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    On Constraining Estimates of Climate Sensitivity with Present-Day Observations through Model Weighting

    Source: Journal of Climate:;2011:;volume( 024 ):;issue: 023::page 6092
    Author:
    Klocke, Daniel
    ,
    Pincus, Robert
    ,
    Quaas, Johannes
    DOI: 10.1175/2011JCLI4193.1
    Publisher: American Meteorological Society
    Abstract: he distribution of model-based estimates of equilibrium climate sensitivity has not changed substantially in more than 30 years. Efforts to narrow this distribution by weighting projections according to measures of model fidelity have so far failed, largely because climate sensitivity is independent of current measures of skill in current ensembles of models. This work presents a cautionary example showing that measures of model fidelity that are effective at narrowing the distribution of future projections (because they are systematically related to climate sensitivity in an ensemble of models) may be poor measures of the likelihood that a model will provide an accurate estimate of climate sensitivity (and thus degrade distributions of projections if they are used as weights). Furthermore, it appears unlikely that statistical tests alone can identify robust measures of likelihood. The conclusions are drawn from two ensembles: one obtained by perturbing parameters in a single climate model and a second containing the majority of the world?s climate models. The simple ensemble reproduces many aspects of the multimodel ensemble, including the distributions of skill in reproducing the present-day climatology of clouds and radiation, the distribution of climate sensitivity, and the dependence of climate sensitivity on certain cloud regimes. Weighting by error measures targeted on those regimes permits the development of tighter relationships between climate sensitivity and model error and, hence, narrower distributions of climate sensitivity in the simple ensemble. These relationships, however, do not carry into the multimodel ensemble. This suggests that model weighting based on statistical relationships alone is unfounded and perhaps that climate model errors are still large enough that model weighting is not sensible.
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      On Constraining Estimates of Climate Sensitivity with Present-Day Observations through Model Weighting

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    contributor authorKlocke, Daniel
    contributor authorPincus, Robert
    contributor authorQuaas, Johannes
    date accessioned2017-06-09T16:40:24Z
    date available2017-06-09T16:40:24Z
    date copyright2011/12/01
    date issued2011
    identifier issn0894-8755
    identifier otherams-71966.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4213916
    description abstracthe distribution of model-based estimates of equilibrium climate sensitivity has not changed substantially in more than 30 years. Efforts to narrow this distribution by weighting projections according to measures of model fidelity have so far failed, largely because climate sensitivity is independent of current measures of skill in current ensembles of models. This work presents a cautionary example showing that measures of model fidelity that are effective at narrowing the distribution of future projections (because they are systematically related to climate sensitivity in an ensemble of models) may be poor measures of the likelihood that a model will provide an accurate estimate of climate sensitivity (and thus degrade distributions of projections if they are used as weights). Furthermore, it appears unlikely that statistical tests alone can identify robust measures of likelihood. The conclusions are drawn from two ensembles: one obtained by perturbing parameters in a single climate model and a second containing the majority of the world?s climate models. The simple ensemble reproduces many aspects of the multimodel ensemble, including the distributions of skill in reproducing the present-day climatology of clouds and radiation, the distribution of climate sensitivity, and the dependence of climate sensitivity on certain cloud regimes. Weighting by error measures targeted on those regimes permits the development of tighter relationships between climate sensitivity and model error and, hence, narrower distributions of climate sensitivity in the simple ensemble. These relationships, however, do not carry into the multimodel ensemble. This suggests that model weighting based on statistical relationships alone is unfounded and perhaps that climate model errors are still large enough that model weighting is not sensible.
    publisherAmerican Meteorological Society
    titleOn Constraining Estimates of Climate Sensitivity with Present-Day Observations through Model Weighting
    typeJournal Paper
    journal volume24
    journal issue23
    journal titleJournal of Climate
    identifier doi10.1175/2011JCLI4193.1
    journal fristpage6092
    journal lastpage6099
    treeJournal of Climate:;2011:;volume( 024 ):;issue: 023
    contenttypeFulltext
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