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    Correspondence among the Correlation, RMSE, and Heidke Forecast Verification Measures; Refinement of the Heidke Score

    Source: Weather and Forecasting:;1992:;volume( 007 ):;issue: 004::page 699
    Author:
    Barnston, Anthony G.
    DOI: 10.1175/1520-0434(1992)007<0699:CATCRA>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: The correspondence among the following three forecast verification scores, based on forecasts and their associated observations, is described: 1) the correlation score, 2) the root-mean-square error (RMSE) score, and 3) the Heidke score (based on categorical matches between forecasts and observations). These relationships are provided to facilitate comparisons among studies of forecast skill that use these differing measures. The Heidke score would be more informative, more ?honest,? and easier to interpret at face value if the severity of categorical errors (i.e., one-class errors versus two-class errors, etc.) were included in the scoring formula. Without taking categorical error severity into account the meaning of Heidke scores depends heavily on the categorical definitions (particularly the number of categories), making intercomparison between Heidke and correlation (or RMSE) scores, or even among Heidke scores, quite difficult. When categorical error severity is taken into account in the Heidke score, its correspondence with other verification measures more closely approximates that of more sophisticated scoring systems such as the experimental LEPS score.
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      Correspondence among the Correlation, RMSE, and Heidke Forecast Verification Measures; Refinement of the Heidke Score

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4163700
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    contributor authorBarnston, Anthony G.
    date accessioned2017-06-09T14:47:16Z
    date available2017-06-09T14:47:16Z
    date copyright1992/12/01
    date issued1992
    identifier issn0882-8156
    identifier otherams-2677.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4163700
    description abstractThe correspondence among the following three forecast verification scores, based on forecasts and their associated observations, is described: 1) the correlation score, 2) the root-mean-square error (RMSE) score, and 3) the Heidke score (based on categorical matches between forecasts and observations). These relationships are provided to facilitate comparisons among studies of forecast skill that use these differing measures. The Heidke score would be more informative, more ?honest,? and easier to interpret at face value if the severity of categorical errors (i.e., one-class errors versus two-class errors, etc.) were included in the scoring formula. Without taking categorical error severity into account the meaning of Heidke scores depends heavily on the categorical definitions (particularly the number of categories), making intercomparison between Heidke and correlation (or RMSE) scores, or even among Heidke scores, quite difficult. When categorical error severity is taken into account in the Heidke score, its correspondence with other verification measures more closely approximates that of more sophisticated scoring systems such as the experimental LEPS score.
    publisherAmerican Meteorological Society
    titleCorrespondence among the Correlation, RMSE, and Heidke Forecast Verification Measures; Refinement of the Heidke Score
    typeJournal Paper
    journal volume7
    journal issue4
    journal titleWeather and Forecasting
    identifier doi10.1175/1520-0434(1992)007<0699:CATCRA>2.0.CO;2
    journal fristpage699
    journal lastpage709
    treeWeather and Forecasting:;1992:;volume( 007 ):;issue: 004
    contenttypeFulltext
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