Changes between Version 16 and Version 17 of ImplementAnalysisseik

Timestamp:

Sep 3, 2010, 3:48:55 PM (14 years ago)

Author:

lnerger

Comment:

--

ImplementAnalysisseik

@@ -24 +24 @@
 For the analysis step of the SEIK filter 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_put_state_seik` that was discussed before. With regard to the parallelization, all these routines are executed by the filter processes (`filterpe=1`) only.
 
-The user-supplied routines for the SEIK filter are 
+For completeness we discuss here all user-supplied routines that are specified in the interface to PDAF_put_state_seik. Thus, some of the user-supplied that are explained on the page explaining the modification of the model code for the ensemble integration are repeated here.
+
+== `PDAF_put_state_seik` ==
+
+The general espects of the filter specific routines `PDAF_put_state_*` have been described on the page [ModifyModelforEnsembleIntegration Modification of the model core for the ensemble integration]. Here, we list once more the full interface. Subsequently, the full set of user-supplied routines specified in the call to `PDAF_put_state_seik` is explained.
+
+The interface when using the SEIK filter is the following:
+{{{
+  SUBROUTINE PDAF_put_state_seik(U_collect_state, U_init_dim_obs, U_obs_op, &
+                                 U_init_obs, U_prepoststep, U_prodRinvA, U_init_obsvar, status)
+}}}
+with the following arguments:
+ * [#U_collect_statecollect_state.F90 U_collect_state]: The name of the user-supplied routine that initializes a state vector from the array holding the ensembel of model states from the model fields. This is basically the inverse operation to `U_distribute_state` used in `PDAF_get_state`
  * [#U_init_dim_obsinit_dim_obs.F90 U_init_dim_obs]: The name of the user-supplied routine that provides the size of observation vector
  * [#U_obs_opobs_op.F90 U_obs_op]: The name of the user-supplied routine that acts as the observation operator on some state vector
  * [#U_init_obsinit_obs.F90 U_init_obs]: The name of the user-supplied routine that initializes the vector of observations
+ * [#U_prepoststepprepoststep_seik.F90 U_prepoststep]: The name of the pre/poststep routine as in `PDAF_get_state`
  * [#U_prodRinvAprodrinva.F90 U_prodRinvA]: The name of the user-supplied routine that computes the product of the inverse of the observation error covariance matrix with some matrix provided to the routine by PDAF. This operation occurs during the analysis step of the SEIK filter.
  * [#U_init_obsvarinit_obsvar.F90 U_init_obsvar]: The name of the user-supplied routine that provides a mean observation error variance to PDAF (This routine will only be executed, if an adaptive forgetting factor is used)
+ * `status`: The integer status flag. It is zero, if `PDAF_put_state_seik` is exited without errors.
 
-Below the names of the corresponding routines in the template directory are provided in parentheses. The the routines in the example implementation have the same name but include '`_dummy_D`' in the name.
 
-== `U_init_dim_obs` (init_dim_obs.F90) ==
+== User-supplied routines ==
+
+Here all user-supplied routines are described that are required in the call to `PDAF_put_state_seik`. For some of the generic routines, we link to the page on [ModifyModelforEnsembleIntegration modifying the model code for the ensemble integration].
+
+To indicate user-supplied routines we use the prefix `U_`. In the template directory `templates/` these routines are provided in files with the routines name without this prefix. In the example implementation in `testsuite/src/dummymodel_1D` the routines exist without the prefix, but with the extension `_dummy_D.F90`. In the section titles below we provide the name of the template file in parentheses.
+
+
+=== `U_collect_state` (collect_state.F90) ===
+
+This routine is independent from the filter algorithm used.
+See [ModifyModelforEnsembleIntegration#U_collect_statecollect_state.F90 here] for the description of this routine.
+
+
+=== `U_init_dim_obs` (init_dim_obs.F90) ===
 
 This routine is used by all global filter algorithms (SEEK, SEIK, EnKF, ETKF).
@@ -50 +76 @@
  * It can be useful to not only determine the size of the observation vector is determined at this point. One can also already gather information about the locations of the observations, which will be used later, e.g. to implement the observation operator. An array for the locations can be defined in a module like `mod_assimilation`.
 
-== `U_obs_op` (obs_op.F90) ==
+
+=== `U_obs_op` (obs_op.F90) ===
 
 This routine is used by all global filter algorithms (SEEK, SEIK, EnKF, ETKF).
@@ -72 +99 @@
  * If the observation operator involves a global operation, e.g. some global integration, while using domain-decompostion one has to gather the information from the other model domains using MPI communication. 
 
-== `U_init_obs` (init_obs.F90) ==
+
+=== `U_init_obs` (init_obs.F90) ===
 
 This routine is used by all global filter algorithms (SEEK, SEIK, EnKF, ETKF).
@@ -91 +119 @@
 
 
-== `U_prodRinvA` (prodrinva.F90) ==
+=== `U_prepoststep` (prepoststep_seik.F90) ===
+ 
+See [ModifyModelforEnsembleIntegration#U_prepoststepprepoststep_seik.F90 here] for the description of this routine.
+
+
+=== `U_prodRinvA` (prodrinva.F90) ===
 
 This routine is used by all filters whose algorithm uses the inverse of the observation error covariance matrix (SEEK, SEIK, and ETKF).
@@ -116 +149 @@
 
 
-
-== `U_init_obsvar` (init_obsvar.F90) ==
+=== `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).
@@ -139 +171 @@
  * 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.
+
+
+== Execution order of user-supplied routines ==
+
+For the SEIK filter, the user-supplied routines are essentially executed in the order they are listed in the interface to `PDAF_put_state_seik`. The order can be important as some routines can perform preparatory work for later routines. For example, `U_init_dim_obs` can prepare an index array that provides the information for executing the observation operator in `PDAF_obs_op`.
+
+Before the analysis step is called the following is executed:
+ 1. [#U_collect_statecollect_state.F90 U_collect_state]
+
+When the ensemble integration of the forecast is completed the analysis step is executed. During the analysis step the following routines are executed:
+ 1. [#U_prepoststepprepoststep_seik.F90 U_prepoststep] (call to handle the forecast, called with negative value of the time step)
+ 1. [#U_init_dim_obsinit_dim_obs.F90 U_init_dim_obs]
+ 1. [#U_obs_opobs_op.F90 U_obs_op] (One call to operate on the ensemble mean state)
+ 1. [#U_init_obsinit_obs.F90 U_init_obs]
+ 1. [#U_obs_opobs_op.F90 U_obs_op] (`dim_ens` calls; one call for each ensemble member)
+ 1. [#U_init_obsvarinit_obsvar.F90 U_init_obsvar] (Only executed, if the adaptive forgetting factor is used (`type_forget=1` in the example implemention))
+ 1. [#U_prodRinvAprodrinva.F90 U_prodRinvA]
+ 1. [#U_prepoststepprepoststep_seik.F90 U_prepoststep] (call to handle the analysis, called with (positive) value of the time step)
+