Implementation of the Analysis step for the SEEK filter

This page describes the implementation of the analysis step without using PDAF-OMI. Please see the page on the analysis with OMI for the more modern and efficient implementation variant using PDAF-OMI.

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 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_seek for the fully-parallel 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 user-supplied routines that are specified in the interface to PDAF_assimialte_seek. Thus, some of the user-supplied 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 user-supplied routines is almost identical. Several of the user-suppplied 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/MWR-D-11-00102.1), 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 sub-page on 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 of the routine. Subsequently, the full set of user-supplied 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 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 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 user-supplied routine that provides the size of observation vector
• U_obs_op: The name of the user-supplied routine that acts as the observation operator on some state vector
• U_init_obs: The name of the user-supplied 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 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 SEEK filter.
• 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.
• status: The integer status flag. It is zero, if PDAF_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 user-supplied 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)

User-supplied routines

Here, all user-supplied 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 user-supplied routines we use the prefix U_. In the tutorials in tutorial/ and in the template directory templates/ these routines exist without the prefix, but with the extension _pdaf. The files are named correspondingly. 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 sub-domain, if a domain decomposed model is used. Thus, the value(s) in the variable will be different for different model sub-domains.

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 domain-decomposed model is used, dim_obs_p will be the size of the observation vector for the sub-domain 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              ! PE-local dimension of state
  INTEGER, INTENT(in) :: dim_obs_p          ! Dimension of observed state
  REAL, INTENT(in)    :: state_p(dim_p)     ! PE-local model state
  REAL, INTENT(out) :: m_state_p(dim_obs_p) ! PE-local 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 PE-local sub-domain of the model and has to provide the observed sub-state for the PE-local domain.

Hint:

• 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.

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        ! PE-local dimension of obs. vector
  REAL, INTENT(out)   :: observation_p(dim_obs_p) ! PE-local 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 sub-domain 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       ! PE-local state dimension
  INTEGER, INTENT(in) :: dim_eof     ! Rank of covariance matrix (Number of EOF modes)
  INTEGER, INTENT(in) :: dim_eof_p   ! PE-local rank of covariance matrix/EOF modes
  INTEGER, INTENT(in) :: dim_obs_p   ! PE-local dimension of observation vector
  REAL, INTENT(inout) :: state_p(dim_p) ! PE-local forecast/analysis state
  REAL, INTENT(inout) :: Uinv(dim_eof, dim_eof)   ! Inverse of matrix U
  REAL, INTENT(inout) :: eofV_p(dim_p, dim_ens)    ! PE-local 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, 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.

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 of U_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            ! PE-local 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)     ! PE-local 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 sub-domain of the calling process. The product has to be computed for this sub-domain, too.

Hints:

• The routine does not require that the product is implemented as a real matrix-matrix 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 user-supplied routines

For the SEEK filter, the user-supplied 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:

1. U_collect_state

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:

1. U_prepoststep (Call to act on the forecast ensemble, called with negative value of the time step)
2. U_init_dim_obs
3. U_obs_op (A single call to operate on the ensemble mean state)
4. U_init_obs
5. U_obs_op (dim_eof calls: one call for each ensemble member)
6. U_prodRinvA
7. 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:

1. U_distribute_state
2. U_next_observation