PDAFlocal_assimilate_lnetf

This page documents the routine PDAFlocal_assimilate_lnetf of PDAF.

The routine is typically called in assimilate_pdaf or directly in the model code.

The general aspects of the filter specific routines PDAFlocal_assimilate_* are described on the page Modification of the model code for the ensemble integration and its sub-page on inserting the analysis step. The routine is used in the fully-parallel implementation variant of the data assimilation system. When the 'flexible' implementation variant, the routines `PDAFlocal_put_state_*' are used.

The interface when using the LNETF algorithm is the following:

  SUBROUTINE PDAFlocal_assimilate_lnetf(U_collect_state, U_distribute_state, U_init_dim_obs_f, U_obs_op_f, &
                                  U_init_obs_f, U_init_obs_l, U_prepoststep, U_likelihood_l, &
                                  U_init_n_domains, U_init_dim_l, U_init_dim_obs_l, &
                                  U_g2l_obs, &
                                  U_init_obsvar, U_init_obsvar_l, U_next_observation, status_pdaf)

with the following arguments:

• U_collect_state: The name of the user-supplied routine that initializes a state vector from the array holding the ensemble of model states from the model fields. This is basically the inverse operation to U_distribute_state used in PDAF_get_state
• U_distribute_state: The name of a user supplied routine that initializes the model fields from the array holding the ensemble of model state vectors.
• U_init_dim_obs_f: The name of the user-supplied routine that provides the size of the full observation vector
• U_obs_op_f: The name of the user-supplied routine that acts as the full observation operator on some state vector
• U_init_obs_f: The name of the user-supplied routine that initializes the full vector of observations
• U_init_obs_l: The name of the user-supplied routine that initializes the vector of observations for a local analysis domain
• U_prepoststep: The name of the pre/poststep routine as in PDAF_get_state
• U_likelihood_l: The name of the user-supplied routine that computes the local likelihood of an ensemble state.
• U_init_n_domains: The name of the routine that provides the number of local analysis domains
• U_init_dim_l: The name of the routine that provides the state dimension for a local analysis domain
• U_init_dim_obs_l: The name of the routine that initializes the size of the observation vector for a local analysis domain
• U_g2l_obs: The name of the routine that initializes a local observation vector from a full observation vector
• U_init_obsvar: The name of the user-supplied routine that provides a global mean observation error variance (This routine will only be executed, if an adaptive forgetting factor is used)
• U_init_obsvar_l: The name of the user-supplied routine that provides a mean observation error variance for the local analysis domain (This routine will only be executed, if a local adaptive forgetting factor is used)
• U_next_observation: The name of a user supplied routine that initializes the variables nsteps, timenow, and doexit. The same routine is also used in PDAF_get_state.
• status_pdaf: The integer status flag. It is zero, if the routine is exited without errors.

Note:

• The order of the routine names does not show the order in which these routines are executed. See the section on the order of the execution on the page on implementing the analysis step of the LNETF algorithm.

The user-supplied call-back routines are described on the page on implementing the analysis step of the LNETF.

It is recommended that the value of status_pdaf is checked in the program after the routine is executed. Only if its value is 0 the initialization was successful.

PDAF also has a Simplified Interface providing the routine PDAFlocal_assimilate_lnetf_si. In the simplified interface, the name of the user-supplied routines have predefined names and do not appear in the call to PDAFlocal_assimilate_lnetf_si. More information on the pre-defined names is provided in the page on implementing the analysis step of the LNETF algorithm.