The WRF Weather Model and DART

How does DART interact with running WRF?

Most users with large WRF domains run a single cycle of filter to do assimilation, and then advance each ensemble member of WRF from a script, possibly submitting them in a batch to the job queues.

For smaller WRF runs, if WRF can be compiled without MPI (the ‘serial’ configuration) then filter can cycle inside the same program, advancing multiple ensemble members in parallel. See the WRF documentation pages for more details.

I have completed running filter and I have the filter_restart.#### files. Can you refer me to the utility to convert them back to a set of wrfinput_d01 files?

If you are using the advance_model.csh script that is distributed with DART, it will take care of converting the filter output files back to the WRF input files for the next model advance.

If you are setting up a free run or doing something different than what the basic script supports, read on to see what must be done.

When you finish running DART it will have created a set of sssss.#### restart files, where the sssss part of the filename comes from the setting of &filter_nml :: restart_out_file_name (and is frequently filter_restart). The .#### is a 4 digit number appended by filter based on the ensemble number. These files contain the WRF state vector data that was used in the assimilation, which is usually a subset of all the fields in a wrfinput_d01 file.

dart_to_wrf is the standard utility to insert the DART state information into a WRF input file, e.g. wrfinput_d01. For multiple WRF domains, a single run of the converter program will update the _d02, _d03, …, files at the same time as the _d01 file.

In the input.nml file, set the following:

&dart_to_wrf_nml
   model_advance_file = .false.
   dart_restart_name  = 'filter_restart.####',
/

where ‘####’ is the ensemble member number. There is no option to alter the input/output WRF filename. Run dart_to_wrf. Remember to preserve each wrfinput_d01 file or you will simply keep overwriting the information in the same output file. Repeat for each ensemble member and you will be ready to run WRF to make ensemble forecasts.

If filter is advancing the WRF model, and you want to spawn forecasts from intermediate assimilation steps:
Use the assim_model_state_ic.#### files instead of the filter_restart.#### files, and set the model_advance_file namelist item to be .true. .

[top]