Changes between Version 3 and Version 4 of ImplementAnalysisENSRF_EAKF

Timestamp:

Mar 25, 2025, 7:55:11 AM (8 days ago)

Author:

lnerger

Comment:

--

ImplementAnalysisENSRF_EAKF

@@ -43 +43 @@
 == Overview ==
 
-The ENSRF and EAKF are ensemble Kalman filter variants using serial observation processing. The implementation follows Houtekamer and Mitchell (2002) for the ENSRF and Anderson (2003) for the EAKF variant using local least squares regression.
+The ENSRF and EAKF are ensemble Kalman filter variants using serial observation processing. The implementation follows Houtekamer and Hamill (2002) for the ENSRF and Anderson (2003) for the EAKF variant using local least squares regression. The variant of the serial-observation processing filter is selected by the `subtype` in the call to `PDAF_init` as follows:
+
+||= subtype =||= Filter variant =""
+||= 0 =|| ENSRF (Whitaker & Hamill, 2002) ||
+||= 1 =|| EAKF (Anderson, 2003) ||
 
 For the analysis step of the ENSRF and EAKF different 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. This procedure should simplify the implementation. The names of the required routines are specified in the call to the routine `PDAF_assimilate_ensrf` for the fully-parallel and flexible parallelization implementations (alternatively `PDAF_put_state_lenkf` for the 'flexible' implementation). With regard to the parallelization, all these routines are executed by the filter processes (`filterpe=.true.`) only.