Changes between Initial Version and Version 1 of ImplementAnalysispf


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Timestamp:
Jul 4, 2019, 11:40:26 AM (5 years ago)
Author:
lnerger
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  • ImplementAnalysispf

    v1 v1  
     1= Implementation of the Analysis step for the PF (Particle Filter) algorithm =
     2
     3{{{
     4#!html
     5<div class="wiki-toc">
     6<h4>Implementation Guide</h4>
     7<ol><li><a href="ImplementationGuide">Main page</a></li>
     8<li><a href="AdaptParallelization">Adaptation of the parallelization</a></li>
     9<li><a href="InitPdaf">Initialization of PDAF</a></li>
     10<li><a href="ModifyModelforEnsembleIntegration">Modifications for ensemble integration</a></li>
     11<li><a href="ImplementationofAnalysisStep">Implementation of the analysis step</a></li>
     12<ol>
     13<li><a href="ImplementAnalysisestkf">Implementation for ESTKF</a></li>
     14<li><a href="ImplementAnalysislestkf">Implementation for LESTKF</a></li>
     15<li><a href="ImplementAnalysisetkf">Implementation for ETKF</a></li>
     16<li><a href="ImplementAnalysisletkf">Implementation for LETKF</a></li>
     17<li><a href="ImplementAnalysisseik">Implementation for SEIK</a></li>
     18<li><a href="ImplementAnalysislseik">Implementation for LSEIK</a></li>
     19<li><a href="ImplementAnalysisseek">Implementation for SEEK</a></li>
     20<li><a href="ImplementAnalysisenkf">Implementation for EnKF</a></li>
     21<li><a href="ImplementAnalysislenkf">Implementation for LEnKF</a></li>
     22<li><a href="ImplementAnalysisnetf">Implementation for NETF</a></li>
     23<li>Implementation for PF</li>
     24<li><a href="ImplementAnalysislnetf">Implementation for LNETF</a></li>
     25</ol>
     26<li><a href="AddingMemoryandTimingInformation">Memory and timing information</a></li>
     27<li><a href="EnsembleGeneration">Ensemble Generation</a></li>
     28<li><a href="DataAssimilationDiagnostics">Diagnostics</a></li>
     29</ol>
     30</div>
     31}}}
     32
     33[[PageOutline(2-3,Contents of this page)]]
     34
     35The PF algorithm was added with Version 1.14 of PDAF.
     36
     37== Overview ==
     38
     39For the analysis step of the PF, 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_pf` in the fully-parallel implementation (or `PDAF_put_state_pf` for the 'flexible' implementation) that was discussed before. With regard to the parallelization, all these routines are executed by the filter processes (`filterpe=.true.`) only.
     40
     41For completeness we discuss here all user-supplied routines that are specified in the interface to `PDAF_assimilate_pf`. Thus, some of the user-supplied routines that are explained on the page explaining the modification of the model code for the ensemble integration are repeated here.
     42
     43The analysis step of the PF is is wide parts similar to that of filters like ETKF, and ESTKF filters and strongly related to the NETF method. For this reason, the interface to the user-supplied routines is almost identical, and in fact identical to the NETF. Depending on the implementation it can be possible to use identical routines for the PF and the ETKF with the exception of the routine `U_likelihood`. Differences are marked in the text below. However, the NETF and PF have the same interface, but there are some different options that can be set when PDAF_init is called.
     44
     45== `PDAF_assimilate_pf` ==
     46
     47The general aspects of the filter-specific routines `PDAF_assimilate_*` have been described on the page [ModifyModelforEnsembleIntegration Modification of the model code for the ensemble integration] and its sub-page on [InsertAnalysisStep inserting the analysis step]. The routine is used in the fully-parallel implementation variant of the data assimilation system. When the 'flexible' implementation variant is used, the routines `PDAF_put_state_*' is used as described further below. Here, we list once more the full interface. Subsequently, the full set of user-supplied routines specified in the call to `PDAF_assimilate_pf` is explained.
     48
     49The interface when using the PF method is the following:
     50{{{
     51  SUBROUTINE PDAF_assimilate_pf(U_collect_state, U_distribute_state, U_init_dim_obs, &
     52                                 U_obs_op, U_init_obs, U_prepoststep, U_likelihood, &
     53                                 U_next_observation, status)
     54}}}
     55with the following arguments:
     56 * [#U_collect_statecollect_state_pdaf.F90 U_collect_state]: 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 `U_distribute_state` used in `PDAF_get_state` as well as here.
     57 * [#U_distribute_statedistribute_state_pdaf.F90 U_distribute_state]:  The name of a user supplied routine that initializes the model fields from the array holding the ensemble of model state vectors.
     58 * [#U_init_dim_obsinit_dim_obs_pdaf.F90 U_init_dim_obs]: The name of the user-supplied routine that provides the size of observation vector
     59 * [#U_obs_opobs_op_pdaf.F90 U_obs_op]: The name of the user-supplied routine that acts as the observation operator on some state vector
     60 * [#U_init_obsinit_obs_pdaf.F90 U_init_obs]: The name of the user-supplied routine that initializes the vector of observations
     61 * [#U_prepoststepprepoststep_ens_pdaf.F90 U_prepoststep]: The name of the pre/poststep routine as in `PDAF_get_state`
     62 * [#U_likelihoodlikelihood_pdaf.F90 U_likelihood]: The name of the user-supplied routine that computes the likelihood of the observations for an ensemble member provide when the routine is called.
     63 * [#U_next_observationnext_observation_pdaf.F90 U_next_observation]: The name of a user supplied routine that initializes the variables `nsteps`, `timenow`, and `doexit`. The same routine is also used in `PDAF_get_state`.
     64 * `status`: The integer status flag. It is zero, if `PDAF_assimilate_pf` is exited without errors.
     65
     66
     67== `PDAF_put_state_pf` ==
     68
     69When the 'flexible' implementation variant is chosen for the assimilation system, the routine `PDAF_put_state_pf` has to be used instead of `PDAF_assimilate_pf`. The general aspects of the filter specific routines `PDAF_put_state_*` have been described on the page [ModifyModelforEnsembleIntegration Modification of the model code for the ensemble integration]. The interface of the routine is identical with that of `PDAF_assimilate_pf` with the exception of the specification of the user-supplied routines `U_distribute_state` and `U_next_observation` are missing.
     70
     71The interface when using the PF method is the following:
     72{{{
     73  SUBROUTINE PDAF_put_state_pf(U_collect_state, U_init_dim_obs, U_obs_op, &
     74                                 U_init_obs, U_prepoststep, U_likelihood, status)
     75}}}
     76
     77
     78== User-supplied routines ==
     79
     80Here, all user-supplied routines are described that are required in the call to `PDAF_assimilate_pf`. For some of the generic routines, we link to the page on [ModifyModelforEnsembleIntegration modifying the model code for the ensemble integration].
     81
     82To indicate user-supplied routines we use the prefix `U_`. In the template directory `templates/` as well as in the example implementation in `testsuite/src/dummymodel_1D` these routines exist without the prefix, but with the extension `_pdaf.F90`. In the section titles below we provide the name of the template file in parentheses.
     83
     84In 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.
     85
     86
     87=== `U_collect_state` (collect_state_pdaf.F90) ===
     88
     89This routine is independent of the filter algorithm used.
     90See the page on [InsertAnalysisStep#U_collect_statecollect_state_pdaf.F90 inserting the analysis step] for the description of this routine.
     91
     92
     93=== `U_distribute_state` (distribute_state_pdaf.F90) ===
     94
     95This routine is independent of the filter algorithm used.
     96See the page on [InsertAnalysisStep#U_distribute_statedistribute_state_pdaf.F90 inserting the analysis step] for the description of this routine.
     97
     98
     99=== `U_init_dim_obs` (init_dim_obs_pdaf.F90) ===
     100
     101This routine is used by all global filter algorithms (SEEK, SEIK, EnKF, ETKF, NETF, PF).
     102
     103The interface for this routine is:
     104{{{
     105SUBROUTINE init_dim_obs(step, dim_obs_p)
     106
     107  INTEGER, INTENT(in)  :: step       ! Current time step
     108  INTEGER, INTENT(out) :: dim_obs_p  ! Dimension of observation vector
     109}}}
     110
     111The routine is called at the beginning of each analysis step.  It has to initialize the size `dim_obs_p` of the observation vector according to the current time step. Without parallelization `dim_obs_p` will be the size for the full model domain. When a domain-decomposed model is used, `dim_obs_p` will be the size of the observation vector for the sub-domain of the calling process.
     112
     113Some hints:
     114 * It can be useful to not only determine the size of the observation vector 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` of the example implementation.
     115
     116
     117=== `U_obs_op` (obs_op_pdaf.F90) ===
     118
     119This routine is used by all global filter algorithms (SEEK, SEIK, EnKF, ETKF, NETF, PF).
     120
     121The interface for this routine is:
     122{{{
     123SUBROUTINE obs_op(step, dim_p, dim_obs_p, state_p, m_state_p)
     124
     125  INTEGER, INTENT(in) :: step               ! Current time step
     126  INTEGER, INTENT(in) :: dim_p              ! PE-local dimension of state
     127  INTEGER, INTENT(in) :: dim_obs_p          ! Dimension of observed state
     128  REAL, INTENT(in)    :: state_p(dim_p)     ! PE-local model state
     129  REAL, INTENT(out) :: m_state_p(dim_obs_p) ! PE-local observed state
     130}}}
     131
     132The routine is called during the analysis step. It has to perform the operation of the observation operator acting on a state vector that is provided as `state_p`. The observed state has to be returned in `m_state_p`.
     133
     134For a model using domain decomposition, the operation is on the PE-local sub-domain of the model and has to provide the observed sub-state for the PE-local domain.
     135
     136Hint:
     137 * If the observation operator involves a global operation, e.g. some global integration, while using domain-decomposition one has to gather the information from the other model domains using MPI communication.
     138
     139
     140=== `U_init_obs` (init_obs_pdaf.F90) ===
     141
     142This routine is used by all global filter algorithms (SEEK, SEIK, EnKF, ETKF, NETF, PF).
     143
     144The interface for this routine is:
     145{{{
     146SUBROUTINE init_obs(step, dim_obs_p, observation_p)
     147
     148  INTEGER, INTENT(in) :: step             ! Current time step
     149  INTEGER, INTENT(in) :: dim_obs_p        ! PE-local dimension of obs. vector
     150  REAL, INTENT(out)   :: observation_p(dim_obs_p) ! PE-local observation vector
     151}}}
     152
     153The routine is called during the analysis step.
     154It has to provide the vector of observations in `observation_p` for the current time step.
     155
     156For a model using domain decomposition, the vector of observations that exist on the model sub-domain for the calling process has to be initialized.
     157
     158
     159=== `U_prepoststep` (prepoststep_ens_pdaf.F90) ===
     160 
     161The routine has been described on the [ModifyModelforEnsembleIntegration#U_prepoststepprepoststep_ens_pdaf.F90 page on modifying the model code for the ensemble integration] for the SEIK filter. For the PF, the interface is generally identical. For completeness, we repeat the description here.
     162
     163The interface for this routine is
     164{{{
     165SUBROUTINE prepoststep(step, dim_p, dim_ens, dim_ens_p, dim_obs_p, &
     166                       state_p, Uinv, ens_p, flag)
     167
     168  INTEGER, INTENT(in) :: step        ! Current time step
     169                         ! (When the routine is called before the analysis -step is provided.)
     170  INTEGER, INTENT(in) :: dim_p       ! PE-local state dimension
     171  INTEGER, INTENT(in) :: dim_ens     ! Size of state ensemble
     172  INTEGER, INTENT(in) :: dim_ens_p   ! PE-local size of ensemble
     173  INTEGER, INTENT(in) :: dim_obs_p   ! PE-local dimension of observation vector
     174  REAL, INTENT(inout) :: state_p(dim_p) ! PE-local forecast/analysis state
     175                                     ! The array 'state_p' is not generally not initialized in the case of SEIK/EnKF/ETKF/NETF/PF.
     176                                     ! It can be used freely in this routine.
     177  REAL, INTENT(inout) :: Uinv(dim_ens, dim_ens) ! Inverse of matrix U
     178  REAL, INTENT(inout) :: ens_p(dim_p, dim_ens)  ! PE-local state ensemble
     179  INTEGER, INTENT(in) :: flag        ! PDAF status flag
     180}}}
     181
     182The routine `U_prepoststep` is called once at the beginning of the assimilation process. In addition, it is called during the assimilation cycles before the analysis step and after the ensemble transformation. The routine is called by all filter processes (that is `filterpe=1`).
     183
     184The routine provides for the user the full access to the ensemble of model states. Thus, user-controlled pre- and post-step operations can be performed.  For example the forecast and the analysis states and ensemble covariance matrix can be analyzed, e.g. by computing the estimated variances. In addition, the estimates can be written to disk.
     185
     186Hint:
     187 * If a user considers to perform adjustments to the estimates (e.g. for balances), this routine is the right place for it.
     188 * The vector (`state_p`) is allocated but not initialized with the ensemble mean. It can be used freely during the execution of `U_prepoststep`, for example to compute the ensemble mean state.
     189 * The interface has a difference for PF and ESTKF/ETKF: For the PF, the array `Uinv` has size `1` x `1`. In contrast it has size `dim_ens` x `dim_ens` for the ESTKF/ETKF filters. (For most cases, this will be irrelevant, because most usually the ensemble array `ens_p` is used for computations, rather than `Uinv`.)
     190 * The interface through which `U_prepoststep` is called does not include the array of smoothed ensembles. In order to access the smoother ensemble array one has to set a pointer to it using a call to the routine `PDAF_get_smootherens` (see page on [AuxiliaryRoutines auxiliary routines])
     191
     192
     193=== `U_likelihood` (likelihood_pdaf.F90) ===
     194
     195This routine is used by the PF and NETF algorithms only.
     196
     197The interface for this routine is:
     198{{{
     199SUBROUTINE U_likelihood(step, dim_obs_p, obs_p, residual, likely)
     200
     201  INTEGER, INTENT(in) :: step                ! Current time step
     202  INTEGER, INTENT(in) :: dim_obs_p           ! PE-local dimension of obs. vector
     203  REAL, INTENT(in)    :: obs_p(dim_obs_p)    ! PE-local vector of observations
     204  REAL, INTENT(in)    :: residual(dim_obs_p) ! Input vector holding the residual y-Hx
     205  REAL, INTENT(out)   :: likely              ! Output value of the likelihood
     206}}}
     207
     208The routine is called during the analysis step. In the PF and NETF, as in other particle filters, the likelihood of the observations has to be computed for each ensemble member. The likelihood is computed from the observation-state residual according to the assumed observation error distribution. Commonly, the observation errors are assumed to be Gaussian distributed. In this case, the likelihood is '''exp(-0.5*(y-Hx)^T^*R^-1^*(y-Hx))'''.
     209
     210For a model with domain decomposition, `resid` contains the part of the matrix that resides on the model sub-domain of the calling process. The likelihood has to be computed for the global state vector. Thus some parallel communication might be required to complete the computation.
     211
     212Hints:
     213 * The routine is very similar to the routine [wiki:U_prodRinvA]. The main addition is the computation of the likelihood after computing '''R^-1^*(y-Hx)''', which corresponds to '''R^-1^*A_p''' in [wiki:U_prodRinvA].
     214 * The information about the inverse observation error covariance matrix has to be provided by the user. Possibilities are to read this information from a file, or to use a Fortran module that holds this information, which one could already prepare in init_pdaf.
     215 * The routine does not require that the product is implemented as a real matrix-vector product. Rather, the product can be implemented in its most efficient form. For example, if the observation error covariance matrix is diagonal, only the multiplication of the inverse diagonal with the vector `resid` has to be implemented.
     216 * The observation vector `obs_p` is provided through the interface for cases where the observation error variance is relative to the actual value of the observations.
     217
     218
     219=== `U_next_observation` (next_observation_pdaf.F90) ===
     220
     221This routine is independent of the filter algorithm used.
     222See the page on [InsertAnalysisStep#U_next_observationnext_observation_pdaf.F90 inserting the analysis step] for the description of this routine.
     223
     224
     225== Execution order of user-supplied routines ==
     226
     227For the PF, the user-supplied routines are essentially executed in the order they are listed in the interface to `PDAF_assimilate_pf`. 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 `U_obs_op`.
     228
     229Before the analysis step is called, the following routine is executed:
     230 1. [#U_collect_statecollect_state_pdaf.F90 U_collect_state]
     231
     232The 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:
     233 1. [#U_prepoststepprepoststep_ens_pdaf.F90 U_prepoststep] (Call to act on the forecast ensemble, called with negative value of the time step)
     234 1. [#U_init_dim_obsinit_dim_obs_pdaf.F90 U_init_dim_obs]
     235 1. [#U_init_obsinit_obs_pdaf.F90 U_init_obs]
     236 1. [#U_obs_opobs_op_pdaf.F90 U_obs_op] (`dim_ens` calls; one call for each ensemble member)
     237 1. [#U_likelihoodlikelihood_pdaf.F90 U_likelihood] (`dim_ens` calls; one call for each ensemble member)
     238 1. [#U_prepoststepprepoststep_ens_pdaf.F90 U_prepoststep] (call to act on the analysis ensemble, called with (positive) value of the time step)
     239
     240In case of the routine `PDAF_assimilate_pf`, the following routines are executed after the analysis step:
     241 1. [#U_distribute_statedistribute_state_pdaf.F90 U_distribute_state]
     242 1. [#U_next_observationnext_observation_pdaf.F90 U_next_observation]
     243