pyPDAF.assim_offline_hyb3dvar_lestkf_nondiagr

pyPDAF.assim_offline_hyb3dvar_lestkf_nondiagr()

Offline hybrid 3DEnVar for a single DA step using non-diagonal observation error covariance matrix.

Here, the background error covariance is hybridised by a static background error covariance, and a flow-dependent background error covariance estimated from ensemble. The 3DVar generates an ensemble mean and the ensemble perturbation is generated by LESTKF in this implementation. This function should be called at each model time step.

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. The iterative optimisation:

    1. py__cvt_pdaf

    2. py__cvt_ens_pdaf

    3. py__obs_op_lin_pdaf

    4. py__prodRinvA_pdaf

    5. py__obs_op_adj_pdaf

    6. py__cvt_adj_pdaf

    7. py__cvt_adj_ens_pdaf

    8. core DA algorithm

  5. py__cvt_pdaf

  6. py__cvt_ens_pdaf

  7. Perform LESTKF:

    1. py__init_n_domains_p_pdaf

    2. py__init_dim_obs_pdaf

    3. py__obs_op_pdaf (for each ensemble member)

    4. loop over each local domain:

      1. py__init_dim_l_pdaf

      2. py__init_dim_obs_l_pdaf

      3. py__prodRinvA_l_pdaf

      4. core DA algorithm

  8. py__prepoststep_state_pdaf

Parameters:

  • py__collect_state_pdaf (Callable) – Routine to collect a state vector

  • py__distribute_state_pdaf (Callable) – Routine to distribute a state vector

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

  • py__obs_op_pdaf (Callable) – Full observation operator

  • py__prodrinva_pdaf (Callable) – Provide product R^-1 A

  • py__cvt_ens_pdaf (Callable) – Apply control vector transform matrix to control vector

  • py__cvt_adj_ens_pdaf (Callable) – Apply adjoint control vector transform matrix

  • py__cvt_pdaf (Callable) – Apply control vector transform matrix to control vector

  • py__cvt_adj_pdaf (Callable) – Apply adjoint control vector transform matrix

  • py__obs_op_lin_pdaf (Callable) – Linearized observation operator

  • py__obs_op_adj_pdaf (Callable) – Adjoint observation operator

  • py__prodrinva_l_pdaf (Callable) – Provide product R^-1 A and apply localizations

  • py__init_n_domains_p_pdaf (Callable) – Provide number of local analysis domains

  • py__init_dim_l_pdaf (Callable) – Init state dimension for local ana. domain

  • py__init_dim_obs_l_pdaf (Callable) – Initialize local dimimension of obs. vector

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

  • py__next_observation_pdaf (Callable) – Provide information on next forecast

  • outflag (int) – Status flag

Returns:

outflag – Status flag

Return type:

int