Parameters¶

stepint: current time step (negative for call before analysis/preprocessing)
dim_pint: PE-local state vector dimension
dim_ensint: number of ensemble members
dim_ens_lint: number of ensemble members run serially on each model task
dim_obs_pint: PE-local dimension of observation vector
state_pndarray[np.float64, ndim=1]: pe-local forecast/analysis state (the array ‘state_p’ is generally not initialised in the case of ESTKF/ETKF/EnKF/SEIK, so it can be used freely here.) Array shape: (dim_p)
uinvndarray[np.float64, ndim=2]: Inverse of the transformation matrix in ETKF and ESKTF; inverse of matrix formed by right singular vectors of error covariance matrix of ensemble perturbations in SEIK/SEEK. not used in EnKF. Array shape: (dim_ens-1, dim_ens-1)
ens_pndarray[np.float64, ndim=2]: PE-local ensemble Array shape: (dim_p, dim_ens)
flagint: pdaf status flag

Returns¶

state_pndarray[np.float64, ndim=1]: pe-local forecast/analysis state (the array ‘state_p’ is generally not initialised in the case of ESTKF/ETKF/EnKF/SEIK, so it can be used freely here.) Array shape: (dim_p)
uinvndarray[np.float64, ndim=2]: Inverse of the transformation matrix in ETKF and ESKTF; inverse of matrix formed by right singular vectors of error covariance matrix of ensemble perturbations in SEIK/SEEK. not used in EnKF. Array shape: (dim_ens-1, dim_ens-1)
ens_pndarray[np.float64, ndim=2]: PE-local ensemble Array shape: (dim_p, dim_ens)