Changes between Initial Version and Version 1 of ImplementAnalysisnetf


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Dec 3, 2016, 6:12:54 PM (7 years ago)
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lnerger
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  • ImplementAnalysisnetf

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     1= Implementation of the Analysis step for the NETF (Nonlinear Ensemble Transform 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>Implementation for NETF</li>
     22</ol>
     23<li><a href="AddingMemoryandTimingInformation">Memory and timing information</a></li>
     24</ol>
     25</div>
     26}}}
     27
     28[[PageOutline(2-3,Contents of this page)]]
     29
     30== Overview ==
     31
     32For the analysis step of the NETF, 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_netf` in the fully-parallel implementation (or `PDAF_put_state_netf` 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.
     33
     34For completeness we discuss here all user-supplied routines that are specified in the interface to PDAF_assimilate_netf. 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.
     35
     36The analysis step of the NETF is is wide parts similar to that of the ETKF, ESTKF, and SEIK filter. For this reason, the interface to the user-supplied routines is almost identical. Depending on the implementation it can be possible to use identical routines for the NETF and the ETKF with the exception of the routine `U_likelihood`. Differences are marked in the text below.
     37
     38== `PDAF_assimilate_netf` ==
     39
     40The 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_netf` is explained.
     41
     42The interface when using the NETF method is the following:
     43{{{
     44  SUBROUTINE PDAF_assimilate_netf(U_collect_state, U_distribute_state, U_init_dim_obs, &
     45                                 U_obs_op, U_init_obs, U_prepoststep, U_likelihood, &
     46                                 U_next_observation, status)
     47}}}
     48with the following arguments:
     49 * [#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.
     50 * [#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.
     51 * [#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
     52 * [#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
     53 * [#U_init_obsinit_obs_pdaf.F90 U_init_obs]: The name of the user-supplied routine that initializes the vector of observations
     54 * [#U_prepoststepprepoststep_ens_pdaf.F90 U_prepoststep]: The name of the pre/poststep routine as in `PDAF_get_state`
     55 * [#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.
     56 * [#U_next_observationnext_observation.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`.
     57 * `status`: The integer status flag. It is zero, if `PDAF_assimilate_netf` is exited without errors.
     58
     59
     60== `PDAF_put_state_netf` ==
     61
     62When the 'flexible' implementation variant is chosen for the assimilation system, the routine `PDAF_put_state_netf` has to be used instead of `PDAF_assimilate_netf`. 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_netf` with the exception of the specification of the user-supplied routines `U_distribute_state` and `U_next_observation` are missing.
     63
     64The interface when using the NETF method is the following:
     65{{{
     66  SUBROUTINE PDAF_put_state_netf(U_collect_state, U_init_dim_obs, U_obs_op, &
     67                                 U_init_obs, U_prepoststep, U_likelihood, status)
     68}}}
     69
     70
     71== User-supplied routines ==
     72
     73Here, all user-supplied routines are described that are required in the call to `PDAF_assimilate_netf`. For some of the generic routines, we link to the page on [ModifyModelforEnsembleIntegration modifying the model code for the ensemble integration].
     74
     75To 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.
     76
     77In 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.
     78
     79
     80=== `U_collect_state` (collect_state_pdaf.F90) ===
     81
     82This routine is independent of the filter algorithm used.
     83See the page on [InsertAnalysisStep#U_collect_statecollect_state_pdaf.F90 inserting the analysis step] for the description of this routine.
     84
     85
     86=== `U_distribute_state` (distribute_state_pdaf.F90) ===
     87
     88This routine is independent of the filter algorithm used.
     89See the page on [InsertAnalysisStep#U_distribute_statedistribute_state_pdaf.F90 inserting the analysis step] for the description of this routine.
     90
     91
     92=== `U_init_dim_obs` (init_dim_obs_pdaf.F90) ===
     93
     94This routine is used by all global filter algorithms (SEEK, SEIK, EnKF, ETKF, NETF).
     95
     96The interface for this routine is:
     97{{{
     98SUBROUTINE init_dim_obs(step, dim_obs_p)
     99
     100  INTEGER, INTENT(in)  :: step       ! Current time step
     101  INTEGER, INTENT(out) :: dim_obs_p  ! Dimension of observation vector
     102}}}
     103
     104The 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.
     105
     106Some hints:
     107 * 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.
     108
     109
     110=== `U_obs_op` (obs_op_pdaf.F90) ===
     111
     112This routine is used by all global filter algorithms (SEEK, SEIK, EnKF, ETKF, NETF).
     113
     114The interface for this routine is:
     115{{{
     116SUBROUTINE obs_op(step, dim_p, dim_obs_p, state_p, m_state_p)
     117
     118  INTEGER, INTENT(in) :: step               ! Current time step
     119  INTEGER, INTENT(in) :: dim_p              ! PE-local dimension of state
     120  INTEGER, INTENT(in) :: dim_obs_p          ! Dimension of observed state
     121  REAL, INTENT(in)    :: state_p(dim_p)     ! PE-local model state
     122  REAL, INTENT(out) :: m_state_p(dim_obs_p) ! PE-local observed state
     123}}}
     124
     125The 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`.
     126
     127For 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.
     128
     129Hint:
     130 * 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.
     131
     132
     133=== `U_init_obs` (init_obs_pdaf.F90) ===
     134
     135This routine is used by all global filter algorithms (SEEK, SEIK, EnKF, ETKF, NETF).
     136
     137The interface for this routine is:
     138{{{
     139SUBROUTINE init_obs(step, dim_obs_p, observation_p)
     140
     141  INTEGER, INTENT(in) :: step             ! Current time step
     142  INTEGER, INTENT(in) :: dim_obs_p        ! PE-local dimension of obs. vector
     143  REAL, INTENT(out)   :: observation_p(dim_obs_p) ! PE-local observation vector
     144}}}
     145
     146The routine is called during the analysis step.
     147It has to provide the vector of observations in `observation_p` for the current time step.
     148
     149For a model using domain decomposition, the vector of observations that exist on the model sub-domain for the calling process has to be initialized.
     150
     151
     152=== `U_prepoststep` (prepoststep_ens_pdaf.F90) ===
     153 
     154The 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 NETF, the interface is generally identical. For completeness, we repeat the description here.
     155
     156The interface for this routine is
     157{{{
     158SUBROUTINE prepoststep(step, dim_p, dim_ens, dim_ens_p, dim_obs_p, &
     159                       state_p, Uinv, ens_p, flag)
     160
     161  INTEGER, INTENT(in) :: step        ! Current time step
     162                         ! (When the routine is called before the analysis -step is provided.)
     163  INTEGER, INTENT(in) :: dim_p       ! PE-local state dimension
     164  INTEGER, INTENT(in) :: dim_ens     ! Size of state ensemble
     165  INTEGER, INTENT(in) :: dim_ens_p   ! PE-local size of ensemble
     166  INTEGER, INTENT(in) :: dim_obs_p   ! PE-local dimension of observation vector
     167  REAL, INTENT(inout) :: state_p(dim_p) ! PE-local forecast/analysis state
     168                                     ! The array 'state_p' is not generally not initialized in the case of SEIK/EnKF/ETKF/NETF.
     169                                     ! It can be used freely in this routine.
     170  REAL, INTENT(inout) :: Uinv(dim_ens, dim_ens) ! Inverse of matrix U
     171  REAL, INTENT(inout) :: ens_p(dim_p, dim_ens)  ! PE-local state ensemble
     172  INTEGER, INTENT(in) :: flag        ! PDAF status flag
     173}}}
     174
     175The 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`).
     176
     177The 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.
     178
     179Hint:
     180 * If a user considers to perform adjustments to the estimates (e.g. for balances), this routine is the right place for it.
     181 * 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.
     182 * The interface has a difference for NETF/ETKF and SEIK: For the NETF, the array `Uinv` has size `dim_ens` x `dim_ens`. In contrast it has size `dim_ens-1` x `dim_ens-1` for the SEIK filter. (For most cases, this will be irrelevant, because most usually the ensemble array `ens_p` is used for computations, rather than `Uinv`. However, for the SEIK filter with fixed covariance matrix, `Uinv` is required to compute the estimate analysis error. The fixed covariance matrix mode is not available for the NETF)
     183 * 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])
     184
     185
     186=== `U_likelihood` (likelihood_pdaf.F90) ===
     187
     188This routine is used by the NETF algorithm only.
     189
     190The interface for this routine is:
     191{{{
     192SUBROUTINE U_likelihood(step, dim_obs_p, obs_p, residual, likely)
     193
     194  INTEGER, INTENT(in) :: step                ! Current time step
     195  INTEGER, INTENT(in) :: dim_obs_p           ! PE-local dimension of obs. vector
     196  REAL, INTENT(in)    :: obs_p(dim_obs_p)    ! PE-local vector of observations
     197  REAL, INTENT(in)    :: residual(dim_obs_p) ! Input vector holding the residual y-Hx
     198  REAL, INTENT(out)   :: likely              ! Output value of the likelihood
     199}}}
     200
     201The routine is called during the analysis step. In the 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))'''.
     202
     203For 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.
     204
     205Hints:
     206 * 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].
     207 * 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.
     208 * 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.
     209 * 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.
     210
     211
     212=== `U_next_observation` (next_observation_pdaf.F90) ===
     213
     214This routine is independent of the filter algorithm used.
     215See the page on [InsertAnalysisStep#U_next_observationnext_observation_pdaf.F90 inserting the analysis step] for the description of this routine.
     216
     217
     218== Execution order of user-supplied routines ==
     219
     220For the NETF, the user-supplied routines are essentially executed in the order they are listed in the interface to `PDAF_assimilate_netf`. 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`.
     221
     222Before the analysis step is called, the following routine is executed:
     223 1. [#U_collect_statecollect_state_pdaf.F90 U_collect_state]
     224
     225The 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:
     226 1. [#U_prepoststepprepoststep_ens_pdaf.F90 U_prepoststep] (Call to act on the forecast ensemble, called with negative value of the time step)
     227 1. [#U_init_dim_obsinit_dim_obs_pdaf.F90 U_init_dim_obs]
     228 1. [#U_init_obsinit_obs_pdaf.F90 U_init_obs]
     229 1. [#U_obs_opobs_op_pdaf.F90 U_obs_op] (`dim_ens` calls; one call for each ensemble member)
     230 1. [#U_likelihoodlikelihood_pdaf.F90 U_likelihood] (`dim_ens` calls; one call for each ensemble member)
     231 1. [#U_prepoststepprepoststep_ens_pdaf.F90 U_prepoststep] (call to act on the analysis ensemble, called with (positive) value of the time step)
     232
     233In case of the routine `PDAF_assimilate_netf`, the following routines are executed after the analysis step:
     234 1. [#U_distribute_statedistribute_state_pdaf.F90 U_distribute_state]
     235 1. [#U_next_observationnext_observation_pdaf.F90 U_next_observation]
     236