= PDAFomi_diag_get_ivar = 

This page documents the routine `PDAFomi_diag_get_ivar` of PDAF, which was introduced with PDAF V3.0. This is part of the [wiki:PDAFomi_observation_diagnostics PDAF-OMI observation diagnostics module].

The routine returns a pointer to a vector of the inverse observation error variances for the specified observation type (`id_obs`).

Usually all PDAFomi_diag routines are called in `prepoststep_pdaf` where the observation information can be retrieved and analyzed.

The interface is: 
{{{
  SUBROUTINE PDAFomi_diag_get_ivar(id_obs, dim_obs_p_diag, ivar_p_ptr)

    INTEGER, INTENT(in)  :: id_obs                   ! Index of observation type to return
    INTEGER, INTENT(out) :: dim_obs_p_diag           ! Observation dimension
    REAL, POINTER, INTENT(out) :: ivar_p_ptr(:)      ! Pointer to inverse observation error variances
}}}

**Notes:**
 * In case of a parallelized model, the vector `ivar_p_prt` contains the observed ensemble mean for the process-sub-domain
 * In Fortran user code the pointer to the vector of inverse observation variances should be declared in the form[[BR]] `REAL, POINTER :: ivar_p_ptr(:)`[[BR]] It does not need to be allocated. The target vector has the length `dim_obs_p_diag`.
 * If the observation diagnostics have not be activated by using [wiki:PDAFomi_set_obs_diag] the pointer will not be set and `dim_obs_diag=0` will be returned. This value can be checked before assessing the pointer array.
 * If the feature `thisobs%inno_omit` is used (see the [wiki:PDAFomi_additional_functionality page Additional functionality of PDAF-OMI]), the inverse variance of the omitted observations will show the small value set by `inno_omit`. One can use this information to exclude such observations when analyzing differences between observations and observed ensemble.