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 standard deviation 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 the following:

SUBROUTINE PDAF_diag_variance(dim_p, dim_ens, state_p, ens_p, variance_p, &
     stddev_g, do_mean, do_stddev, status)

with the following arguments:

  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_pdaf to monitor the assimilation process.
• The option do_mean exists mainly for performance reasons. If state_p contains is ensemble mean state it does not need to be computed again.
• The routine compute the unbiased variance, i.e. the normalization is 1/(dim_ens-1)