pyPDAF.init_forecast

pyPDAF.init_forecast()

The routine PDAF_init_forecast has to be called once at the end of the initialization of PDAF/start of DA cycles.

This function has the purpose to initialize the model fields to be propagated from the array holding the ensemble states. In addition, the function initializes the information on how many time steps have to be performed in the upcoming forecast phase before the next assimilation step, and an exit flag indicating whether further model integrations have to be computed. These variables are used internally in PDAF and can be retrieved by the user by calling PDAF_get_fcst_info.

Parameters:

• py__next_observation_pdaf (Callable) – Get the number of time steps to be computed in the forecast phase. See details for pyPDAF.pdaf_c_cb_interface.c__next_observation_pdaf().

• py__distribute_state_pdaf (Callable) – Distribute a state vector from pdaf to the model/any arrays See details for pyPDAF.pdaf_c_cb_interface.c__distribute_state_pdaf().

• py__prepoststep_pdaf (Callable) – Process ensemble before or after DA. See details for pyPDAF.pdaf_c_cb_interface.c__prepoststep_pdaf().

• outflag (int) – Status flag

Returns:

outflag – Status flag

Return type:

int