= PDAF_diag_stddev_nompi = 

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

This routine computes mean ensemble standard deviation.

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 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 doe snot consider the full domain. The variant taking into account parallelization is [wiki:PDAF_diag_stddev].

The interface is the following: 
{{{
SUBROUTINE PDAF_diag_stddev_nompi(dim, dim_ens, &
     state, ens, stddev, do_mean, status)
}}}
with the following arguments:
{{{
  INTEGER, INTENT(in) :: dim               !< state dimension
  INTEGER, INTENT(in) :: dim_ens           !< Ensemble size
  REAL, INTENT(inout) :: state(dim)        !< State vector
  REAL, INTENT(in)    :: ens(dim, dim_ens) !< State ensemble
  REAL, INTENT(out)   :: stddev            !< Standard deviation of ensemble
  INTEGER, INTENT(in) :: do_mean           !< 1 to also compute ensemble mean; 0 for no computation of mean
  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.
 * We recommend to use this routine only in cases where the MPI parallelization is not initialized, e.g. in separate post-analysis programs. In assimilation programs, where the parallelization is initialized for PDAF, we recommend to use the routine [wiki:PDAF_diag_stddev] for better overall compatibility.
 * The option `do_mean` exists mainly for performance reasons. If `state_p` contains is ensmeble mean state it does not need to be computed again.