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    Comments on “Conditional Exceedance Probabilities”

    Source: Monthly Weather Review:;2011:;volume( 139 ):;issue: 010::page 3322
    Author:
    Bröcker, Jochen
    ,
    Siegert, Stefan
    ,
    Kantz, Holger
    DOI: 10.1175/2011MWR3658.1
    Publisher: American Meteorological Society
    Abstract: n a recent paper, Mason et al. propose a reliability test of ensemble forecasts for a continuous, scalar verification. As noted in the paper, the test relies on a very specific interpretation of ensembles, namely, that the ensemble members represent quantiles of some underlying distribution. This quantile interpretation is not the only interpretation of ensembles, another popular one being the Monte Carlo interpretation. Mason et al. suggest estimating the quantiles in this situation; however, this approach is fundamentally flawed. Errors in the quantile estimates are not independent of the exceedance events, and consequently the conditional exceedance probabilities (CEP) curves are not constant, which is a fundamental assumption of the test. The test would reject reliable forecasts with probability much higher than the test size.
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      Comments on “Conditional Exceedance Probabilities”

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    contributor authorBröcker, Jochen
    contributor authorSiegert, Stefan
    contributor authorKantz, Holger
    date accessioned2017-06-09T16:41:09Z
    date available2017-06-09T16:41:09Z
    date copyright2011/10/01
    date issued2011
    identifier issn0027-0644
    identifier otherams-72199.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4214175
    description abstractn a recent paper, Mason et al. propose a reliability test of ensemble forecasts for a continuous, scalar verification. As noted in the paper, the test relies on a very specific interpretation of ensembles, namely, that the ensemble members represent quantiles of some underlying distribution. This quantile interpretation is not the only interpretation of ensembles, another popular one being the Monte Carlo interpretation. Mason et al. suggest estimating the quantiles in this situation; however, this approach is fundamentally flawed. Errors in the quantile estimates are not independent of the exceedance events, and consequently the conditional exceedance probabilities (CEP) curves are not constant, which is a fundamental assumption of the test. The test would reject reliable forecasts with probability much higher than the test size.
    publisherAmerican Meteorological Society
    titleComments on “Conditional Exceedance Probabilities”
    typeJournal Paper
    journal volume139
    journal issue10
    journal titleMonthly Weather Review
    identifier doi10.1175/2011MWR3658.1
    journal fristpage3322
    journal lastpage3324
    treeMonthly Weather Review:;2011:;volume( 139 ):;issue: 010
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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