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PDAF_diag_variance_nompi
This page documents the routine PDAF_diag_variance_nompi of PDAF, which was introduced with PDAF V3.0.
This routine computes the unbiased variance of the ensemble and returns it in the form of a state vector. In addition the mean standard deviation is computed. This variant only compute the standard deviation for the provided ensemble array ens. Thus, with a domain-decomposed parallel model, the value of of the standard deviation does not consider the full domain. The variant taking into account parallelization is PDAF_diag_variance.
The interface is:
SUBROUTINE PDAF_diag_variance(dim_p, dim_ens, state_p, ens_p, variance_p, &
stddev_g, do_mean, do_stddev, status)
INTEGER, INTENT(in) :: dim_p ! state dimension
INTEGER, INTENT(in) :: dim_ens ! Ensemble size
REAL, INTENT(inout) :: state_p(dim_p) ! State vector
REAL, INTENT(in) :: ens_p(dim_p, dim_ens) ! State ensemble
REAL, INTENT(out) :: variance_p(dim_p) ! Variance state vector
REAL, INTENT(out) :: stddev_g ! Global standard deviation of ensemble
INTEGER, INTENT(in) :: do_mean ! 1 to compute ensemble mean;
! 0 take values froem state_p as ensemble mean
INTEGER, INTENT(in) :: do_stddev ! 1 to compute the ensemble mean standard deviation;
! 0 no computation of ensemble standard deviation
INTEGER, INTENT(out) :: status ! Status flag (0=success)
Note:
- The ensemble standard deviation is a common measure of the estimate model root mean square error. It is typically computed in
prepoststep_pdafto monitor the assimilation process. - The option
do_meanexists mainly for performance reasons. Ifstate_pcontains is ensemble mean state it does not need to be computed again. - The option
do_stddevalso exists for performance reasons. If one is not interested in this number, it does not need to be computed. - The routine computes the unbiased variance, i.e. the normalization is 1/(dim_ens-1)
- The routine does not perform any MPI operations and can also be used if PDAF was not initialized by calling
PDAF_init.
Note:
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