Generate an ensemble of initial states

The DART executable perturb_single_instance takes a single ROMS restart file as input and will generate additional copies of the restart file with small perturbations to the first file, in order to generate an ensemble of initial model states.

You should always use a restart file from your experimental domain. But for demonstration purposes, DART profiles an archive that contains several restart files. To download the demo archive:

cd DART/models/ROMS/work
wget https://www.image.ucar.edu/pub/DART/ROMS/dart_roms_test_data.tar.gz
tar -xzvf dart_roms_test_data.tar.gz

This will extract a directory named wc12 that contains .in files and netCDF files from the West Coast domain described in Moore et al. (2020) 1.

ls wc12
ocean.in                     varinfo.dat
roms_posterior_0001_37700.nc wc12_avg.nc
roms_posterior_0002_37700.nc wc12_dia.nc
roms_posterior_0003_37700.nc wc12_his.nc
roms_posterior_0004_37700.nc wc12_ini_0001.nc
s4dvar.in

The perturb_single_instance executable expects the initial input file to be named roms_input.nc so use a symbolic link to associate one of the netCDF restart files in wc12 with that name.

ln -s wc12/roms_posterior_0001_37700.nc roms_input.nc

Next, add a namelist in the input.nml file named perturb_single_instance_nml to instruct the executable how many perturbed copies it should create. Open input.nml with a text editor and add a namlist similar to:

&perturb_single_instance_nml
   ens_size               = 3
   input_files            = 'roms_input.nc'
   output_files           = 'wc12/roms_posterior_0005_37700.nc','wc12/roms_posterior_0006_37700.nc','wc12/roms_posterior_0007_37700.nc'
   output_file_list       = ''
   perturbation_amplitude = 0.2
 /

Save the namelist and run the executable:

./perturb_single_instance

You should see as many perturbed files as you specified in the namelist:

ls -art wc12
[ ...  ]
roms_posterior_0005_37700.nc
roms_posterior_0006_37700.nc
roms_posterior_0007_37700.nc

References

1

Moore, A., J. Zavala-Garay, H. G. Arango, C. A. Edwards, J. Anderson, and T. Hoar, 2020: Regional and basin scale applications of ensemble adjustment Kalman filter and 4D-Var ocean data assimilation systems. Progress in Oceanography, 189, 102450, https://doi.org/10.1016/j.pocean.2020.102450.