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  2. Machine Learning Methods for Postprocessing Ensemble Forecasts of Wind Gusts: Data
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    Dataset: Machine Learning Methods for Postprocessing Ensemble Forecasts of Wind Gusts: Data

    Alternate identifier:
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    Related identifier:
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    Creator/Author:
    Schulz, Benedikt https://orcid.org/0000-0003-1367-1543 [Institut für Stochastik]

    Lerch, Sebastian https://orcid.org/0000-0002-3467-4375 [Institut für Statistik]
    Contributors:
    (Data Curator)
    Redl, Robert [Redl, Robert]

    (Data Curator)
    Hess, Reinhold [Hess, Reinhold]
    Title:
    Machine Learning Methods for Postprocessing Ensemble Forecasts of Wind Gusts: Data
    Additional titles:
    -
    Description:
    (Abstract) Datensatz zu Schulz und Lerch (2022): "Machine learning methods for postprocessing ensemble forecasts of wind gusts: A systematic comparison", Monthly Weather Review, 150 (1), 235-257, https://doi.org/10.1175/MWR-D-21-0150.1. Die Daten beinhalten die NWV-Vorhersagen und dazugehörigen Beobachtungen ...
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    (Abstract) Data set for Schulz and Lerch (2022): "Machine learning methods for postprocessing ensemble forecasts of wind gusts: A systematic comparison", Monthly Weather Review, 150 (1), 235-257, https://doi.org/10.1175/MWR-D-21-0150.1. The data includes the NWP forecasts and corresponding observations for th...
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    (Technical Remarks) A detailed description of the data is given on the corresponding Github-page (https://github.com/benediktschulz/paper_pp_wind_gusts).
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    Keywords:
    Statistical postprocessing
    wind gusts
    data set
    machine learning
    ensemble forecasts
    numerical weather prediction
    Related information:
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    Language:
    -
    Publishers:
    Karlsruhe Institute of Technology
    Production year:
    Subject areas:
    Mathematics
    Resource type:
    Dataset
    Data source:
    -
    Software used:
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    Data processing:
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    Publication year:
    Rights holders:
    Deutscher Wetterdienst
    Funding:
    -
    Name Storage Metadata Upload Action
    Status:
    Published
    Uploaded by:
    kitopen
    Created on:
    Archiving date:
    2024-05-28
    Archive size:
    37.4 GB
    Archive creator:
    kitopen
    Archive checksum:
    98a75d41fcf5e660085626d754cd209c (MD5)
    Embargo period:
    -