Changes between Version 9 and Version 10 of ImplementAnalysisseik

Timestamp:

Aug 27, 2010, 9:39:34 AM (14 years ago)

Author:

lnerger

Comment:

--

ImplementAnalysisseik

@@ -92 +92 @@
 The routine is called during the analysis step. In the algorithms the product of the inverse of the observation error covariance matrix with some matrix has to be computed. For the SEIK filter this matrix holds the observed part of the ensemble perturbations ('''HL'''). The matrix is provided as `A_p`. The product has to be given as `C_p`.
 
+For a model with domain decomposition, `A_p` contains the part of the matrix that resides on the model sub-domain of the calling process. The product has to be computed for this sub-domain, too.
 
 Hints:
@@ -101 +102 @@
 == `U_init_obsvar` (init_obsvar.F90) ==
 
+This routine is used by the global filter algorithms SEIK and  ETKF as well as the local filters LSEIK and LETKF. The routine is only called if the adaptive forgetting factor is used (`type_forget=1` in the example impementation).
+
+The interface for this routine is:
 {{{
 SUBROUTINE init_obsvar(step, dim_obs_p, obs_p, meanvar)
@@ -110 +114 @@
 }}}
 
-! User-supplied routine for PDAF (SEIK/LSEIK/ETKF/LETKF)
-! with adaptive forgetting factor. This routine will
-! only be called, if the adaptive forgetting factor
-! feature is used. Please note that this is an 
-! experimental feature.
-!
-! The routine is called in SEIK during the analysis or 
-! in LSEIK before the loop over local analysis domains 
-! by the routine PDAF\_set\_forget that estimates an 
-! adaptive forgetting factor.  The routine has to 
-! initialize the mean observation error variance.  
-! For SEIK this should be the global mean, while for 
-! LSEIK it should be the mean for the PE-local 
-! sub-domain.  (See init\_obsvar\_local() for a 
-! localized variant for LSEIK.)
+The routine is called in the global filters during the analysis or 
+by the routine that computes an adaptive forgetting factor (PDAF_set_forget).
+The routine has to initialize the mean observation error variance.  
+For the global filters this should be the global mean.
+
+Hin