wiki:PDAF_diag_stddev

PDAF_diag_stddev

This page documents the routine PDAF_diag_stddev of PDAF, which was introduced with PDAF V3.0.

This routine computes mean ensemble standard deviation taking into account domain-decomposition for parallelized models. The output is the square root of the spatial mean variance.

The routine can be called in the pre/poststep routine of PDAF both before and after the analysis step to compute the ensemble statistics.

This variant computes the standard deviation for the provided ensemble over the full decomposed domain of a parallel model. The variant without parallelization is PDAF_diag_stddev_nompi.

The interface is:

SUBROUTINE PDAF_diag_stddev(dim, dim_ens, &
     state, ens, stddev, do_mean, COMM_filter, status)

  INTEGER, INTENT(in) :: dim_p                 ! process-local state dimension
  INTEGER, INTENT(in) :: dim_ens               ! Ensemble size
  REAL, INTENT(inout) :: state_p(dim_p)        ! process-local state vector
  REAL, INTENT(in)    :: ens_p(dim_p, dim_ens) ! process-local state ensemble
  REAL, INTENT(out)   :: stddev_g              ! Global mean standard deviation of ensemble
  INTEGER, INTENT(in) :: do_mean               ! 1 to also compute ensemble mean; 
                                               ! 0 for no computation of mean
  INTEGER, INTENT(in) :: COMM_filter           ! Filter communicator
  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 already the ensemble mean state it does not need to be computed again.
  • The routine performs MPI operations to obtain the global result. These operations are done within the communicator COMM_filter which is specified as an argument. This allows to also use the routine if PDAF was not initialized by calling PDAF_init.
Last modified 4 days ago Last modified on Mar 26, 2025, 2:24:58 PM
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