Changes between Initial Version and Version 1 of ImplementAnalysisPDAF3_Hyb3DVar


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Timestamp:
May 26, 2025, 4:35:49 PM (6 days ago)
Author:
lnerger
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  • ImplementAnalysisPDAF3_Hyb3DVar

    v1 v1  
     1= Implementation of the Analysis Step of Hybrid 3D-Var  =
     2
     3{{{
     4#!html
     5<div class="wiki-toc">
     6<h4>Implementation Guide - Analysis Step</h4>
     7<ol><li>Implementing the analysis step</li>
     8<ol>
     9<li><b>Ensemble filters</b></li>
     10<ol>
     11<li> <a href="ImplementFilterAnalysisOverviewPDAF3"> General overview for ensemble filters</a></li>
     12<li><a href="ImplementAnalysisPDAF3Universal">Universal interface </a></li>
     13<li><a href="ImplementAnalysisPDAF3UniversalLocal">Universal interface using g2l/l2g_state</a></li>
     14<li><a href="ImplementanalysisPDAF3Gloval">Interface specific for global filters</a></li>
     15</ol>
     16<li><b>3D-Var methods</b></li>
     17<ol>
     18<li> <a href="Implement3DVarAnalysisOverviewPDAF3"> General overview for 3D-Var methods</a></li>
     19<li><a href="Implement3DVarAnalysisPDAF3Universal">Universal interface for 3D-Var</a></li>
     20<li><a href="Implement3DVarAnalysisPDAF3_3DVar">Implementation for 3D-Var</a></li>
     21<li><a href="Implement3DVarAnalysisPDAF3_3DEnVar">Implementation for 3D Ensemble Var</a></li>
     22<li><a href="Implement3DVarAnalysisPDAF3_Hyb3DVar">Implementation for Hybrid 3D-Var</a></li>
     23</ol>
     24
     25<li><a href="nondiagonal_observation_error_covariance_matrices_PDAF3">Using nondiagonal R-matrices</a></li>
     26<li><a href="PDAF_OMI_Overview">PDAF-OMI Overview</a></li>
     27</ol>
     28</div>
     29}}}
     30
     31
     32[[PageOutline(2-3,Contents of this page)]]
     33
     34== Overview ==
     35
     36This page describes the recommended implementation of the analysis step for the hybrid 3D-Var schemes using the PDAF3 interface of.
     37
     38|| The interface for hybrid 3D-Var using the localized LESTKF for the transformation is the universal interface. If one intends to implement particularly for the variant using the global filter ESTKF, there is a separate interface for this special case. ||
     39
     40For the analysis step of 3D-Var we need different operations related to the observations. These operations are requested by PDAF by call-back routines supplied by the user and provided in the OMI structure. The names of the routines that are provided by the user are specified in the call to the assimilation routines. With regard to the parallelization, all these routines (except `collect_state_pdaf`, `distribute_state_pdaf`, and `next_observation_pdaf`) are executed by the filter processes (`filterpe=.true.`) only.
     41
     42The different 3D-Var methods in PDAF were explained on the [wiki:Implement3DVarAnalysisOverview page providing the verview of the Analysis Step for 3D-Var Methods]. Depending the type of 3D-Var, the background covariance matrix '''B''' is represented either in a parameterized form, by an ensemble, or by a combination of both. The 3D-Var methods that use an ensemble need to transform the ensemble perturbations using an ensemble Kalman filter. PDAF uses for this the error-subspace transform filter ESTKF. There are two variants: The first uses the localized filter LESTKF, while the second uses the global filter ESTKF.
     43
     44For completeness we discuss here all user-supplied routines that are specified in the interface to `PDAFomi_assimilate_hyb3dvar_X`. Thus, some of the user-supplied routines that are explained on the page describing the modification of the model code for the ensemble integration are repeated here.
     45
     46
     47== Analysis Routines ==
     48
     49The general aspects of the filter (or solver) specific routines `PDAF_assimilate_*` have been described on the page [OnlineModifyModelforEnsembleIntegration_PDAF3 Modification of the model code for the ensemble integration]. Here, we list the full interface of the routine. Subsequently, the user-supplied routines specified in the call is explained.
     50
     51There are two variants that either compute the transformataion of the ensemble transformation using the local LESTKF method, or the global ESTKF.
     52
     53=== `PDAF3_assimilate_3dvar_all` ===
     54
     55This universal routine can be used for the hybrid 3D-Var in both variants, using the local LESTKF or the global ESTKF for the transformation of the ensemble perturbations.
     56
     57This routine is used both in the ''fully-parallel'' and the ''flexible'' implementation variants of the data assimilation system. (See the page [ModifyModelforEnsembleIntegration Modification of the model code for the ensemble integration] for these variants)
     58
     59The interface is:
     60{{{
     61SUBROUTINE PDAF3_assimilate_3dvar_all(collect_state_pdaf, distribute_state_pdaf, &
     62                                 init_dim_obs_pdafomi, obs_op_pdafomi, &
     63                                 cvt_ens_pdaf, cvt_adj_ens_pdaf, cvt_pdaf, cvt_adj_pdaf, &
     64                                 obs_op_lin_pdafomi, obs_op_adj_pdafomi, &
     65                                 init_n_domains_p_pdaf, init_dim_l_pdaf, init_dim_obs_l_pdafomi, &
     66                                 prepoststep_pdaf, next_observation_pdaf, outflag)
     67}}}
     68where all arguments, except the last one, are the names of call-back routines:
     69 * [#collect_state_pdafcollect_state_pdaf.F90 collect_state_pdaf]: The name of the user-supplied routine that initializes a state vector from the array holding the ensemble of model states from the model fields. This is basically the inverse operation to `distribute_state` used in `PDAF_init_forecast` as well as here.
     70 * [#distribute_state_pdafdistribute_state_pdaf.F90 distribute_state_pdaf]:  The name of a user supplied routine that initializes the model fields from the array holding the ensemble of model state vectors.
     71 * [#init_dim_obs_pdafomicallback_obs_pdafomi.F90 init_dim_obs_pdafomi]: The name of the user-supplied routine that initializes the observation information and provides the size of observation vector
     72 * [#obs_op_pdafomicallback_obs_pdafomi.F90 obs_op_pdafomi]: The name of the user-supplied routine that acts as the observation operator on some state vector
     73 * [#cvt_ens_pdafcvt_ens_pdaf.F90 cvt_ens_pdaf]: The name of the user-supplied routine that applies the ensemble control-vector transformation (square-root of the B-matrix) on some control vector to obtain a state vector.
     74 * [#cvt_adj_ens_pdafcvt_adj_ens_pdaf.F90 cvt_adj_ens_pdaf]: The name of the user-supplied routine that applies the adjoint ensemble control-vector transformation (with square-root of the B-matrix) on some state vector to obtain the control vector.
     75 * [#cvt_pdafcvt_pdaf.F90 cvt_pdaf]: The name of the user-supplied routine that applies the control-vector transformation (square-root of the B-matrix) on some control vector to obtain a state vector.
     76 * [#cvt_adj_pdafcvt_adj_pdaf.F90 cvt_adj_pdaf]: The name of the user-supplied routine that applies the adjoint control-vector transformation (with square-root of the B-matrix) on some state vector to obtain the control vector.
     77 * [#obs_op_pdafomicallback_obs_pdafomi.F90 obs_op_lin_pdafomi]: The name of the user-supplied routine that acts as the linearized observation operator on some state vector
     78 * [#obs_op_pdafomicallback_obs_pdafomi.F90 obs_op_lin_pdafomi]: The name of the user-supplied routine that acts as the adjoint observation operator on some state vector
     79 * [#init_n_domains_pdafinit_n_domains_pdaf.F90 init_n_domains_pdaf]: The name of the routine that provides the number of local analysis domains
     80 * [#init_dim_l_pdafinit_dim_l_pdaf.F90 init_dim_l_pdaf]: The name of the routine that provides the state dimension for a local analysis domain
     81 * [#init_dim_obs_l_pdafomicallback_obs_pdafomi.F90 init_dim_obs_l_pdafomi]: The name of the routine that initializes the size of the observation vector for a local analysis domain
     82 * [#prepoststep_pdafprepoststep_ens_pdaf.F90 prepoststep_pdaf]: The name of the pre/poststep routine as in `PDAF_init_forecast`
     83 * [#next_observation_pdafnext_observation.F90 next_observation_pdaf]: The name of a user supplied routine that initializes the variables `nsteps`, `timenow`, and `doexit`. The same routine is also used in `PDAF_init_forecast`.
     84 * `status`: The integer status flag. It is zero, if the routine is exited without errors.
     85
     86=== `PDAF3_assim_offline_3dvar_all` ===
     87
     88For the offline mode of PDAF, the routine `PDAF3_assim_offline_3dvar_all` is used to perform the analysis step.
     89The interface of the routine is identical with that of `PDAF3_assimilate_3dvar_all`, except that the user-supplied routines `U_distribute_state`, `U_collect_state` and `U_next_observation` are missing.
     90
     91The interface when using one of the global filters is the following:
     92{{{
     93  SUBROUTINE PDAF3_assim_offline_3dvar_all(&
     94                                 U_init_dim_obs_pdafomi, U_obs_op_pdafomi, &
     95                                 U_cvt_ens, U_cvt_adj_ens, U_cvt, U_cvt_adj, &
     96                                 U_obs_op_lin_pdafomi, U_obs_op_adj_pdafomi, &
     97                                 U_init_n_domains_p, U_init_dim_l, U_init_dim_obs_l_pdafomi, &
     98                                 U_prepoststep, outflag)
     99}}}
     100
     101=== `PDAF3_put_state_3dvar_all` ===
     102
     103This routine exists for backward-compatibility. In implementations that were done before the release of PDAF V3.0, a 'put_state' routine was used for the `flexible` parallelization variant and for the offline mode.
     104When the 'flexible' implementation variant is chosen for the assimilation system, the routine. The routine `PDAF3_put_state_3dvar_all` allows to port such implemnetations to the PDAF3 interface with minimal changes.
     105The interface of the routine is identical with that of `PDAF3_assimilate_3dvar_all`, except that the user-supplied routines `U_distribute_state` and `U_next_observation` are missing.
     106
     107The interface when using one of the global filters is the following:
     108{{{
     109  SUBROUTINE PDAF3_put_state_3dvar_all(U_collect_state, &
     110                                 U_init_dim_obs_pdafomi, U_obs_op_pdafomi, &
     111                                 U_cvt_ens, U_cvt_adj_ens, U_cvt, U_cvt_adj, &
     112                                 U_obs_op_lin_pdafomi, U_obs_op_adj_pdafomi, &
     113                                 U_init_n_domains_p, U_init_dim_l, U_init_dim_obs_l_pdafomi, &
     114                                 U_prepoststep, outflag)
     115}}}
     116
     117
     118== Analysis Routines specific for using global ESTKF ==
     119
     120=== `PDAF3_assimilate_hyb3dvar_estkf` ===
     121
     122This routine is particular for the ESTKF. One can use it if one exclusively uses the global filter. In the argument list of this routine, the call-back routine for localization are not present and hence the argument list is shorter than that of `PDAF3_assimilate_3dvar_all`.
     123 
     124This routine is used both in the ''fully-parallel'' and the ''flexible'' implementation variants of the data assimilation system. (See the page [ModifyModelforEnsembleIntegration Modification of the model code for the ensemble integration] for these variants)
     125
     126The interface is:
     127{{{
     128SUBROUTINE PDAF3_assimilate_hyb3dvar_estkf(collect_state_pdaf, distribute_state_pdaf, &
     129                                 init_dim_obs_pdafomi, obs_op_pdafomi, &
     130                                 cvt_ens_pdaf, cvt_adj_ens_pdaf, cvt_pdaf, cvt_adj_pdaf, &
     131                                 obs_op_lin_pdafomi, obs_op_adj_pdafomi, &
     132                                 prepoststep_pdaf, next_observation_pdaf, outflag)
     133}}}
     134where all arguments, except the last one, are the names of call-back routines. See the description of the arguments for `PDAF3_assimilate_3dvar_all`.
     135
     136
     137
     138=== `PDAF3_assim_offline_hyb3dvar_estkf` ===
     139
     140This routine is particular for the ESTKF. One can use it if one exclusively uses the global filter. In the argument list of this routine, the call-back routine for localization are not present and hence the argument list is shorter than that of `PDAF3_assim_offline_3dvar_all`.
     141
     142This routine is used to perform the analysis step for the offline mode.
     143The interface of the routine is identical with that of `PDAF3_assimilate_hyb3dvar_estkf`, except that the user-supplied routines `U_distribute_state`, `U_collect_state` and `U_next_observation` are missing.
     144
     145The interface is:
     146{{{
     147SUBROUTINE PDAF3_assimilate_hyb3dvar_estkf(&
     148                                 init_dim_obs_pdafomi, obs_op_pdafomi, &
     149                                 cvt_ens_pdaf, cvt_adj_ens_pdaf, cvt_pdaf, cvt_adj_pdaf, &
     150                                 obs_op_lin_pdafomi, obs_op_adj_pdafomi, &
     151                                 prepoststep_pdaf, outflag)
     152}}}
     153where all arguments, except the last one, are the names of call-back routines. See the description of the arguments for `PDAF3_assimilate_3dvar_all`.
     154
     155
     156
     157=== `PDAF3_put_state_hyb3dvar_estkf` ===
     158
     159This routine exists for backward-compatibility. In implementations that were done before the release of PDAF V3.0, a 'put_state' routine was used for the `flexible` parallelization variant and for the offline mode.
     160When the 'flexible' implementation variant is chosen for the assimilation system, the routine. The routine `PDAF3_put_state_hyb3dvar_estkf` allows to port such implemnetations to the PDAF3 interface with minimal changes.
     161The interface of the routine is identical with that of `PDAF3_assimilate_hyb3dvar_estkf`, except that the user-supplied routines `U_distribute_state` and `U_next_observation` are missing.
     162
     163This routine is particular for the ESTKF. One can use it if one exclusively uses the global filter. In the argument list of this routine, the call-back routine for localization are not present and hence the argument list is shorter than that of `PDAF3_put_state_3dvar_all`.
     164
     165The interface is:
     166{{{
     167SUBROUTINE PDAF3_assimilate_hyb3dvar_estkf(collect_state_pdaf, &
     168                                 init_dim_obs_pdafomi, obs_op_pdafomi, &
     169                                 cvt_ens_pdaf, cvt_adj_ens_pdaf, cvt_pdaf, cvt_adj_pdaf, &
     170                                 obs_op_lin_pdafomi, obs_op_adj_pdafomi, &
     171                                 prepoststep_pdaf, outflag)
     172}}}
     173where all arguments, except the last one, are the names of call-back routines. See the description of the arguments for `PDAF3_assimilate_3dvar_all`.
     174
     175
     176
     177
     178== User-supplied routines ==
     179
     180Here all user-supplied routines are described that are required in the call to the assimilation routines for hybrid 3D-Var. For some of the generic routines, we link to the page on [wiki:OnlineModifyModelforEnsembleIntegration_PDAF3 modifying the model code for the ensemble integration].
     181
     182To indicate user-supplied routines we use the prefix `U_`. In the template directory `templates/` as well as in the tutorial implementations in `tutorial/` these routines exist without the prefix, but with the extension `_pdaf.F90`. The user-routines relating to OMI are collected in the file `callback_obs_pdafomi.F90`. In the section titles below we provide the name of the template file in parentheses.
     183
     184In the subroutine interfaces some variables appear with the suffix `_p`. This suffix indicates that the variable is particular to a model sub-domain, if a domain decomposed model is used. Thus, the value(s) in the variable will be different for different model sub-domains.
     185
     186
     187=== `collect_state_pdaf` (collect_state_pdaf.F90) ===
     188
     189This routine is independent of the filter algorithm used.
     190
     191See the page on [ModifyModelforEnsembleIntegration#collect_state_pdafcollect_state_pdaf.F90 modifying the model code for the ensemble integration] for the description of this routine.
     192
     193=== `distribute_state_pdaf` (distribute_state_pdaf.F90) ===
     194
     195This routine is independent of the filter algorithm used.
     196
     197See the page on [ModifyModelforEnsembleIntegration#distribute_state_pdafdistribute_state_pdaf.F90 modifying the model code for the ensemble integration] for the description of this routine.
     198
     199
     200
     201=== `init_dim_obs_pdafomi` (callback_obs_pdafomi.F90) ===
     202
     203This is a call-back routine initializing the observation information. The routine just calls a routine from the observation module for each observation type.
     204
     205See the [wiki:OMI_Callback_obs_pdafomi documentation on callback_obs_pdafomi.F90] for more information.
     206
     207
     208
     209=== `obs_op_pdafomi` (callback_obs_pdafomi.F90) ===
     210
     211This is a call-back routine applying the observation operator to the state vector. The routine calls a routine from the observation module for each observation type.
     212
     213See the [wiki:OMI_Callback_obs_pdafomi documentation on callback_obs_pdafomi.F90] for more information.
     214
     215
     216
     217=== `cvt_ens_pdaf` (cvt_ens_pdaf.F90) ===
     218
     219The interface for this routine is:
     220{{{
     221SUBROUTINE cvt_ens_pdaf(iter, dim_p, dim_ens, dim_cv_ens_p, ens_p, cv_p, Vcv_p)
     222
     223  INTEGER, INTENT(in) :: iter               ! Iteration of optimization
     224  INTEGER, INTENT(in) :: dim_p              ! PE-local observation dimension
     225  INTEGER, INTENT(in) :: dim_ens            ! Ensemble size
     226  INTEGER, INTENT(in) :: dim_cv_ens_p       ! Dimension of control vector
     227  REAL, INTENT(in) :: ens_p(dim_p, dim_ens) ! PE-local ensemble
     228  REAL, INTENT(in) :: cv_p(dim_cv_ens_p)    ! PE-local control vector
     229  REAL, INTENT(inout) :: Vcv_p(dim_p)       ! PE-local state increment
     230}}}
     231
     232The routine is called during the analysis step during the iterative minimization of the cost function.
     233It has to apply the control vector transformation to the control vector and return the transformed result vector. Usually this transformation is the multiplication with the square-root of the background error covariance matrix '''B'''. For the 3D Ensemble Var, this square root is usually expressed through the ensemble.
     234
     235If the control vector is decomposed in case of parallelization it first needs to the gathered on each processor and afterwards the transformation is computed on the potentially domain-decomposed state vector.
     236
     237
     238=== `cvt_adj_pdaf` (cvt_adj_pdaf.F90) ===
     239
     240The interface for this routine is:
     241{{{
     242SUBROUTINE cvt_adj_ens_pdaf(iter, dim_p, dim_ens, dim_cv_ens_p, ens_p, Vcv_p, cv_p)
     243
     244  INTEGER, INTENT(in) :: iter                ! Iteration of optimization
     245  INTEGER, INTENT(in) :: dim_p               ! PE-local observation dimension
     246  INTEGER, INTENT(in) :: dim_ens             ! Ensemble size
     247  INTEGER, INTENT(in) :: dim_cv_ens_p        ! PE-local dimension of control vector
     248  REAL, INTENT(in) :: ens_p(dim_p, dim_ens)  ! PE-local ensemble
     249  REAL, INTENT(in)    :: Vcv_p(dim_p)        ! PE-local input vector
     250  REAL, INTENT(inout) :: cv_p(dim_cv_ens_p)  ! PE-local result vector
     251}}}
     252
     253The routine is called during the analysis step during the iterative minimization of the cost function.
     254It has to apply the adjoint control vector transformation to a state vector and return the control vector. Usually this transformation is the multiplication with transpose of the square-root of the background error covariance matrix '''B'''. or the 3D Ensemble Var, this square root is usually expressed through the ensemble.
     255
     256If the state vector is decomposed in case of parallelization one needs to take care that the application of the trasformation is complete. This usually requries a comminucation with MPI_Allreduce to obtain a global sun.
     257
     258
     259
     260=== `cvt_pdaf` (cvt_pdaf.F90) ===
     261
     262The interface for this routine is:
     263{{{
     264SUBROUTINE cvt_pdaf(iter, dim_p, dim_cvec, cv_p, Vv_p)
     265
     266  INTEGER, INTENT(in) :: iter           ! Iteration of optimization
     267  INTEGER, INTENT(in) :: dim_p          ! PE-local observation dimension
     268  INTEGER, INTENT(in) :: dim_cvec       ! Dimension of control vector
     269  REAL, INTENT(in)    :: cv_p(dim_cvec) ! PE-local control vector
     270  REAL, INTENT(inout) :: Vv_p(dim_p)    ! PE-local result vector (state vector increment)
     271}}}
     272
     273The routine is called during the analysis step during the iterative minimization of the cost function.
     274It has to apply the control vector transformation to the control vector and return the transformed result vector. Usually this transformation is the multiplication with the square-root of the background error covariance matrix '''B'''.
     275
     276If the control vector is decomposed in case of parallelization it first needs to the gathered on each processor and afterwards the transformation is computed on the potentially domain-decomposed state vector.
     277
     278
     279=== `cvt_adj_pdaf` (cvt_adj_pdaf.F90) ===
     280
     281The interface for this routine is:
     282{{{
     283SUBROUTINE cvt_adj_pdaf(iter, dim_p, dim_cvec, Vv_p, cv_p)
     284
     285  INTEGER, INTENT(in) :: iter           ! Iteration of optimization
     286  INTEGER, INTENT(in) :: dim_p          ! PE-local observation dimension
     287  INTEGER, INTENT(in) :: dim_cvec       ! Dimension of control vector
     288  REAL, INTENT(in)    :: Vv_p(dim_p)    ! PE-local result vector (state vector increment)
     289  REAL, INTENT(inout) :: cv_p(dim_cvec) ! PE-local control vector
     290}}}
     291
     292The routine is called during the analysis step during the iterative minimization of the cost function.
     293It has to apply the adjoint control vector transformation to a state vector and return the control vector. Usually this transformation is the multiplication with transposed of the square-root of the background error covariance matrix '''B'''.
     294
     295If the state vector is decomposed in case of parallelization one needs to take care that the application of the trasformation is complete. This usually requries a comminucation with MPI_Allreduce to obtain a global sun.
     296
     297
     298
     299
     300=== `obs_op_lin_pdafomi` (callback_obs_pdafomi.F90) ===
     301
     302This is a call-back routine for PDAF-OMI applying the linearized observation operator to the state vector. The routine calls a routine from the observation module for each observation type. If the full observation operator is lineaer the same operator can be used here.
     303
     304See the [wiki:OMI_Callback_obs_pdafomi documentation on callback_obs_pdafomi.F90] for more information.
     305
     306
     307=== `obs_op_adj_pdafomi` (callback_obs_pdafomi.F90) ===
     308
     309This is a call-back routine for PDAF-OMI applying the adjoint observation operator to some vector inthe observation space. The routine calls a routine from the observation module for each observation type.
     310
     311See the [wiki:OMI_Callback_obs_pdafomi documentation on callback_obs_pdafomi.F90] for more information.
     312
     313
     314
     315=== `init_n_domains_pdaf` (init_n_domains_pdaf.F90) ===
     316
     317This routine is only used for localization. It is called during the analysis step before the loop over the local analysis domains is entered. It has to provide the number of local analysis domains. In case of a domain-decomposed model, the number of local analysis domain for the model sub-domain of the calling process has to be initialized.
     318
     319The interface for this routine is:
     320{{{
     321SUBROUTINE init_n_domains_pdaf(step, n_domains_p)
     322
     323  INTEGER, INTENT(in)  :: step        ! Current time step
     324  INTEGER, INTENT(out) :: n_domains_p ! Number of analysis domains for local model sub-domain
     325}}}
     326
     327Hints:
     328 * As a simple case, if the localization is only performed horizontally, the local analysis domains can be single vertical columns of the model grid. In this case, `n_domains_p` is simply the number of vertical columns in the process-local model sub-domain.
     329
     330
     331=== `init_dim_l_pdaf` (init_dim_l_pdaf.F90) ===
     332
     333This routine is only used for localization.
     334
     335The interface for this routine is:
     336{{{
     337SUBROUTINE init_dim_l_pdaf(step, domain_p, dim_l)
     338
     339  INTEGER, INTENT(in)  :: step        ! Current time step
     340  INTEGER, INTENT(in)  :: domain_p    ! Current local analysis domain
     341  INTEGER, INTENT(out) :: dim_l       ! Local state dimension
     342}}}
     343
     344The routine is called during the loop over the local analysis domains in the analysis step.
     345
     346It provides in `dim_l` the dimension of the state vector for the local analysis domain with index `domain_p` to PDAF.
     347
     348In the recommended implementation shown in the tutorial and template codes, there are two further initializations:
     3491. The routine has initialize the index array `id_lstate_in_pstate` containing the indices of the elements of the local state vector in the global (or domain-decomposed) state vector. Then it has to provide this array to PDAF by calling `PDAFlocal_set_indices` (see below).
     3502. The routine initializes an array `coords_l` containing the coordinates of the local analysis domain. This is shared with `U_init_dim_obs_l_pdafomi` via the module `mod_assimilation`.
     351
     352Hints:
     353  * The coordinates in `coords_l` have to describe one location in space that is used for localization to compute the distance from observations.
     354  * The coordinates in `coords_l` have the same units as those used for the observations
     355  * For geographic distance computations, the unit of the coordinates needs to be radian, thus (0, 2*pi) or (-pi,pi) for longitude and (-pi/2, pi/2) for latitude.
     356 * Any form of local domain is possible as long as it can be describe as a single location.
     357  * If the local domain is a single grid point, `dim_l` will be the number of model variables at this grid point.
     358  * The local analysis domain can also be a single vertical column of the model grid if observations are only horizontally distributed (a common situation with satellite data in the ocean).
     359   * In this case, `dim_l` will be the number of vertical grid points at this location times the number of model fields that exist in the vertical, plus possible variables at e.g. the surface.
     360   * In this case only the horizontal coordinates are used in `coords_l`.
     361
     362The index array `id_lstate_in_pstate` is an integer array in form of a one-dimensional vector. One initializes this vector by determining the indices of the elements of the local state vector in the global, or domain decomposed, state vector. After initializing `id_lstate_in_pstate`, one has to provided it to PDAF by calling `PDAFlocal_set_indices'. The interface interface is:
     363
     364{{{
     365SUBROUTINE PDAFlocal_set_indices(dim_l, id_lstate_in_pstate)
     366
     367  INTEGER, INTENT(in) :: dim_l                          ! Dimension of local state vector
     368  INTEGER, INTENT(in) :: id_lstate_in_pstate(dim_l)     ! Index array for mapping
     369}}}
     370
     371Hint for `id_lstate_in_pstate`:
     372 * The initialization of the index vector `id_lstate_to_pstate` is analogous to a loop that directly performs the initialization of a local state vector. However, here only the indices are stored.
     373 * See the [wiki:PDAFlocal_overview PDAFlocal overview page] for more information on the functionality of PDAFlocal.
     374
     375
     376=== `init_dim_obs_l_pdafomi` (callback_obs_pdafomi.F90) ===
     377
     378This routine is only used for localization. It is a call-back routine for PDAF-OMI that initializes the local observation vector. The routine calls a routine from the observation module for each observation type.
     379
     380See the [wiki:OMI_Callback_obs_pdafomi documentation on callback_obs_pdafomi.F90] for more information.
     381
     382
     383=== `prepoststep_pdaf` (prepoststep_ens_pdaf.F90) ===
     384
     385The routine has already been described for modifying the model for the ensemble integration and for inserting the analysis step.
     386
     387See the page on [ModifyModelforEnsembleIntegration#distribute_state_pdafdistribute_state_pdaf.F90 modifying the model code for the ensemble integration] for the description of this routine.
     388
     389
     390=== `next_observation_pdaf` (next_observation_pdaf.F90) ===
     391
     392This routine is independent of the filter algorithm used.
     393
     394See the page on [ModifyModelforEnsembleIntegration#distribute_state_pdafdistribute_state_pdaf.F90 modifying the model code for the ensemble integration] for the description of this routine.
     395
     396== Execution order of user-supplied routines ==
     397
     398The user-supplied routines are executed in the order listed below.  The order can be important as some routines can perform preparatory work for later routines. For example, `init_dim_obs_pdafomi` prepares an index array that provides the information for executing the observation operator in `obs_op_pdafomi`. How this information is initialized is described in the documentation of OMI.
     399
     400Before the analysis step is called the following routine is executed:
     401 1. [#collect_state_pdafcollect_state_pdaf.F90 collect_state_pdaf]
     402
     403The analysis step is executed when the ensemble integration of the forecast is completed. During the analysis step the following routines are executed in the given order:
     404 1. [#prepoststep_pdafprepoststep_ens_pdaf.F90 prepoststep_pdaf] (Call to act on the forecast ensemble, called with negative value of the time step)
     405 1. [#init_dim_obs_pdafomicallback_obs_pdafomi.F90 init_dim_obs_pdafomi]
     406 1. [#obs_op_pdafomicallback_obs_pdafomi.F90 obs_op_pdafomi] (multiple calls, one for each ensemble member)
     407
     408Inside the analysis step the interative optimization is computed. This involves the repeated call of the routines:
     409 1. [#cvt_pdafcvt_pdaf.F90 cvt_pdaf]
     410 1. [#cvt_ens_pdafcvt_ens_pdaf.F90 cvt_ens_pdaf]
     411 1. [#obs_op_lin_pdafomicallback_obs_pdafomi.F90 U_obs_op_lin_pdafomi]
     412 1. [#obs_op_adj_pdafomicallback_obs_pdafomi.F90 U_obs_op_adj_pdafomi]
     413 1. [#cvt_adj_pdafcvt_adj_pdaf.F90 cvt_adj_pdaf]
     414 1. [#cvt_adj_ens_pdafcvt_adj_ens_pdaf.F90 cvt_adj_ens_pdaf]
     415
     416After the iterative optimization the following routines are executes to complte the analysis step:
     417 1. [#cvt_enscvt_pdaf.F90 U_cvt] (Call to the parameterized part of the control vector transform to compute the final state vector increment)
     418 1. [#cvt_enscvt_ens_pdaf.F90 U_cvt_ens] (Call to the eensemble-part of the control vector transform to compute the final state vector increment)
     419 1. [#prepoststepprepoststep_ens_pdaf.F90 U_prepoststep] (Call to act on the analysis ensemble, called with (positive) value of the time step)
     420
     421The iterative optimization abovve computes an updated ensemble mean state. Subsequently, the ensemble perturbations are updated using the LESTKF or ESTKF. The execution of the routines for these filters is described on the [wiki:ImplementAnalysisPDAF3Universal page on implementing the local filter analysis step] .
     422
     423In case of the routine `PDAF3_assimilate_3dvar_all`, the following routines are executed after the analysis step:
     424 1. [#distribute_state_pdafdistribute_state_pdaf.F90 distribute_state_pdaf]
     425 1. [#next_observation_pdafnext_observation_pdaf.F90 next_observation_pdaf]