pyPDAF.PDAF.diag_ensstats

pyPDAF.PDAF.diag_ensstats()

Computing the skewness and kurtosis of the ensemble of a given element of the state vector.

The definition used for kurtosis follows that used by [1].

References

[1]

Lawson, W. G., & Hansen, J. A. (2004). Implications of stochastic and deterministic filters as ensemble-based data assimilation methods in varying regimes of error growth. Monthly weather review, 132(8), 1966-1981.

Parameters:

• element (int) – Index of state vector/ensemble element to be used. If element=0, mean values over all elements are computed

• state (ndarray[tuple[dim], np.float64]) –

  State vector (typically ensemble mean)

  The array dimension dim is PE-local state dimension

• ens (ndarray[tuple[dim, dim_ens], np.float64]) –

  State ensemble

  The 1st-th dimension dim is PE-local state dimension The 2nd-th dimension dim_ens is Ensemble size

Returns:

• skewness (float) – Skewness of ensemble

• kurtosis (float) – Kurtosis of ensemble

• status (int) – Status flag (0=success)