Changes between Version 9 and Version 10 of ImplementGenerateObs


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Timestamp:
Nov 30, 2020, 1:14:31 PM (4 years ago)
Author:
lnerger
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  • ImplementGenerateObs

    v9 v10  
    33[[PageOutline(2-3,Contents of this page)]]
    44
    5 The observation generation functionality was added with Version 1.14 of PDAF.
     5The observation generation functionality was added with Version 1.14 of PDAF. Here we describe the implementation using PDAF-OMI that was introduced with PDAF version 1.16. (The older implementation variant is documented on the page on [wiki:ImplementGenerateObs_noOMI Implementation of Observation Generation without OMI].)
    66
    77== Overview ==
    … …  
    2525This step replaces the analysis step. The implementation is analogous to implementing the analysis step as described on the [wiki:ImplementationofAnalysisStep page on implementing the analysis step].
    2626
    27 == `PDAF_generate_obs` ==
     27== `PDAFomi_generate_obs` ==
    2828
    29 This routine is used in the same way as the filter specific routines `PDAF_assimilate_*`. Thus the general aspect 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 `PDAF_generate_obs` 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_generate_obs' 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_generate_obs` is explained. Apart from two call-back routines, the routines are idnetical to e.g. those used for the LESTKF and LETKF filters.
     29This routine is used in the same way as the filter specific routines `PDAFomi_assimilate_*`. Thus the general aspect 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 `PDAFomi_generate_obs` is used in the fully-parallel implementation variant of the data assimilation system. When the 'flexible' implementation variant is used, the routines `PDAFomi_put_state_generate_obs' 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 `PDAFomi_generate_obs` is described. Apart from two call-back routines, the routines are identical to e.g. those used for the local filters.
    3030
    3131{{{
    3232  SUBROUTINE PDAF_generate_obs(U_collect_state, U_distribute_state, &
    33                                   U_init_dim_obs_f, U_obs_op_f, U_init_obserr_f, U_get_obs_f, &
     33                                  U_init_dim_obs, U_obs_op, U_get_obs_f, &
    3434                                  U_prepoststep, U_next_observation, status_pdaf)
    3535}}}
    … …  
    3737 * `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 [ModifyModelforEnsembleIntegration#PDAF_get_state PDAF_get_state]
    3838 * `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.
    39  * `U_init_dim_obs_f`: The name of the user-supplied routine that provides the size of the full observation vector
    40  * `U_obs_op_f`: The name of the user-supplied routine that acts as the full observation operator on some state vector
    41  * `U_init_obserr_f`: The name of the user-supplied routine that initializes the vector of observations error standard deviations for full observation vector
     39 * `U_init_dim_obs`: The name of the user-supplied routine that provides the size of the full observation vector
     40 * `U_obs_op`: The name of the user-supplied routine that acts as the full observation operator on some state vector
    4241 * `U_get_obs_f`: The name of the user-supplied routine that receives the full vector of generated synthetic observations from PDAF
    4342 * `U_prepoststep`: The name of the pre/poststep routine as in `PDAF_get_state`
    … …  
    4645
    4746
    48 == `PDAF_put_state_generate_obs` ==
     47== `PDAFomi_put_state_generate_obs` ==
    4948
    50 When the 'flexible' implementation variant is chosen for the assimilation system, the routine `PDAF_put_state_generate_obs` has to be used instead of `PDAF_generate_obs`. 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_generate_obs` with the exception the specification of the user-supplied routines `U_distribute_state` and `U_next_observation` are missing.
     49When the 'flexible' implementation variant is chosen for the assimilation system, the routine `PDAFomi_put_state_generate_obs` has to be used instead of `PDAFomi_generate_obs`. The general aspects of the filter specific routines `PDAFomi_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 `PDAFomi_generate_obs` with the exception the specification of the user-supplied routines `U_distribute_state` and `U_next_observation` are missing.
    5150
    5251The interface is the following:
    5352{{{
    54   SUBROUTINE PDAF_put_state_generate_obs(U_collect_state, U_init_dim_obs_f, U_obs_op_f, U_init_obserr_f, &
     53  SUBROUTINE PDAFomi_put_state_generate_obs(U_collect_state, U_init_dim_obs, U_obs_op, &
    5554                                  U_get_obs_f, U_prepoststep, status_pdaf)
    5655}}}
    … …  
    7776
    7877
    79 === `U_init_dim_obs_f` (init_dim_obs_f_pdaf.F90) ===
     78=== `U_init_dim_obs` (callback_obs_pdafomi.F90) ===
    8079
    81 This routine has to initialize the size `dim_obs_f` of the full observation vector according to the current time step. For simplicity, `dim_obs_f` can be the size for the global model domain. The routine is described in detail on the [wiki:ImplementAnalysislestkf page on implementing the analysis step for LESKTF].
     80The routine is called at the beginning of each analysis step.  For PDAF, it has to initialize the size `dim_obs_p` of the observation vector according to the current time step. Apart from this routine will initialize overall observation information.  In this routine one just calls `init_dim_obs_TYPE` for each observation type. The routine is described in detail on [wiki:OMI_Callback_obs_pdafomi callback_obs_pdafomi.F90].
    8281
    83 === `U_obs_op_f` (obs_obs_f_pdaf.F90) ===
    8482
    85 This routine has to perform the operation of the observation operator acting on a state vector, which is provided as `state_p`. The observed state has to be returned in `m_state_f`. It is the observed state corresponding to the 'full' observation vector. The routine is described in detail on the [wiki:ImplementAnalysislestkf page on implementing the analysis step for LESKTF].
     83=== `U_obs_op` (callback_obs_pdafomi.F90) ===
    8684
    87 === `U_init_obserr_f` (init_obserr_f_pdaf.F90) ===
     85The 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`. In this routine one just calls `obs_op_TYPE` for each observation type. The routine is described in detail on [wiki:OMI_Callback_obs_pdafomi callback_obs_pdafomi.F90].
    8886
    89 This routine is specific for the observation generation. The routine is called by PDAF during the observation generation. Its purpose is to fill the provided vector of observation error standard deviations.
    90 
    91 The interface is the following:
    92 {{{
    93 SUBROUTINE init_obserr_f_pdaf(step, dim_obs_f, obs_f, rms_obs)
    94 }}}
    95 with
    96  * `step` : `integer, intent(in)`[[BR]] Current time step
    97  * `dim_obs_f` : `integer, intent(in)`[[BR]] Size of full observation vector
    98  * `obs_f` : `real, intent(in), dimension(dim_obs_f)`[[BR]] Full vector of observations
    99  * `rms_obs` : `real, intent(out), dimension(dim_obs_f)`[[BR]] Full vector of observation error standard deviations
    100 
    101 Notes:
    102  * The routines handles the 'full' observation vector as in localizated filters. As described for the observation generation functionality one can also use it for global filters. In this case the 'full' vector would just contain the observations local to a process sub-domain.
    103  * The observation vector `obs_f` is provided to the routine for the case that the observation error is relative to the value of the observations.
    10487
    10588=== `U_get_obs_f` (get_obs_f_pdaf.F90) ===
    … …  
    132115
    133116
    134 == Recommendations for using `PDAF_generate_obs` ==
     117== Recommendations for using `PDAFomi_generate_obs` ==
    135118
    136 The observation-generation with `PDAF_generate_obs` or `PDAF_put_state_generate_obs` works analogously to the observation handling in the localized filters like LESTKF and LETKF. However, the observation generation does not modify the ensemble states and `prepoststep_pdaf` is only called once before the each observation generation, but not afterwards. The routine `init_dim_obs_f_pdaf` can be identical to the actuall assimilation case. It initializes the full observation dimension and usually also some more observation information (as described e.g. on the [wikio:init_dim_obs_f_pdaf detail page on init_dim_obs_f_pdaf]. Subsequently `obs_op_f_pdaf` is applied. One can run the ensemble generation with a single ensemble member (dim_ens=1) or a larger ensemble. If dim_ens>1, the observation operator is applied to the ensemble mean state. The routine `init_obserr_f_pdaf` provides PDAF with the vector of observation error standard deviations. This is used in combination with Gaussian random noise to compute the perturbations that are added to the true state to generate the observations. Finally `get_obs_f_pdaf` gives the user access to the generated synthetic observation vector so that one can write it to a file for later use (See the [wiki:readwrite_obs page on the template file readwrite_obs.F90] for a description how the observations can be written to a file and used later on).
     119The observation-generation with `PDAFomi_generate_obs` or `PDAFomi_put_state_generate_obs` works analogously to the observation handling in the localized filters like LESTKF and LETKF. However, the observation generation does not modify the ensemble states and `prepoststep_pdaf` is only called once before the each observation generation, but not afterwards. The usual observation functionality of `init_dim_obs_pdafomi` and `obs_op_pdafomi` is used to obtain the observed model state.
    137120
    138 If one has access to real observations, one can use the implementation of `init_dim_obs_f_pdaf` and `obs_ob_f_pdaf` for these observations to generate synthetic observations simulating these real observations. Thus one runs the observation generation using these routines without any modifications.
     121One can run the ensemble generation with a single ensemble member (dim_ens=1) or a larger ensemble. If dim_ens>1, the observation operator is applied to the ensemble mean state. The observation error information initialized in `init_dim_obs_pdafomi` is used in combination with Gaussian random noise to compute the perturbations that are added to the true state to generate the observations. Finally `get_obs_f_pdaf` gives the user access to the generated synthetic observation vector so that one can write it to a file for later use (See the [wiki:readwrite_obs page on the template file readwrite_obs.F90] for a description how the observations can be written to a file and used later on).
     122
     123If one has access to real observations, one can use the implementation of `init_dim_obs_pdafomi` and `obs_ob_pdafomi` for these observations to generate synthetic observations simulating these real observations. Thus, one runs the observation generation using these routines without any modifications.
     124
     125'''Note:''' The observation generation should always be performed for a single observation type at a time. Thus one generates separate observation files for each observation type.
    139126
    140127
    141128== Using the synthetic observations in twin experiments ==
    142129
    143 To perform a twin experiment using the synthetic observations generated by PDAF, one runs the data assimilation as one would with real observations. If one already initializes the vector of actual observations in the routine `init_dim_obs_f` one only needs to small modification of this routine. Namely, only required modification is that at the end of `init_dim_obs_f` one overwrites the vector of real observations with the values from the synthetic observations. If one uses the template file `readwrite_obs.F90` for this, one can use `read_syn_obs` from this file at the end of `init_dim_obs_f` to overwrite the observatio vector. To allow for a flexible switching between the case using real observations and the twin experiment, one can for example introduce a flag `twin_experiment` that controls whether the real observation values are overwritten.
     130To perform a twin experiment using the synthetic observations generated by PDAF, one runs the data assimilation as one would with real observations. If one already initializes the vector of actual observations in the routines `init_dim_obs_TYPE` in the observation modules one only needs a small modification of this routine. Namely, the only required modification is that at the end of `init_dim_obs_TYPE` one overwrites the vector of real observations with the values from the synthetic observations. If one uses the template file `readwrite_obs.F90` for this, one can use `read_syn_obs` from this file at the end of `init_dim_obs_TYPE` to overwrite the observation vector. To allow for a flexible switching between the case using real observations and the twin experiment, one can for example introduce a flag `twin_experiment` that controls whether the real observation values are overwritten. This reading is already included, but out-commented, in the templates.
    144131
    145 Example implementations using `PDAF_put_state_generate_obs` and `readwrite_obs.F90` are provided by the two test cases `testsuite/src/dummymodel_1D` and `testsuite/src/lorenz96`. These also use the flag `twin_experiment` to actiavate the twin experiment (Note: These two test cases always use simulated observations. Nonetheless, they allow to see how the synthetic observations are generated with PDAF and how they are used in a twin experiment).
     132Example implementations using `PDAFomi_put_state_generate_obs` and `readwrite_obs.F90` are provided by the test case `testsuite/src/lorenz96_omi`. These also use the flag `twin_experiment` to activate the twin experiment (Note: These two test cases always use simulated observations. Nonetheless, they allow to see how the synthetic observations are generated with PDAF and how they are used in a twin experiment).
    146133