Changes between Version 10 and Version 11 of ImplementAnalysisestkf


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Timestamp:
May 5, 2014, 2:05:42 PM (11 years ago)
Author:
lnerger
Comment:

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  • ImplementAnalysisestkf

    v10 v11  
    3131With Version 1.8 of PDAF, the ESTKF [Error Subspace Transform Kalman Filter] algorithm has been introduced. The user-supplied routines required for the ESTKF are identical to those required for the SEIK filter and amost identical to those required for the ETKF method.
    3232
    33 For the analysis step of the ESTKF different operations related to the observations are needed. These operations are requested by PDAF by call-back routines supplied by the user. Intentionally, the operations are split into separate routines in order to keep the operations rather elementary and efficient. This procedure should simplify the implementation. The names of the required routines are specified in the call to the routine `PDAF_assimilate_estkf` (or `PDAF_put_state_estkf`) that was discussed before. With regard to the parallelization, all these routines are executed by the filter processes (`filterpe=.true.`) only.
     33For the analysis step of the ESTKF different operations related to the observations are needed. These operations are requested by PDAF by call-back routines supplied by the user. Intentionally, the operations are split into separate routines in order to keep the operations rather elementary and efficient. This procedure should simplify the implementation. The names of the required routines are specified in the call to the routine `PDAF_assimilate_estkf` in the fully-parallel implementation (or `PDAF_put_state_estkf` 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.
    3434
    3535For completeness we discuss here all user-supplied routines that are specified in the interface to PDAF_assimilate_estkf. Thus, some of the user-supplied routines that are explained on the page describing the modification of the model code for the ensemble integration are repeated here.