pyPDAF.PDAF.seik_TtimesA

pyPDAF.PDAF.seik_TtimesA()

This is an internal function in PDAF where it perform matrix calculation of B = TA. This allows for two types of T matrix. The resulting matrix B is the transformation matrix act on the full forecast ensemble. Mathematical description of the function is the second term of Eq. (23) and the T matrix is defined in Eq. (13) in Nerger, L., Janjić, T., Schröter, J., Hiller, W. (2012). A unification of ensemble square root Kalman filters. Monthly Weather Review, 140, 2335-2345. doi:10.1175/MWR-D-11-00102.1

Parameters:

A (ndarray[tuple[rank, dim_col], np.float64]) –

Input matrix

The 1st-th dimension rank is Rank of initial covariance matrix The 2nd-th dimension dim_col is Number of columns in A and B

Returns:

B – Output matrix (TA)

The 1st-th dimension dim_col is Number of columns in A and B

Return type:

ndarray[tuple[rank+1, dim_col], np.float64]