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    Further Statistics of Precipitation Probability Forecasts

    Source: Journal of Applied Meteorology:;1977:;volume( 016 ):;issue: 011::page 1231
    Author:
    Paegle, Julia N.
    ,
    Wright, Robert P.
    ,
    De Nevers, Klancy
    ,
    Keir, Marilyn
    DOI: 10.1175/1520-0450(1977)016<1231:FSOPPF>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: A nonparametric technique based on a pattern recognition algorithm is used to forecast the probability of precipitation for 42 stations over the western United States. Mean-square errors or Brier scores between forecasted values and observed precipitation are obtained for an independent data sample. These mean-square errors are compared with those obtained from linear regression equations and climatology for the same data set. The skill of this technique is comparable with that of the linear regression equations and is considerably better than that of climatological forecasts.
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      Further Statistics of Precipitation Probability Forecasts

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4232827
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    • Journal of Applied Meteorology

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    contributor authorPaegle, Julia N.
    contributor authorWright, Robert P.
    contributor authorDe Nevers, Klancy
    contributor authorKeir, Marilyn
    date accessioned2017-06-09T17:39:13Z
    date available2017-06-09T17:39:13Z
    date copyright1977/11/01
    date issued1977
    identifier issn0021-8952
    identifier otherams-9349.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4232827
    description abstractA nonparametric technique based on a pattern recognition algorithm is used to forecast the probability of precipitation for 42 stations over the western United States. Mean-square errors or Brier scores between forecasted values and observed precipitation are obtained for an independent data sample. These mean-square errors are compared with those obtained from linear regression equations and climatology for the same data set. The skill of this technique is comparable with that of the linear regression equations and is considerably better than that of climatological forecasts.
    publisherAmerican Meteorological Society
    titleFurther Statistics of Precipitation Probability Forecasts
    typeJournal Paper
    journal volume16
    journal issue11
    journal titleJournal of Applied Meteorology
    identifier doi10.1175/1520-0450(1977)016<1231:FSOPPF>2.0.CO;2
    journal fristpage1231
    journal lastpage1234
    treeJournal of Applied Meteorology:;1977:;volume( 016 ):;issue: 011
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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