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    On the Reliability of the Rank Histogram

    Source: Monthly Weather Review:;2010:;volume( 139 ):;issue: 001::page 311
    Author:
    Wilks, D. S.
    DOI: 10.1175/2010MWR3446.1
    Publisher: American Meteorological Society
    Abstract: Ensemble consistency is a name for the condition that an observation being forecast by a dynamical ensemble is statistically indistinguishable from the ensemble members. This statistical indistinguishability condition is meaningful only in a multivariate sense. That is, it pertains to the joint distribution of the ensemble members and the observation. The rank histogram has been designed to assess overall ensemble consistency, but mistakenly employing it to assess only restricted aspects of this joint distribution (e.g., the climatological distribution) leads to the incorrect conclusion that the verification rank histogram is not a useful diagnostic for good behavior of ensemble forecasts. The potential confusion is analyzed in the context of an idealized multivariate Gaussian model of forecast ensembles and their corresponding observations, and it is shown that the rank histogram does correctly assess the consistency of forecast ensembles.
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      On the Reliability of the Rank Histogram

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    contributor authorWilks, D. S.
    date accessioned2017-06-09T16:38:17Z
    date available2017-06-09T16:38:17Z
    date copyright2011/01/01
    date issued2010
    identifier issn0027-0644
    identifier otherams-71375.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4213260
    description abstractEnsemble consistency is a name for the condition that an observation being forecast by a dynamical ensemble is statistically indistinguishable from the ensemble members. This statistical indistinguishability condition is meaningful only in a multivariate sense. That is, it pertains to the joint distribution of the ensemble members and the observation. The rank histogram has been designed to assess overall ensemble consistency, but mistakenly employing it to assess only restricted aspects of this joint distribution (e.g., the climatological distribution) leads to the incorrect conclusion that the verification rank histogram is not a useful diagnostic for good behavior of ensemble forecasts. The potential confusion is analyzed in the context of an idealized multivariate Gaussian model of forecast ensembles and their corresponding observations, and it is shown that the rank histogram does correctly assess the consistency of forecast ensembles.
    publisherAmerican Meteorological Society
    titleOn the Reliability of the Rank Histogram
    typeJournal Paper
    journal volume139
    journal issue1
    journal titleMonthly Weather Review
    identifier doi10.1175/2010MWR3446.1
    journal fristpage311
    journal lastpage316
    treeMonthly Weather Review:;2010:;volume( 139 ):;issue: 001
    contenttypeFulltext
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