Contact: | Jeff Anderson |
Reviewers: | |
Revision: | $Revision: 1.2 $ |
Change Date: | $Date: 2004/04/26 20:15:59 $ |
Change history: | see CVS log |
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.
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
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
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. |
Routine | Message | Comment |
---|---|---|
filter | output metadata in filter needs ensemble size < 10000 | Ensemble sizes greater than require modifications to output ensemble code. |
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.