pyPDAF.PDAF.omi_init_obscovar_cb

pyPDAF.PDAF.omi_init_obscovar_cb()

This is an internal PDAF-OMI function that is used as a call-back function to construct a full observation error covariance matrix used only in stochastic EnKF. This could be used to modify the observation variance when OMI is used with pyPDAF.PDAF.assimilate_xxx instead of pyPDAF.PDAF.omi_assimilate_xxx.

Parameters:

• step (int) – Current time step

• dim_obs (int) – Dimension of observation vector

• dim_obs_p (int) – PE-local dimension of obs. vector

• covar (ndarray[tuple[dim_obs, dim_obs], np.float64]) –

  Observation error covar. matrix

  The 1st-th dimension dim_obs is Dimension of observation vector The 2nd-th dimension dim_obs is Dimension of observation vector

• m_state_p (ndarray[tuple[dim_obs_p], np.float64]) –

  Observation vector

  The array dimension dim_obs_p is PE-local dimension of obs. vector

• isdiag (bool) – Whether matrix R is diagonal

Returns:

• covar (ndarray[tuple[dim_obs, dim_obs], np.float64]) – Observation error covar. matrix

  The 1st-th dimension dim_obs is Dimension of observation vector The 2nd-th dimension dim_obs is Dimension of observation vector

• isdiag (bool) – Whether matrix R is diagonal