Changes between Version 17 and Version 18 of ImplementAnalysislseik

Timestamp:

Sep 3, 2010, 12:11:26 PM (14 years ago)

Author:

lnerger

Comment:

--

ImplementAnalysislseik

@@ -313 +313 @@
 
 
-
-
 === `U_init_obsvar` (init_obsvar.F90) ===
 
@@ -337 +335 @@
  * For a model with domain-decomposition one might use the mean variance for the model sub-domain of the calling process. Alternatively one can compute a mean variance for the full model domain using MPI communication (e.g. the function `MPI_allreduce`).
  * The observation vector `obs_p` is provided to the rotine for the case that the observation error variance is relative to the value of the observations.
+
+
+=== `U_init_obsvar_local` (init_obsvar_local.F90) ===
+
+This routine is used by the local filters LSEIK and LETKF. The routine is only called if the local adaptive forgetting factor is used (`type_forget=2` in the example impementation).
+
+The interface for this routine is:
+{{{
+SUBROUTINE init_obsvar_local(domain_p, step, dim_obs_l, obs_l, meanvar_l)
+
+  INTEGER, INTENT(in) :: domain_p         ! Current local analysis domain
+  INTEGER, INTENT(in) :: step             ! Current time step
+  INTEGER, INTENT(in) :: dim_obs_l        ! Local dimension of observation vector
+  REAL, INTENT(in)    :: obs_l(dim_obs_l) ! Local observation vector
+  REAL, INTENT(out)   :: meanvar_l        ! Mean local observation error variance
+}}}
+
+The routine is called in the local filters during the loop over all local analysis domains by the by the routine that computes a local adaptive forgetting factor (PDAF_set_forget_local). The routine has to initialize a local mean observation error variance for all observations sued for the analysis in the current local analysis domain. 
+
+Hints:
+ * For a model with domain-decomposition one might use the mean variance for the model sub-domain of the calling process. Alternatively one can compute a mean variance for the full model domain using MPI communication (e.g. the function `MPI_allreduce`).
+ * The observation vector `obs_p` is provided to the rotine for the case that the observation error variance is relative to the value of the observations.