Changes between Version 82 and Version 83 of FeaturesofPdaf


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Timestamp:
Dec 9, 2021, 4:12:29 PM (2 years ago)
Author:
lnerger
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  • FeaturesofPdaf

    v82 v83  
    33[[PageOutline]]
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    5  * PDAF is implemented in Fortran90 with some features from Fortran 2003. The standard interface also supports models that are written in other languages like C or C++. ALso the combination is Python is possible.
     5 * PDAF is implemented in Fortran90 with some features from Fortran 2003. The standard interface also supports models that are written in other languages like C or C++. Also the combination is Python is possible.
    66 * The parallelization uses the MPI (Message Passing Interface) standard. The localized filters use, in addition, OpenMP-parallelization with features of OpenMP-4.
    77 * The core routines are fully independent of the model code. They can be compiled separately and can be used as a library.
     
    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. Further nonlienar filters are provided.
     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.
    1414 1. PDAF is 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.
    1515 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.
     
    2222== Filter algorithms ==
    2323
    24 PDAF provides the following algorithms for data assimilation. All filters are fully implemented, optimized and parallelized.
     24PDAF provides the following algorithms for data assimilation. All filters are fully implemented, optimized and parallelized. In addition, all filters offer an Ensemble-OI mode in which only a single emseble state needs to be integrated
    2525
    2626Local filters:
     
    4040 * PF (Particle filter with resampling, added in version 1.14)
    4141
    42 Starting from version 1.9 of PDAF, smoothers algorithms are provided for the following algorithms
     42Smoother algorithms are provided for the following algorithms
    4343 * ESTKF & LESTKF
    4444 * ETKF & LETKF
     
    4646 * NETF & LNETF (added in version 1.12)
    4747
     48Starting from Version 2.0 of PDAF, 3D variational methods are also provided. The 3D-Var methods are implemented in incremental form using a control vector transformation (following the review by R. Bannister, Q. J. Roy. Meteorol. Soc., 2017) in three different variants:
     49 * 3D-Var - 3D-Var with parameterized covariance matrix
     50 * 3DEnVar - 3D-Var using ensemble covariance matrix. The ensemble perturbations are updated with either the LESTKF and ESTKF filters
     51 * Hyb3DVar - Hybrid 3D-Var using a combination of parameterized and ensemble covariance matrix. The ensemble perturbations are updated with either the LESTKF and ESTKF filters
     52
    4853== Requirements ==
    4954
    5055 * '''Compiler'''[[BR]]To compile PDAF a Fortran compiler is required which supports Fortran 2003. PDAF has been tested with a variety of compilers like gfortran, ifort, xlf, pgf90, cce.
    5156 * '''BLAS''' and '''LAPACK'''[[BR]]The BLAS and LAPACK libraries are used by PDAF. For Linux there are usually packages with these libraries. With commercial compilers the functions are usually provided by optimized libraries (like MKL, ESSL).
    52  * '''MPI''' (optional) [[BR]]If the assimilation program should be executed with parallelization, an MPI library is required (e.g. OpenMPI). The assimilation program can also be compiled and run without parallelization. For this, PDAF provides functions that mimic MPI operations for a single process.
     57 * '''MPI''' [[BR]] An MPI library is required (e.g. OpenMPI). [For the PDAF versions before V2.0, the assimilation program can also be compiled and run without parallelization. For this, PDAF <2.0 provides functions that mimic MPI operations for a single process.]
    5358 * '''make'''[[BR]]PDAF provides Makefile definitions for different compilers and operating systems.
    5459
     
    8994 || FESOM ||Finite Element Sea-ice Ocean Model, see e.g. Nerger et al., 2006, Janjic et al. 2011, Androsov et al. 2019 || model binding available as part of AWI-CM included since PDAF V1.15 ||
    9095 || HBM ||Hiromb-Boos Model, see Nerger et al., 2016 ||
     96 || HYSPLIT ||Volcanic ash transport and dispersion model, see Pardini et al., 2020 ||
    9197 || Lorenz-96 || the low-dimensional chaotic test model for data assimilation (also known as Lorenz-40 or Lorenz-95) || included in PDAF release ||
    9298 || Lorenz-63 || the 3-variable chaotic system by Lorenz (1963) || included in PDAF release ||
     99 || Lorenz-2005 II || Model variant II of Lorenz (2005) || included in PDAF release since PDAF V2.0 ||
     100 || Lorenz-2005 III || the two-scale model variant III of Lorenz (2005) || included in PDAF release since PDAF V2.0 ||
    93101 || MITgcm ||ocean circulation model, see e.g. Yang et al., 2014-2016,|| model binding included since PDAF V1.13 ||
    94102 || MPI-ESM ||The MPI Earth-System Model, see Brune et al. 2015 ||