Version 16 (modified by 14 months ago) (diff)  ,

Implementation of the Analysis step for the SEEK filter
Implementation Guide
 Main page
 Adaptation of the parallelization
 Initialization of PDAF
 Modifications for ensemble integration
 Implementation of the analysis step
 Implementation for ESTKF
 Implementation for LESTKF
 Implementation for ETKF
 Implementation for LETKF
 Implementation for SEIK
 Implementation for LSEIK
 Implementation for SEEK
 Implementation for EnKF
 Implementation for LEnKF
 Implementation for NETF
 Implementation for LNETF
 Implementation for PF
 Implementation for 3DVar
 Implementation for 3D Ensemble Var
 Implementation for Hybrid 3DVar
 Memory and timing information
 Ensemble Generation
 Diagnostics
Contents of this page
 Overview

PDAF_assimilate_seek

PDAF_put_state_seek

Usersupplied routines

U_collect_state
(collect_state_pdaf.F90) 
U_distribute_state
(distribute_state_pdaf.F90) 
U_init_dim_obs
(init_dim_obs_pdaf.F90) 
U_obs_op
(obs_op_pdaf.F90) 
U_init_obs
(init_obs_pdaf.F90) 
U_prepoststep
(prepoststep_seek_pdaf.F90) 
U_prodRinvA
(prodrinva_pdaf.F90) 
U_next_observation
(next_observation_pdaf.F90)

 Execution order of usersupplied routines
This page describes the implementation of the analysis step without using PDAFOMI. Please see the page on the analysis with OMI for the more modern and efficient implementation variant using PDAFOMI. 
Overview
For the analysis step of the SEEK filter different operations related to the observations are needed. These operations are requested by PDAF by calling usersupplied 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_seek
for the fullyparallel configuration (or PDAF_put_state_seek
for the flexible configuration). With regard to the parallelization, all these routines are executed by the filter processes (filterpe=.true.
) only.
For completeness we discuss here all usersupplied routines that are specified in the interface to PDAF_assimialte_seek. Thus, some of the usersupplied routines that are explained on the page explaining the modification of the model code for the ensemble integration for the SEIK filter are repeated here, but specified for the SEEK filter.
The SEEK filter is very similar to the SEIK filter. In fact, the SEIK filter has been introduced as an interpolated (Pham et al., 1998) version of the SEEK filter. Due to the similarity of both filters, the interface to the usersupplied routines is almost identical. Several of the usersuppplied routines can be identical for SEEK and SEIK. Differences are marked in the text below. The implementation of the SEEK filter follows its original description by Pham et al. (1998) as reviewed by Nerger et al. (Tellus, 2005).
There is no localized variant of the SEEK filter in PDAF. In Nerger et al. (Tellus, 2005), the SEIK filter performed much better than the SEEK filter. Due to this, we focused more on the SEIK filter after this comparison study. For real applications, we recommend using the ESTKF or its local variants LESTKF (In our study Nerger et al. (Mon. Wea. Rev., 2012, doi:10.1175/MWRD1100102.1), we developed the ESTKF method as an alternative to both the SEIK filter and the ETKF, to give better compute performance and assimilation results).
PDAF_assimilate_seek
The general aspects of the filter specific routines PDAF_assimilate_*
have been described on the page Modification of the model code for the ensemble integration and its subpage on inserting the analysis step. The routine is used in the fullyparallel 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 of the routine. Subsequently, the full set of usersupplied routines specified in the call to
PDAF_assimilate_seek` is explained.
is explained.
The interface when using the SEEK filter is the following:
SUBROUTINE PDAF_assimilate_seek(U_collect_state, U_distribute_state, U_init_dim_obs, & U_obs_op, U_init_obs, U_prepoststep, & U_prodRinvA, U_next_observation, status)
with the following arguments:
 U_collect_state: The name of the usersupplied 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 inPDAF_get_state
and also here.  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.
 U_init_dim_obs: The name of the usersupplied routine that provides the size of observation vector
 U_obs_op: The name of the usersupplied routine that acts as the observation operator on some state vector
 U_init_obs: The name of the usersupplied routine that initializes the vector of observations
 U_prepoststep: The name of the pre/poststep routine as in
PDAF_get_state
 U_prodRinvA: The name of the usersupplied 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 SEEK filter.
 U_next_observation: The name of a user supplied routine that initializes the variables
nsteps
,timenow
, anddoexit
. The same routine is also used inPDAF_get_state
. status
: The integer status flag. It is zero, ifPDAF_assimilate_seek
is exited without errors.
PDAF_put_state_seek
When the 'flexible' implementation variant is chosen for the assimilation system, the routine PDAF_put_state_seek
has to be used instead of PDAF_assimilate_seek
. The general aspects of the filter specific routines PDAF_put_state_*
have been described on the page Modification of the model code for the ensemble integration. The interface of the routine is identical with that of PDAF_assimilate_seek
with the exception the specification of the usersupplied routines U_distribute_state
and U_next_observation
are missing.
The interface when using the SEEK filter is the following:
SUBROUTINE PDAF_put_state_seek(U_collect_state, U_init_dim_obs, U_obs_op, & U_init_obs, U_prepoststep, U_prodRinvA, status)
Usersupplied routines
Here, all usersupplied routines are described that are required in the call to PDAF_assimilate_seek
. For some of the generic routines, we link to the page on modifying the model code for the ensemble integration.
To indicate usersupplied 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.
In the subroutine interfaces some variables appear with the suffix _p
. This suffix indicates that the variable is particular to a model subdomain, if a domain decomposed model is used. Thus, the value(s) in the variable will be different for different model subdomains.
U_collect_state
(collect_state_pdaf.F90)
This routine is independent of the filter algorithm used. See the page on inserting the analysis step for the description of this routine.
U_distribute_state
(distribute_state_pdaf.F90)
This routine is independent of the filter algorithm used. See the page on inserting the analysis step for the description of this routine.
U_init_dim_obs
(init_dim_obs_pdaf.F90)
This routine is used by all global filter algorithms (SEEK, SEIK, EnKF, ETKF).
The interface for this routine is:
SUBROUTINE init_dim_obs(step, dim_obs_p) INTEGER, INTENT(in) :: step ! Current time step INTEGER, INTENT(out) :: dim_obs_p ! Dimension of observation vector
The 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 domaindecomposed model is used, dim_obs_p
will be the size of the observation vector for the subdomain of the calling process.
Some hints:
 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.
U_obs_op
(obs_op_pdaf.F90)
This routine is used by all global filter algorithms (SEEK, SEIK, EnKF, ETKF).
The interface for this routine is:
SUBROUTINE obs_op(step, dim_p, dim_obs_p, state_p, m_state_p) INTEGER, INTENT(in) :: step ! Currrent time step INTEGER, INTENT(in) :: dim_p ! PElocal dimension of state INTEGER, INTENT(in) :: dim_obs_p ! Dimension of observed state REAL, INTENT(in) :: state_p(dim_p) ! PElocal model state REAL, INTENT(out) :: m_state_p(dim_obs_p) ! PElocal observed state
The 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
.
For a model using domain decomposition, the operation is on the PElocal subdomain of the model and has to provide the observed substate for the PElocal domain.
Hint:
 If the observation operator involves a global operation, e.g. some global integration, while using domaindecomposition one has to gather the information from the other model domains using MPI communication.
U_init_obs
(init_obs_pdaf.F90)
This routine is used by all global filter algorithms (SEEK, SEIK, EnKF, ETKF).
The interface for this routine is:
SUBROUTINE init_obs(step, dim_obs_p, observation_p) INTEGER, INTENT(in) :: step ! Current time step INTEGER, INTENT(in) :: dim_obs_p ! PElocal dimension of obs. vector REAL, INTENT(out) :: observation_p(dim_obs_p) ! PElocal observation vector
The routine is called during the analysis step.
It has to provide the vector of observations in observation_p
for the current time step.
For a model using domain decomposition, the vector of observations that exist on the model subdomain for the calling process has to be initialized.
U_prepoststep
(prepoststep_seek_pdaf.F90)
The routine has already been described on the page on modifying the model code for the ensemble integration for the SEIK filter. For the SEEK filter there are some differences, because of the fact that the covariance matrix is computed from the modes and eigenvalue matrix rather than from an ensemble of model states.
The interface of the routine is identical for all filters, but sizes can be different. In addition, the particular operations that are performed in the routine can be specific for each filter algorithm.
The interface for this routine is for the SEEK filter
SUBROUTINE prepoststep(step, dim_p, rank, rank_p, dim_obs_p, & state_p, Uinv, ens_p, flag) INTEGER, INTENT(in) :: step ! Current time step ! (When the routine is called before the analysis step is provided.) INTEGER, INTENT(in) :: dim_p ! PElocal state dimension INTEGER, INTENT(in) :: dim_eof ! Rank of covariance matrix (Number of EOF modes) INTEGER, INTENT(in) :: dim_eof_p ! PElocal rank of covariance matrix/EOF modes INTEGER, INTENT(in) :: dim_obs_p ! PElocal dimension of observation vector REAL, INTENT(inout) :: state_p(dim_p) ! PElocal forecast/analysis state REAL, INTENT(inout) :: Uinv(dim_eof, dim_eof) ! Inverse of matrix U REAL, INTENT(inout) :: eofV_p(dim_p, dim_ens) ! PElocal mode matrix V INTEGER, INTENT(in) :: flag ! PDAF status flag
The 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
).
The routine provides for the user the full access to the EOF modes of the SEEK filter, as well as the eigenvalue matrix Uinv
and the state estimate state_p
. Thus, usercontrolled pre and poststep 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.
Hint:
 If a user considers to perform adjustments to the estimates (e.g. for balances), this routine is the right place for it.
 Only for the SEEK filter the state vector (
state_p
) is initialized. For all other filters, the array is allocated, but it can be used freely during the execution ofU_prepoststep
.
U_prodRinvA
(prodrinva_pdaf.F90)
This routine is used by all filter algorithms that use the inverse of the observation error covariance matrix (SEEK, SEIK, and ETKF).
The interface for this routine is:
SUBROUTINE prodRinvA(step, dim_obs_p, rank, obs_p, A_p, C_p) INTEGER, INTENT(in) :: step ! Current time step INTEGER, INTENT(in) :: dim_obs_p ! PElocal dimension of obs. vector INTEGER, INTENT(in) :: rank ! Rank of initial covariance matrix/Number of EOF modes REAL, INTENT(in) :: obs_p(dim_obs_p) ! PElocal vector of observations REAL, INTENT(in) :: A_p(dim_obs_p, rank) ! Input matrix from analysis routine REAL, INTENT(out) :: C_p(dim_obs_p, rank) ! Output matrix
The routine is called during the analysis step. In the algorithms the product of the inverse of the observation error covariance matrix with some matrix has to be computed. For the SEEK filter this matrix holds the observed part of the EOF modes. The matrix is provided as A_p
. The product has to be given as C_p
.
For a model with domain decomposition, A_p
contains the part of the matrix that resides on the model subdomain of the calling process. The product has to be computed for this subdomain, too.
Hints:
 The routine does not require that the product is implemented as a real matrixmatrix 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 diagonal with matrix
A_p
has to be implemented.  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.
U_next_observation
(next_observation_pdaf.F90)
This routine is independent of the filter algorithm used. See the page on inserting the analysis step for the description of this routine.
Execution order of usersupplied routines
For the SEEK filter, the usersupplied routines are essentially executed in the order they are listed in the interface to PDAF_assimilate_seek
. 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
.
Before the analysis step is called the following routine is executed:
The 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:
 U_prepoststep (Call to act on the forecast ensemble, called with negative value of the time step)
 U_init_dim_obs
 U_obs_op (A single call to operate on the ensemble mean state)
 U_init_obs
 U_obs_op (
dim_eof
calls: one call for each ensemble member)  U_prodRinvA
 U_prepoststep (Call to act on the analysis ensemble, called with (positive) value of the time step)
In case of the routine PDAF_assimilate_seek
, the following routines are executed after the analysis step: