= 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 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 [wiki:PDAF_diag_stddev_nompi].

The interface is the following: 
{{{
SUBROUTINE PDAF_diag_stddev(dim, dim_ens, &
     state, ens, stddev, do_mean, COMM_filter, status)
}}}
with the following arguments:
{{{
  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 is ensemble mean state it does not need to be computed again.