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AWS_machine
WRFChem_LinuxMachine
WRFChem_new_postproc
WRF_12km
WRF_4km
anthro_and_dust
nested_input_files
operational_WRF_Chem
with_chemistry_anthro
AQI_WRFChem.R
Crontab_HPC_FK.docx
ENVIRONM_VARIABLES_R_HPC.docx
README.md
Settings for WRF.docx
all_station_info1.prn
bash_profile_copy
copyoldData.sh
download_GFS0.25.sh
download_GFS_today.sh
download_gfs.sh
execute_Model.sh
export.sh
export_FW.sh
nc_WRFChem_post_proc_d01.R
sendMail.py
short_execute_Model.sh
shp_buffer_AQ_UAE.R
wrfchem_env.txt
wrfpost_dust_20170927_airquality.ncl
wrfpost_dust_DUST.ncl
wrfpost_met.ncl

README.md

WRF-Chem

A series of R script to post process outputs from the WRFChem (WRF-Chem) air quality model. Maps of regridded data are proposed in an operational way.

a) Run WRF-Chem

The WRF-Chem model is run following the methodology reported in the script execute_Model_lsf.sh . This script reports all the necessary steps to run WRF-Chem in two domain (one main domain (d01) and one nested domain (d02)). However, during the execution, only d01 is processed even if, all the executable files for d02 are also generated. N.B. please do not change the methodology to setup WRF-Chem operating with 2 domains. Even if it not currently generating output data for the second domain (4km resolution), it is still the optimal configuration but with long-time run time.

b) Post-processing

WRF-Chem output data are post-processed by the script POSTPROCESSING.sh . This script uses .ncl and R codes to generate .tif files to be synchronized into the cesam-web-prod server. .tif files are generated by the R script nc_WRFChem_post_proc_d01.R . Basically, this script extracts air pollution variables (PM2.5, PM10, NO2, SO2, O3 and CO) from netcdf files and converts them into /tif files (after some cropping and re-gridding).

Please hit me up if should you need further information