Step 1: Getting meteorological data from IFS or ERA5 reanalysis

Boundary conditions for WRF can be freely downloaded from ftp://ftp.ecmwf.int/pub/wrf. The output comes from ECMWF's operational HRES forecast and only one day's data is available. For more information please have a look at: ECMWF WRF Test Data. For those who have access to ECMWF MARS (access restricted) they can find the recipe how to retrieve the data for the past.

Alternatively, users can download the freely available ERA5 global reanalysis data from the C3S Climate Data Store (CDS) to drive WRF meteorological component. Please read through How to download ERA5. You also need to have a look at the parameter table in ECMWF WRF Test Data for retrieving relevant data.

...

We tested with the CAMS reanalysis data for driving the WRF-Chem model. Please have a look at how to download the CAMS Reanalysis data via the ECMWF Web API so  so that you have a good understanding of the scripts below. Scripts below are using ECMWF's Web API.

Script for retrieving aerosols, parameter names are given in the table bellow:

#!/usr/bin/env python
from ecmwfapi import ECMWFDataServer
   
server = ECMWFDataServer()
   
server.retrieve({
	'dataset'   : "cams_reanalysis

#!/usr/bin/env python
from ecmwfapi import ECMWFDataServer
   
server = ECMWFDataServer()
   
server.retrieve({
	'dataset'   : "cams_reanalysis",
    'class'     : "mc",
	'type'      : "an",
	'stream'    : "oper",
	'expver'    : "eac4",
    'levtype'   : "ml",
    'repres'	: "gg",
	'levellist'	: "7/to/60",
    'param'     : "T/1.210/2.210/3.210/4.210/5.210/6.210/7.210/8.210/9.210/10.210/11.210",
	'date'      : "20100101/to/20100102",
    'step'      : "0",
    'timeclass'      : "0/to/21/by/3mc",
	'grid'		type'      : "0.75/0.75an",
	'stream'    'target : "oper",
	'expver'    : "AER_20100101_20100102_eac4.grib"
})

#!/usr/bin/env python
from ecmwfapi import ECMWFDataServer
   
server = ECMWFDataServer()
   
server.retrieve({
	'dataset'   : "cams_reanalysis,
    'levtype'   : "ml",
    'repres'	: "gg",
	'levellist'	: "7/to/60",
    'classparam'     : "mcT/1.210/2.210/3.210/4.210/5.210/6.210/7.210/8.210/9.210/10.210/11.210",
	'typedate'      : "an20100101/to/20100102",
	'stream'    : "oper",
	'expver'step'      : "eac40",
    'levtypetime'   : "ml",
    'repres'	: "gg0/to/21/by/3",
	'levellistgrid'		: "7/to/600.75/0.75",
     'paramtarget'     : "203.210/123.210/27.217/121.210/13.217/6.217/124.210/122.210",
	'date'      : "20100101/to/20100102",
    'step'      : "0",
    'time'      : "0/to/21/by/3",
	'grid'		: "0.75/0.75",
    'target'    : "GRG_20100101_20100102_eac4.grib"
})
AER_20100101_20100102_eac4.grib"
})

Script for retrieving global reactive gases, parameter names are given in the table bellow:

#!/usr/bin/env python
from ecmwfapi import ECMWFDataServer
   
server = ECMWFDataServer()
   
server.retrieve({
	'dataset'   : "cams_reanalysis",
    'class'     : "mc",
	'type'      : "an",
	'stream'    : "oper",
	'expver'    : "eac4",
    'levtype'   : "ml",
    'repres'	: "gg",
	'levellist'	: "7/to/60",
    'param'     : "203.210/123.210/27.217/121.210/13.217/6.217/124.210/122.210",
	'date'      : "20100101/to/20100102",
    'step'      : "0",
    'time'      : "0/to/21/by/3",
	'grid'		: "0.75/0.75",
    'target'    : "GRG_20100101_20100102_eac4.grib"
})

Script for retrieving volatile organic compounds, parameter names are given in the table bellow:

#!/usr/bin/env python
from ecmwfapi import ECMWFDataServer
   
server = ECMWFDataServer()
   
server.retrieve({
	'dataset'   : "cams_reanalysis",
    'class'     : "mc",
	'type'      : "an",
	'stream'    : "oper",
	'expver'    : "eac4",
    'levtype'   : "ml",
    'repres'	: "gg",
	'levellist'	: "7/to/60",
    'param'     : "52.217/45.217/9.217/42.217/47.217/46.217/10.217/12.217/11.217/16.217/43.217/7.217/15.217",
	'date'      : "20100101/to/20100102",
    'step'      : "0",
    'time'      : "0/to/21/by/3",
	'grid'		: "0.75/0.75",
    'target'    : "GRG_voc_20100101_20100102_eac4.grib"
})

Script for retrieving h2o2:

#!/usr/bin/env python
from ecmwfapi import ECMWFDataServer
   
server = ECMWFDataServer()
   
server.retrieve({
	'dataset'   : "cams_reanalysis",
    'class'     : "mc",
	'type'      : "an",
	'stream'    : "oper",
	'expver'    : "eac4",
    'levtype'   : "ml",
    'repres'	: "gg",
	'levellist'	: "7/to/60",
    'param'     : "3.217",
	'date'      : "20100101/to/20100102",
    'step'      : "0",
    'time'      : "0/to/21/by/3",
	'grid'		: "0.75/0.75",
    'target'    : "GRG_h2o2_20100101_20100102_eac4.grib"
})

Script for retrieving surface pressure:

#!/usr/bin/env python
from ecmwfapi import ECMWFDataServer
   
server = ECMWFDataServer()
   
server.retrieve({
	'dataset'   : "cams_reanalysis",
    'class'     : "mc",
	'type'      : "an",
	'stream'    : "oper",
	'expver'    : "eac4",
    'levtype'   : "ml",
    'repres'	: "gg",
	'levellist'	: "1",
    'param'     : "152",
	'date'      : "20100101/to/20100102",
    'step'      : "0",
    'time'      : "0/to/21/by/3",
	'grid'		: "0.75/0.75",
    'target'    : "PS_20100101_20100102_eac4.grib"
})

...

Before running the script below you will need to have these packages installed:

• netcdf4
• cdo
• nco
  

You also need to download the get_tablecol script and and table_tm5ver15htap.txt file into the same directory where script is to be run. The next step is to run the script below:

...

With a set of additional utilities, it is possible to use the mozbc package provided by the Atmospheric Chemistry Observations and Modelling Lab (ACOM) of NCAR to pre-process CAMS data with some minor modifications to the original code. The set of additional utilities has been developed as part of the AQMEII project and kindly provided by A. Lupascu (IASS-Posdam) and C. Knote (NCAR):  public_box.tar.gz. The package contains:

Step 4: Running the model

The first step is to run the WRF model but only up to real.exe. Instruction on how run the model are provided in WRF official user guide. Note that you should not execute the wrf.exe because we still do not have a chemical BC interpolated to the WRF grid. This will be created using the utility provided by AQMEII and the mozart package. Before running this step you should check and edit paths in convert.sh and MACC_BC2MOZART.ncl if necessary.

$> cd ECMWF2WRFChem/
$> ./convert.sh

This step converts four NetCDF files (AER_*, GRG_*, GRG_voc_*, and PS_*) into a single AQMEII_*.nc file.

Once it is completed you can run the next step. Unpack, mozbc.tar, go to the mozbc main directory, copy mo_mozart_lib.patch, install, edit path to WRF run directory in the saprc99.inp namelist, and finally run mozbc.

$> tar -xvf mozbc.tar
$> cd mozbc/
$> cp public_box/mo_mozart_lib.patch .
$> patch < mo_mozart_lib.patch
$> make_mozbc
$> mozbc < saprc99.inp > mozbc.out

...

Step 4: Running the model

The first step is to run the WRF model but only up to real.exe. Instruction on how run the model are provided in WRF official user guide. Note that you should not execute the wrf.exe because we still do not have a chemical BC interpolated to the WRF grid. This will be created using the utility provided by AQMEII and the mozart package. Before running this step you should check and edit paths in convert.sh and MACC_BC2MOZART.ncl if necessary.

$> cd ECMWF2WRFChem/
$> ./convert.sh

This step converts four NetCDF files (AER_*, GRG_*, GRG_voc_*, and PS_*) into a single AQMEII_*.nc file.

Once it is completed you can run the next step. Unpack, mozbc.tar, go to the mozbc main directory, copy mo_mozart_lib.patch, install, edit path to WRF run directory in the saprc99.inp namelist, and finally run mozbc.

$> tar -xvf mozbc.tar
$> cd mozbc/
$> cp public_box/mo_mozart_lib.patch .
$> patch < mo_mozart_lib.patch
$> make_mozbc
$> mozbc < saprc99.inp > mozbc.out

This program will read NetCDF files created in the previous step (AQMEII_*.nc), chemical variables from it will be interpolated on WRF grid and added to wrfinput_d01 and wrfbdy_d01 files. Once this step has completed successfully you are ready to execute wrf.exe.

...

...