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This repository contains scripts to stage RRFS data for retrospective experiments.

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rrfs-stagedata

This repository contains scripts to stage RRFS data for retrospective experiments.

We will need to stage these data for RRFS retro run:

Observation: GVF, SST, snow, conventional observation, vaisala lightning, radar reflectivity Data Assimilation: GDAS or RRFS ensemble for GSI hybrid, mesonet use list, amdar reject list Model: GFS forecast as ICs/LBCs, RAP/HRRR soil for soil surgery

These scripts mainly provide the HPSS path for each data, please make a copy and necessary changes for your use.

Clone scripts: git clone https://github.com/NOAA-GSL/rrfs-stagedata.git

Observation Scripts:

GVF: gvf.ksh, zip file contains j01 and npp data, npp is used in RRFS. SST: sst.ksh Snow: snow.ksh

RRFS reads GVF, SST and snow from the previous day for the current cycle, so if retro run start from July 20, you need to save July 19 data also.

Vaisala lightning: lightning.ksh

RAP conventional observation: obsrap.ksh, zip file contain several types of data, .rap. and rap_e data are used in RRFS, you can delete other types if it’s needed.

Radar reflectivity: use refl.ksh to get MRMS reflectivity data and unzip files. It’s almost 23K files/day, the files are saved under upperair/mrms/conus/MergedReflectivityQC automatically, so usually I put data in tmp directory, if all data looks good, then move data day by day to the desired location, for example, mv tmp/upperair/mrms/conus/MergedReflectivityQC/20230610 reflectivity/

Data Assimilation scripts:

mesonet use list and amdar reject list are saved on Jet at AIRCRAFT_REJECT="/home/role.amb-verif/acars_RR/amdar_reject_lists" SFCOBS_USELIST="/lfs4/BMC/amb-verif/rap_ops_mesonet_uselists"

If retro run is on Hera, please copy the required file to Hera. GSI reads the previous day file for the current cycle, so if retro run start from July 20, you need to save July 19 data also.

GDAS ensemble members: getFV3GDASensembles, GSI reads previous six hour GDAS members for current cycle, so if retro run starts on July 20 03Z, you need to stage July 19 18Z members also.

RRFS ensemble

retrieve_dsg_GEFS.sh: pull GEFS GRIB-2 data for initializing the RRFS ensemble Fill_GEFS_from_aws.sh: pull GEFS data from AWS and fill the DSG GEFS data gap

Previous 30 hr GEFS data is needed, if retro run starts on July 20 03Z, you need to stage July 19 00Z members also.

If need to interpolate the 3-hourly GEFS data to hourly data, please refer to the scripts at https://github.com/NOAA-GSL/GEFS_time_interpolation

Model scripts:

GFS forecast: gfs.ksh, 50 hour forecast should be enough for current RRFS. If retro starts on July 20 03Z, you need to stage July 19 18Z GFS forecast also.

If you need to interpolate 3-hourly GFS data to hourly data (e.g. 2020 gfs data), use /scratch1/BMC/wrfruc/chunhua/code/GEFS_time_interpolation/GFS_time_interp_standalone.sh

For example, get hourly data for 00Z July 27, 2020 from forecast hours 0 to 24, please do so: ./GFS_time_interp_standalone.sh 2020727 0 24 00

RAP/HRRR soil: If you use GFS for ICs, you need to do soil surgery. Use get_raphrrrsoil.ksh to get rap/hrrr soil, for example, retro run starts at 2022072003(spin up cycle), soil surgery should be done at 04Z, so stage 2022072004 rap.t04z.wrf_inout_smoke and hrrr.t04z.wrf_inout. If the data is missing for current cycle, use previous/next cycle data instead since soil does not change much.

If you use RAP for ICs, there is no need to do soil surgery.

After stage data, usually I will check the file number for each data using retro_check.ksh, it checks GFS forecast, lightning, GDAS ensembles, RAP observation and MRMS reflectivity. For other data, it’s easy to check manually. If all data looks good, then update the data path in rrfs-workflow/ush/set_rrfs_config.sh before generating the workflow.

For example, update these variables to your location on Hera if it’s needed: if [[ $DO_RETRO == "TRUE" ]] ; then … if [[ $MACHINE == "hera" ]] ; then …
RETRODATAPATH="/scratch2/BMC/zrtrr/RRFS_RETRO_DATA"

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This repository contains scripts to stage RRFS data for retrospective experiments.

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