$ ! Due to domain decomposition in our case the mean variance is computed $ ! for the full domain using the function MPI_Allreduce $#ifndef CLMSA $ if (model .eq. tag_model_parflow) then $ meanvar_p = 0 $ sum_p = 0 $ count = 0 $ do i = 1, dim_obs_p $ if(pressure_obserr_p(i) /= 0) then $ sum_p = sum_p + pressure_obserr_p(i) $ count = count + 1 $ endif $ enddo $ ! averaging the sum of observation errors with total no of non-zero observations $ meanvar_p = sum_p/count $ ! summing the average of observation errors and communicating it back to each rank $ call MPI_Allreduce(meanvar_p, meanvar, 1, MPI_REAL8, MPI_SUM, COMM_filter, MPIerr) $ ! to get the mean dividing the mean observation error by size of processors $ meanvar = meanvar/npes_filter $ end if $#endif $ $#if defined CLMSA $ if(model .eq. tag_model_clm) then $ meanvar_p = 0 $ sum_p = 0 $ count = 0 $ do i = 1, dim_obs_p $ if(clm_obserr_p(i) /= 0) then $ sum_p = sum_p + clm_obserr_p(i) $ count = count + 1 $ endif $ enddo $ ! averaging the sum of observation errors with total no of non-zero observations $ meanvar_p = sum_p/count $ ! summing the average of observation errors and communicating it back to each rank $ call MPI_Allreduce(meanvar_p, meanvar, 1, MPI_REAL8, MPI_SUM, COMM_filter, MPIerr) $ ! to get the mean dividing the mean observation error by size of processors $ meanvar = meanvar/npes_filter $ end if $#endif
| Type | Intent | Optional | Attributes | Name | ||
|---|---|---|---|---|---|---|
| integer, | intent(in) | :: | domain_p | |||
| integer, | intent(in) | :: | step | |||
| integer, | intent(in) | :: | dim_obs_l | |||
| real, | intent(in) | :: | obs_l(dim_obs_l) | |||
| real, | intent(out) | :: | meanvar_l |