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    Ocean Data Assimilation, Initialization, and Predictions of ENSO with a Coupled GCM

    Source: Monthly Weather Review:;1999:;volume( 127 ):;issue: 006::page 1187
    Author:
    Schneider, Edwin K.
    ,
    Huang, Bohua
    ,
    Zhu, Zhengxin
    ,
    DeWitt, David G.
    ,
    Kinter, James L.
    ,
    Kirtman, Ben P.
    ,
    Shukla, J.
    DOI: 10.1175/1520-0493(1999)127<1187:ODAIAP>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: A scheme for making seasonal to interannual predictions of El Niño?Southern Oscillation with a coupled atmosphere?ocean general circulation model that incorporates subsurface ocean measurements in the initial conditions is described. Anomaly initial conditions are used in order to reduce initial shock and climate drift. The ocean component of the prediction model has a nearly global domain, and the coupled model does not employ anomaly coupling or empirical statistical corrections. Initial conditions for the ocean were obtained from a near-global ocean analysis produced by an ocean data assimilation system. The assimilation system uses a variationally formulated optimal interpolation method to analyze oceanic fields from temperature observations and a first-guess field provided by integrating a global ocean general circulation model. The period of the analysis was 1986 through 1992. The anomaly initial conditions for the ocean were generated by adding the anomalies of the assimilated fields from the assimilation climatology to the coupled model climatology. A series of 28 1-yr hindcast experiments, four each year for the years 1986?1992, was carried out to test the scheme. The hindcasts show considerable skill in the equatorial Pacific.
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      Ocean Data Assimilation, Initialization, and Predictions of ENSO with a Coupled GCM

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4204295
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    • Monthly Weather Review

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    contributor authorSchneider, Edwin K.
    contributor authorHuang, Bohua
    contributor authorZhu, Zhengxin
    contributor authorDeWitt, David G.
    contributor authorKinter, James L.
    contributor authorKirtman, Ben P.
    contributor authorShukla, J.
    date accessioned2017-06-09T16:12:25Z
    date available2017-06-09T16:12:25Z
    date copyright1999/06/01
    date issued1999
    identifier issn0027-0644
    identifier otherams-63306.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4204295
    description abstractA scheme for making seasonal to interannual predictions of El Niño?Southern Oscillation with a coupled atmosphere?ocean general circulation model that incorporates subsurface ocean measurements in the initial conditions is described. Anomaly initial conditions are used in order to reduce initial shock and climate drift. The ocean component of the prediction model has a nearly global domain, and the coupled model does not employ anomaly coupling or empirical statistical corrections. Initial conditions for the ocean were obtained from a near-global ocean analysis produced by an ocean data assimilation system. The assimilation system uses a variationally formulated optimal interpolation method to analyze oceanic fields from temperature observations and a first-guess field provided by integrating a global ocean general circulation model. The period of the analysis was 1986 through 1992. The anomaly initial conditions for the ocean were generated by adding the anomalies of the assimilated fields from the assimilation climatology to the coupled model climatology. A series of 28 1-yr hindcast experiments, four each year for the years 1986?1992, was carried out to test the scheme. The hindcasts show considerable skill in the equatorial Pacific.
    publisherAmerican Meteorological Society
    titleOcean Data Assimilation, Initialization, and Predictions of ENSO with a Coupled GCM
    typeJournal Paper
    journal volume127
    journal issue6
    journal titleMonthly Weather Review
    identifier doi10.1175/1520-0493(1999)127<1187:ODAIAP>2.0.CO;2
    journal fristpage1187
    journal lastpage1207
    treeMonthly Weather Review:;1999:;volume( 127 ):;issue: 006
    contenttypeFulltext
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