Changes between Version 9 and Version 10 of ImplementAnalysislestkf

Timestamp:

May 5, 2014, 2:06:14 PM (11 years ago)

Author:

lnerger

Comment:

--

ImplementAnalysislestkf

@@ -32 +32 @@
 With Version 1.8 of PDAF, the LESTKF [Local Error Subspace Transform Kalman Filter] algorithm has been introduced. The user-supplied routines required for the LESTKF are identical to those required for the LSEIK filter. 
 
-For the analysis step of the LESTKF, several operations related to the observations are needed. These operations are requested by PDAF by calling user-supplied routines. Intentionally, the operations are split into separate routines in order to keep the operations rather elementary as this procedure should simplify the implementation. The names of the required routines are specified in the call to the routine `PDAF_assimilate_lestkf` (or `PDAF_put_state_lestkf`) described below. With regard to the parallelization, all these routines (except `U_collect_state`, `U_distribute_state`, and `U_next_observation`) are executed by the filter processes (`filterpe=.true.`) only.
+For the analysis step of the LESTKF, several operations related to the observations are needed. These operations are requested by PDAF by calling user-supplied routines. Intentionally, the operations are split into separate routines in order to keep the operations rather elementary as this procedure should simplify the implementation. The names of the required routines are specified in the call to the routine `PDAF_assimilate_lestkf` in the fully-parallel implementation (or `PDAF_put_state_lestkf` for the 'flexible' implementation) described below. With regard to the parallelization, all these routines (except `U_collect_state`, `U_distribute_state`, and `U_next_observation`) are executed by the filter processes (`filterpe=.true.`) only.
 
 For completeness we discuss here all user-supplied routines that are specified in the interface to `PDAF_assimilate_lestkf`. Many of the routines are localized versions of those that are needed for the global ESTKF method. Hence, if the user-supplied routines for the global ESTKF have been already implemented, one can base on these routines to speed up the implementation. Due to this, it can also be reasonable to first fully implement a global filter version and subsequently implement the corresponding localized filter by modifying and extending the global routines.