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PROGRAM filter

Contact: Jeff Anderson
Reviewers:  
Revision: $Revision: 1.2 $
Change Date: $Date: 2004/04/26 20:15:59 $
Change history: see CVS log

OVERVIEW

Main program for driving ensemble filter assimilations. This program provides a number of options that are driven from its namelist. The number of assimilation steps to be done are controlled by the input observation sequence and by the time-stepping capabilities of the model being used in the assimilation.




OTHER MODULES USED

types_mod
obs_sequence_mod
time_manager_mod
utilities_mod
assim_model_mod
random_seq_mod
assim_tools_mod
cov_cutoff_mod
location_mod
reg_factor_mod
sort_mod



NAMELIST

We adhere to the F90 standard of starting a namelist with an ampersand '&' and terminating with a slash '/'.

namelist / filter_nml /  &
      async, ens_size, cutoff, cov_inflate, start_from_restart, output_restart &
      obs_sequence_file_name, restart_in_file_name, restart_out_file_name, &
      init_time_days, init_time_seconds, output_state_ens_mean, &
      output_state_ens_spread, num_output_ens_members, output_interval, &
      num_groups, confidence_slope, output_obs_diagnostics, get_mean_reg, get_median_reg

Discussion

This namelist is read in a file called input.nml

Contents Type Description
async integer Controls whether models are advanced via a subroutine call or by writing initial condition files for ensemble members to disk and having shellscript advance the model. Option: 0 = advance by subroutine; 1 = shell advance using shell script piped to filter; 2 = advance by F90 calls to shell to advance model. Default value is 0.
ens_size integer Number of ensemble members to be integrated. Default is 20.
cutoff real(r8) Cutoff controls a distance dependent weight that modulates the impact of an observation on a state variable. The units depend both on the location module being used and on the covariance cutoff module options selected. Default is 0.2.
cov_inflate real(r8) Covariance inflation factor applied to prior estimate before each assimilation step. Default is 1.0 (no inflation).
start_from_restart logical Should initial ensemble states come from a restart file. Default is .false.
output_restart logical Should a restart file be written out for all ensemble members? Default is .false.
obs_sequence_file_name character(len = 129) File name that contains and observation sequence file. Default is 'obs_seq.in'.
restart_in_file_name character(len=129) File name for a file containing restart state for all ensemble members. Default is 'filter_ics'.
restart_out_file_name character(len = 129) File name for output restart file. Default is 'filter_restart'.
init_time_days integer Initial time of model (time is in days and seconds; see time_manager. If init_time_days and init_time_seconds are less than 0, the initial time comes from the time in the restart file. Default value is 0.
init_time_seconds integer Initial time of model in seconds. Default is 0.
output_state_ens_mean logical Output ensemble mean in state diagnostic files.
num_output_ens_members integer This number of ensemble members is output to the state diagnostics file. If this is less than the total number of ensemble members the first subset is output. Default is 0.
output_interval integer The frequency with which output diagnostics are written. Default value is 1.
num_groups integer Number of groups for hierarchical group filter. Should be a divisor of the ensemble size. Default is 1.
confidence_slope real(r8) Controls strength of bias correction algorithm. See assim_tools module. Default is 0 (no correction).
output_obs_diagnostics logical Should an observation space diagnostics file be output. Default value is .false.
get_mean_reg logical Compute time mean regressions from group filter and output to file. Only works with group filter. Default is .false.
get_median_reg logical Compute time median regression from group filter and output to file. Only works with group filter. Default is .false.



FILES




REFERENCES


ERROR CODES and CONDITIONS

RoutineMessageComment
filter output metadata in filter needs ensemble size < 10000 Ensemble sizes greater than require modifications to output ensemble code.



KNOWN BUGS




FUTURE PLANS

The filter will be modified to support parallel implementation and use of observations that can only be computed from the state prior once at the start of the assimilation. A new observation sequence module is also under development to support this and clean up the use of observations.

Discussion