pyPDAF.generate_obs_offline

pyPDAF.generate_obs_offline()

Generation of synthetic observations based on given error statistics and observation operator in offline setup.

The generated synthetic observations are based on each member of model forecast. Therefore, an ensemble of observations can be obtained. In a typical experiment, one may only need one ensemble member. The implementation strategy is similar to an assimilation step. This means that, one can reuse many user-supplied functions for assimilation and observation generation.

User-supplied functions are executed in the following sequence:

  1. py__prepoststep_state_pdaf

  2. py__init_dim_obs_pdaf

  3. py__obs_op_pdaf

  4. py__get_obs_f_pdaf

  5. py__prepoststep_state_pdaf

Parameters:

  • py__init_dim_obs_pdaf (Callable) – Initialize dimension of full observation vector

  • py__obs_op_pdaf (Callable) – Full observation operator

  • py__get_obs_f_pdaf (Callable) – Initialize observation vector

  • py__prepoststep_pdaf (Callable) – User supplied pre/poststep routine

Returns:

outflag – Status flag

Return type:

int