Downscaling near-surface atmospheric fields with multi-objective Genetic Programming

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@Article{Zerenner:2016:EMS,
  author =       "Tanja Zerenner and Victor Venema and 
                 Petra Friederichs and Clemens Simmer",
  title =        "Downscaling near-surface atmospheric fields with
                 multi-objective Genetic Programming",
  journal =      "Environmental Modelling \& Software",
  year =         "2016",
  volume =       "84",
  number =       "Supplement C",
  pages =        "85--98",
  keywords =     "genetic algorithms, genetic programming, Statistical
                 downscaling, Disaggregation, Evolutionary computation,
                 Machine learning, Pareto optimality, Coupled
                 modelling",
  ISSN =         "1364-8152",
  URL =          "http://www.sciencedirect.com/science/article/pii/S1364815216302122",
  DOI =          "doi:10.1016/j.envsoft.2016.06.009",
  abstract =     "We present a new Genetic Programming based method to
                 derive downscaling rules (i.e., functions or short
                 programs) generating realistic high-resolution fields
                 of atmospheric state variables near the surface given
                 coarser-scale atmospheric information and
                 high-resolution information on land surface properties.
                 Such downscaling rules can be applied in coupled
                 subsurface-land surface-atmosphere simulations or to
                 generate high-resolution atmospheric input data for
                 off-line applications of land surface and subsurface
                 models. Multiple features of the high-resolution
                 fields, such as the spatial distribution of
                 subgrid-scale variance, serve as objectives. The
                 downscaling rules take an interpretable form and
                 contain on average about 5 mathematical operations. The
                 method is applied to downscale ten m-temperature fields
                 from 2.8km to 400m grid resolution. A large part of the
                 spatial variability is reproduced, also in stable night
                 time situations, which generate very heterogeneous
                 near-surface temperature fields in regions with
                 distinct topography",
  notes =        "See also \cite{journals/corr/ZerennerVFS14}. Also
                 known as \cite{ZERENNER201685}",
}

Genetic Programming entries for Tanja Zerenner Victor Venema Petra Friederichs Clemens Simmer

Citations