pyPDAF.PDAF.put_state_prepost

pyPDAF.PDAF.put_state_prepost()

It is used to preprocess and postprocess of the ensemble.

No DA is performed in this function. Compared to pyPDAF.PDAF.assimilate_prepost(), this function does not set assimilation flag, and does not distribute the processed ensemble to the model field. This function also does not set the next assimilation step as pyPDAF.PDAF.assimilate_prepost() because it does not call pyPDAF.PDAF.get_state().

This function executes the user-supplied functions in the following sequence:
  1. py__collect_state_pdaf

  2. py__prepoststep_state_pdaf (preprocess, step < 0)

Parameters:
  • py__collect_state_pdaf (Callable[dim_p:int, state_p : ndarray[tuple[dim_p], np.float64]]) –

    Routine to collect a state vector

    Callback Parameters
    • dim_pint
      • pe-local state dimension

    • state_pndarray[tuple[dim_p], np.float64]
      • local state vector

    Callback Returns
    • state_pndarray[tuple[dim_p], np.float64]
      • local state vector

  • py__prepoststep_pdaf (Callable[step:int, dim_p:int, dim_ens:int, dim_ens_p:int, dim_obs_p:int, state_p : ndarray[tuple[dim_p], np.float64], uinv : ndarray[tuple[dim_ens-1, dim_ens-1], np.float64], ens_p : ndarray[tuple[dim_p, dim_ens], np.float64], flag:int]) –

    User supplied pre/poststep routine

    Callback Parameters
    • stepint
      • current time step (negative for call after forecast)

    • dim_pint
      • pe-local state dimension

    • dim_ensint
      • size of state ensemble

    • dim_ens_pint
      • pe-local size of ensemble

    • dim_obs_pint
      • pe-local dimension of observation vector

    • state_pndarray[tuple[dim_p], np.float64]
      • pe-local forecast/analysis state (the array ‘state_p’ is not generally not initialized in the case of seik. it can be used freely here.)

    • uinvndarray[tuple[dim_ens-1, dim_ens-1], np.float64]
      • inverse of matrix u

    • ens_pndarray[tuple[dim_p, dim_ens], np.float64]
      • pe-local state ensemble

    • flagint
      • pdaf status flag

    Callback Returns
    • state_pndarray[tuple[dim_p], np.float64]
      • pe-local forecast/analysis state (the array ‘state_p’ is not generally not initialized in the case of seik. it can be used freely here.)

    • uinvndarray[tuple[dim_ens-1, dim_ens-1], np.float64]
      • inverse of matrix u

    • ens_pndarray[tuple[dim_p, dim_ens], np.float64]
      • pe-local state ensemble

Returns:

flag – Status flag

Return type:

int