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    Evaluating the Potential Predictive Utility of Ensemble Forecasts

    Source: Journal of Climate:;1996:;volume( 009 ):;issue: 002::page 260
    Author:
    Anderson, Jeffrey L.
    ,
    Stern, William F.
    DOI: 10.1175/1520-0442(1996)009<0260:ETPPUO>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: A method is presented for determining when an ensemble of model forecasts has the potential to provide some useful information. An ensemble forecast of a particular scale quantity is said to have potential predictive utility when the ensemble forecast distribution is significantly different from an appropriate climatological distribution. Here, the potential predictive utility is measured using Kuiper's statistical test for comparing two discrete distributions. More traditional measures of the potential usefulness of an ensemble forecast based on ensemble mean or variance discard possibly valuable information by making implicit assumptions about the distributions being compared. Application of the potential predictive utility to long integrations of an atmospheric general circulation model in a boundary value problem (an ensemble of Atmospheric Model Intercomparison Project integrations) reveals a number of features about the response of a GCM to observed sea surface temperatures. In particular, the ensemble of forecasts is found to have potential predictive utility over large geographic areas for a number of atmospheric fields during strong El Niño-Southern Oscillation anomalous events. Unfortunately, there are only limited areas of potential predictive utility for near-surface fields and precipitation outside the regions of the tropical oceans. Nevertheless, the method presented here can identify all areas where the GCM ensemble may provide useful information, whereas methods that make assumptions about the distribution of the ensemble forecast variables may not be able to do so.
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      Evaluating the Potential Predictive Utility of Ensemble Forecasts

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    contributor authorAnderson, Jeffrey L.
    contributor authorStern, William F.
    date accessioned2017-06-09T15:29:04Z
    date available2017-06-09T15:29:04Z
    date copyright1996/02/01
    date issued1996
    identifier issn0894-8755
    identifier otherams-4497.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4183922
    description abstractA method is presented for determining when an ensemble of model forecasts has the potential to provide some useful information. An ensemble forecast of a particular scale quantity is said to have potential predictive utility when the ensemble forecast distribution is significantly different from an appropriate climatological distribution. Here, the potential predictive utility is measured using Kuiper's statistical test for comparing two discrete distributions. More traditional measures of the potential usefulness of an ensemble forecast based on ensemble mean or variance discard possibly valuable information by making implicit assumptions about the distributions being compared. Application of the potential predictive utility to long integrations of an atmospheric general circulation model in a boundary value problem (an ensemble of Atmospheric Model Intercomparison Project integrations) reveals a number of features about the response of a GCM to observed sea surface temperatures. In particular, the ensemble of forecasts is found to have potential predictive utility over large geographic areas for a number of atmospheric fields during strong El Niño-Southern Oscillation anomalous events. Unfortunately, there are only limited areas of potential predictive utility for near-surface fields and precipitation outside the regions of the tropical oceans. Nevertheless, the method presented here can identify all areas where the GCM ensemble may provide useful information, whereas methods that make assumptions about the distribution of the ensemble forecast variables may not be able to do so.
    publisherAmerican Meteorological Society
    titleEvaluating the Potential Predictive Utility of Ensemble Forecasts
    typeJournal Paper
    journal volume9
    journal issue2
    journal titleJournal of Climate
    identifier doi10.1175/1520-0442(1996)009<0260:ETPPUO>2.0.CO;2
    journal fristpage260
    journal lastpage269
    treeJournal of Climate:;1996:;volume( 009 ):;issue: 002
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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