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    Coupled Ocean–Atmosphere Forecasts in the Presence of Climate Drift

    Source: Monthly Weather Review:;1997:;volume( 125 ):;issue: 005::page 809
    Author:
    Stockdale, Timothy N.
    DOI: 10.1175/1520-0493(1997)125<0809:COAFIT>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: Two different coupled atmosphere?ocean GCMs are used to forecast SST anomalies with lead times of up to one year. The initialization procedure does not balance the ocean and atmosphere components, nor is the coupled model flux corrected to maintain the correct mean state. Rather, the coupled model is allowed to evolve freely during the forecast. The inevitable climate drift is estimated across an ensemble of forecasts and subtracted to give the true forecast. Although the climate drift is often bigger than the interannual signal, the method works. This is true for a drift toward both warmer and colder SSTs, as exemplified by the two models. The best way of establishing the mean bias correction from a small sample of prior forecasts is discussed. In some circumstances the sample median may be a more robust estimator than the sample mean. For the limited set of forecasts here, use of the median bias in the cross-correlated forecasts reduces forecast error, when compared to use of the mean bias.
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      Coupled Ocean–Atmosphere Forecasts in the Presence of Climate Drift

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4203824
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    contributor authorStockdale, Timothy N.
    date accessioned2017-06-09T16:11:16Z
    date available2017-06-09T16:11:16Z
    date copyright1997/05/01
    date issued1997
    identifier issn0027-0644
    identifier otherams-62883.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4203824
    description abstractTwo different coupled atmosphere?ocean GCMs are used to forecast SST anomalies with lead times of up to one year. The initialization procedure does not balance the ocean and atmosphere components, nor is the coupled model flux corrected to maintain the correct mean state. Rather, the coupled model is allowed to evolve freely during the forecast. The inevitable climate drift is estimated across an ensemble of forecasts and subtracted to give the true forecast. Although the climate drift is often bigger than the interannual signal, the method works. This is true for a drift toward both warmer and colder SSTs, as exemplified by the two models. The best way of establishing the mean bias correction from a small sample of prior forecasts is discussed. In some circumstances the sample median may be a more robust estimator than the sample mean. For the limited set of forecasts here, use of the median bias in the cross-correlated forecasts reduces forecast error, when compared to use of the mean bias.
    publisherAmerican Meteorological Society
    titleCoupled Ocean–Atmosphere Forecasts in the Presence of Climate Drift
    typeJournal Paper
    journal volume125
    journal issue5
    journal titleMonthly Weather Review
    identifier doi10.1175/1520-0493(1997)125<0809:COAFIT>2.0.CO;2
    journal fristpage809
    journal lastpage818
    treeMonthly Weather Review:;1997:;volume( 125 ):;issue: 005
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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