Changes between Version 89 and Version 90 of FeaturesofPdaf


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Timestamp:
May 30, 2025, 5:45:49 PM (42 hours ago)
Author:
lnerger
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  • FeaturesofPdaf

    v89 v90  
    1111PDAF simplifies the implementation of data assimilation systems using existing model code by the following:
    1212
    13  1. PDAF provides fully implemented, parallelized, and optimized ensemble-based algorithms for data assimilation. Currently, these are ensemble-based Kalman filters like the LETKF, LESTKF, and EnKF methods and nonlinear filters are provided. Starting from PDAF V2.0 also 3D-variational methods are provided.
     13 1. PDAF provides fully implemented, parallelized, and optimized ensemble-based algorithms for data assimilation. These are ensemble-based Kalman filters like the LETKF, LESTKF, and EnKF methods. Also nonlinear filters and 3D-variational methods are provided.
    1414 1. PDAF provides two variants to build a data assimilation system:
    15   1. PDAF can be attached to the model source code by minimal changes to the code, which we call ``online mode``. These changes only concern the general part of the code, but not the numerics of the model. In addition, a small set of routines is required that are specific to the model or the observations to be assimilated. These routines can be implemented like routines of the model.
    16   1. PDAF also offers an ``offline mode``. This is for the case that you don't like to (or even cannot) modify your model source code at all. In the offline mode, PDAF is compiled separately from the model together with the supporting routines to handle the observations. Then, the model and the assimilation step are executed separately. This approach is simpler to implement than the ``online mode``, but it is computationally less efficient.
    17  1. PDAF is called through a well-defined standard interface. This allows, for example, to switch between the LETKF, LESTKF, and LSEIK methods without additional coding.
    18  1. PDAF provides parallelization support for the data assimilation system. If your numerical model is already parallelized, PDAF enables the data assimilation system to run several model tasks in parallel within a single executable. However, PDAF can also be used without parallelization, for example to test small systems.
    19  1. PDAF does not require that your model can be called as a subroutine. Rather, PDAF is added to the model and the formed data assimilation system can be executed pretty much like the model-program would without data assimilation.
    20  1. The PDAF release also provides bindings to couple PDAF with selected real models. Such modelbindings are, e.g., available for the MITgcm and the NEMO ocean circulation models, for the AWI Climate Model (AWI-CM, a coupled model consisting of ECHAM (atmosphere) and FESOM (ocean)) and the Weather and Forecast Model (WRF). See the [wiki:ModelsConnectedToPDAF list of models that were already coupled to PDAF] for an overview.
     15  1. ''Online Mode'': In this case, PDAF is attached to the model source code by minimal changes to the code. These changes only concern the general part of the code, but not the numerics of the model. In addition, a small set of routines is required that are specific to the model or the observations to be assimilated. These routines can be implemented like routines of the model. The online mode is computational particularly efficient.
     16  1. ''Offline Mode'': In this case the assimilation program is separate from the model. An assimilation program handling the observations and the analysis step of the data assimilation is implemented with PDAF. Then, the model and the assimilation step are executed separately and the information between model and assimilation are exchanged by files. In this case, one does not need to modify the model source code at all. This approach is simpler to implement than the online mode, but it is computationally less efficient.
     17 1. PDAF is called through a well-defined universal standard interface. This allows,  for example, to switch between all ensemble-based filter methods without additional coding.
     18 1. PDAF provides parallelization support for the data assimilation system. If your numerical model is already parallelized, the online mode of PDAF enables the data assimilation system to run several model tasks in parallel within a single executable. However, PDAF can also run small systems on a single processor.
     19 1. PDAF does not require that your model can be called as a subroutine. In the online mode, PDAF is added to the model and the formed data assimilation system can be executed pretty much like the model-program would without data assimilation, but with additional options for the data assimilation.
     20 1. There exist couplings between PDAF with various real models. Such model-couplings are, e.g., available for the MITgcm, NEMO, and SCHISM ocean circulation models, for the AWI Climate Model (a coupled model consisting of either ECHAM or OpenIFS (atmosphere) and FESOM (ocean)) and the Weather and Forecast Model (WRF). See the [wiki:ModelsConnectedToPDAF list of models that were already coupled to PDAF] for an overview.
    2121
    2222== Data Assimilation Methods ==
    2323
    24 PDAF provides the following method for data assimilation. All assimilation methods are fully implemented, optimized and parallelized. In addition, all ensemble-based methods offer an Ensemble-OI mode in which only a single ensemble state needs to be integrated.
     24PDAF provides the following data assimilation methods. All assimilation methods are fully implemented, optimized and parallelized. In addition, all ensemble-based methods offer an Ensemble-OI mode in which only a single ensemble state needs to be integrated.
    2525
    2626=== Ensemble filters and smoothers ===