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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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