file: STATION_ASF/input_data/input_output_VALIDATION_IDEALIZED.nc

Performing the sanity test

First compile the STATION_ASF test-case as follows (compile with xios-2.5 support → check your ARCH file):

./makenemo -a STATION_ASF -m <your_arch> -n STATION_ASF2 -j 4

(successful compilation generates tests/STATION_ASF2/BLD/bin/nemo.exe

Move to: tests/STATION_ASF/SANITY_CHECK/

There, in script sanity_check_SBCBLK.sh, double check that the variables given a value in the first lines are consistent with your setup (it should).

Launch the script:

$ ./sanity_check_SBCBLK.sh

The report is both interactively shown in the standard output and spawned in the report file:

• SBCBLK.success the test passed :)
• SBCBLK.fail the test failed :(

In case of failure, read the rapport to know which algorithm/computed variables did not pass the test... You should also re-run the script sanity_check_SBCBLK.sh with the "more" argument:

$ ./sanity_check_SBCBLK.sh more

This will generate more output such as figure of time series for the tested variables.

Dependencies

In order for the python script analyze_output.py to work, you need Python 3 with the following modules:

• NumPy
• netCDF4
• (Matplotlib)

Example of the report for a successful test

############ FINAL REPORT ############

 ***** Algorithm "ECMWF" PASSED sanity check !!!

 ***** Algorithm "NCAR" PASSED sanity check !!!

 ***** Algorithm "COARE3p0" PASSED sanity check !!!

 ***** Algorithm "COARE3p6" PASSED sanity check !!!

 ***** Algorithm "ANDREAS" PASSED sanity check !!!

 Test performed on the following NEMO prognostic variables:
  ==> qsb_oce, qla_oce, qlw_oce, taum, Cd_oce, Ce_oce

   ####################################
   ###    TEST PASSED FOR SBCBLK !  ###
   ####################################

Playing with STATION_ASF

Input forcing files to test STATION ASF

By default, STATION_ASF comes with two forcing sets:

• The PAPA forcing is an "open-ocean-only" hourly forcing, that corresponds to a real off-shore platform, the PAPA station (North-East Pacific, 50°N, 145°W). Hence the data provided for the PAPA test is actual data measured by the PAPA station.

• The ERA5_NorthGreenland forcing simulates a virtual station as it is extracted from the ECMWF ERA5 reanalysis right north of Greenland (84°N,36°W). This forcing is also hourly and allows for STATION_ASF to be used with sea-ice support as this particular location is ice-covered year-round.

PAPA forcing

One full year (2018) of processed hourly data from the PAPA station (buoy) are found in the 3 following files (found in tests/STATION_ASF/input_data):

• Station_PAPA_50N-145W_atm_hourly_y2018.nc → contains hourly surface atmospheric state
• Station_PAPA_50N-145W_precip_daily_y2018.nc → contains daily precipitation
• Station_PAPA_50N-145W_oce_hourly_y2018.nc → contains hourly sea surface state

For station PAPA (50.1 N, 144.9 W), air temperature and humidity are measured at 2.5 m, the wind speed at 4 m, and the SST at 1 m below the surface, hence the following namelist parameters are given:

...
&namusr_def
    rn_dept1 =    1. 
...
&namc1d
    rn_lat1d =  50.1 
    rn_lon1d = 215.1
...
&namsbc_blk
    ...
    rn_zqt = 2.5
    rn_zu  = 4.
    ...
    ln_humi_rlh = .true.  !  humidity in PAPA data is relative humidity  [%]
    ...

The namelists for the PAPA forcing are located into EXPREF/PAPA/oce/

ERA5_NorthGreenland forcing

The entire forcing is found in one single file: ERA5_NorthGreenland_surface_84N_-36E_1h_y2018.nc. Since we are dealing with a reanalysis of the ECMWF:

...
&namusr_def
    rn_dept1 = 1. ! we assume ECMWF uses a prescribed bulk SST product at the standard depth of 1m...
...
&namc1d
    rn_lat1d =  84. 
    rn_lon1d = 324.
...
&namsbc_blk
    ...
    rn_zqt =  2.
    rn_zu  = 10.
    ...
    ln_humi_dpt = .true.  !  humidity in ERA5 is dew-point temperature [K]
    ...

The namelists for the ERA5_NorthGreenland forcing are located into ERA5/oce+ice/ or ERA5/oce, depending whether you want to use sea-ice support or not.

Compiling and launching STATION_ASF simulations

First compile the test-case as follows (compile with xios-2.5 support → check your ARCH file):

$ ./makenemo -a STATION_ASF -m <your_arch> -n STATION_ASF2 -j 4

Move to tests/STATION_ASF/EXPREF/, there, you can use the script launch_sasf.sh to launch STATION_ASF simulations. You need to adapt the following variable to your environment in the script:

• CONFIG_BLD : the name of the sub-directory of tests/ in which STATION_ASF has been compiled (default: CONFIG_BLD="STATION_ASF2")

• FORCING : this is where you pick the forcing you want to use, and wether to use sea-ice support or not (only available for ERA5_NorthGreenland forcing)

• PROD_DIR : Directory in which the simulation will be installed and run

• MPI_LAUNCH: this is where you can adapt how the nemo.exe executable is launched on your system (default: MPI_LAUNCH="mpirun -n 1")

Now, it's time to launch simulations:

$ ./launch_sasf.sh

If everything goes according to plan, launch_sasf.sh should have generated the 4 following output files into ${PROD_DIR}/output (example for PAPA forcing, 4 algos tested):

STATION_ASF-ANDREAS_PAPA_1h_20180101_20181231_gridT.nc
STATION_ASF-COARE3p6_PAPA_1h_20180101_20181231_gridT.nc
STATION_ASF-ECMWF_PAPA_1h_20180101_20181231_gridT.nc
STATION_ASF-NCAR_PAPA_1h_20180101_20181231_gridT.nc

Post-processing and figures

Use the plot_station_asf_OCE.py script (Python 3) to generate a multitude of figures that compares the open ocean transfer coefficients and fluxes between the 4 algorithms, in our case with the PAPA forcing:

$ ./plot_station_asf_OCE.py -d <PROD_DIR> -f PAPA

Example of a comparison plot:

If you have used a forcing with sea-ice support, such as ERA5_NorthGreenland, you can do the same for sea-ice transfer coefficients and fluxes, which will compare air-ice bulk algorithms:

$ ./plot_station_asf_ICE.py -d <PROD_DIR> -f ERA5_NorthGreenland

Example of a comparison plot: Note: when sea-ice support is enabled, typically by using the following FORCING configuration in script launch_sasf.sh:

FORCING="ERA5_NorthGreenland" ; i_sea_ice=1 ; SFORC="ERA5_NorthGreenland_surface_84N_-36E_1h"

the fact that i_sea_ice=1 trigers the computation of air-ice fluxes with different bulk air-ice algorithms, over the remaining open-ocean fraction the same air-sea algorithm is used: ECMWF.

TO FINISH, BROKEN !!!

Then, you can fire the Jupyter notebook station_asf_notebook.ipynb found into the notebook directory! In which you should update cprod_dir to the same path as PROD_DIR of launch_sasf.sh...

/Laurent, November 2020.