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    Understanding the CMIP3 Multimodel Ensemble

    Source: Journal of Climate:;2011:;volume( 024 ):;issue: 016::page 4529
    Author:
    Annan, J. D.
    ,
    Hargreaves, J. C.
    DOI: 10.1175/2011JCLI3873.1
    Publisher: American Meteorological Society
    Abstract: he Coupled Model Intercomparison Project phase 3 (CMIP3) multimodel ensemble has been widely utilized for climate research and prediction, but the properties and behavior of the ensemble are not yet fully understood. Here, some investigations are undertaken into various aspects of the ensemble?s behavior, in particular focusing on the performance of the multimodel mean. This study presents an explanation of this phenomenon in the context of the statistically indistinguishable paradigm and also provides a quantitative analysis of the main factors that control how likely the mean is to outperform the models in the ensemble, both individually and collectively. The analyses lend further support to the usage of the paradigm of a statistically indistinguishable ensemble and indicate that the current ensemble size is too small to adequately sample the space from which the models are drawn.
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      Understanding the CMIP3 Multimodel Ensemble

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    contributor authorAnnan, J. D.
    contributor authorHargreaves, J. C.
    date accessioned2017-06-09T16:39:51Z
    date available2017-06-09T16:39:51Z
    date copyright2011/08/01
    date issued2011
    identifier issn0894-8755
    identifier otherams-71802.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4213735
    description abstracthe Coupled Model Intercomparison Project phase 3 (CMIP3) multimodel ensemble has been widely utilized for climate research and prediction, but the properties and behavior of the ensemble are not yet fully understood. Here, some investigations are undertaken into various aspects of the ensemble?s behavior, in particular focusing on the performance of the multimodel mean. This study presents an explanation of this phenomenon in the context of the statistically indistinguishable paradigm and also provides a quantitative analysis of the main factors that control how likely the mean is to outperform the models in the ensemble, both individually and collectively. The analyses lend further support to the usage of the paradigm of a statistically indistinguishable ensemble and indicate that the current ensemble size is too small to adequately sample the space from which the models are drawn.
    publisherAmerican Meteorological Society
    titleUnderstanding the CMIP3 Multimodel Ensemble
    typeJournal Paper
    journal volume24
    journal issue16
    journal titleJournal of Climate
    identifier doi10.1175/2011JCLI3873.1
    journal fristpage4529
    journal lastpage4538
    treeJournal of Climate:;2011:;volume( 024 ):;issue: 016
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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