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    Assimilation of Geosat Altimeter Data for the Agulhas Current Using the Ensemble Kalman Filter with a Quasigeostrophic Model

    Source: Monthly Weather Review:;1996:;volume( 124 ):;issue: 001::page 85
    Author:
    Evensen, Geir
    ,
    van Leeuwen, Peter Jan
    DOI: 10.1175/1520-0493(1996)124<0085:AOGADF>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: The ring-shedding process in the Agulhas Current is studied using the ensemble Kalman filter to assimilate Geosat altimeter data into a two-layer quasigeostrophic ocean model. The properties of the ensemble Kalman filter are further explored with focus on the analysis scheme and the use of gridded data. The Geosat data consist of 10 fields of gridded sea surface height anomalies separated 10 days apart that are added to a climatic mean field. This corresponds to a huge number of data values, and a data reduction scheme must be applied to increase the efficiency of the analysis procedure. Further, it is illustrated how one can resolve the rank problem occurring when a too large dataset or a small ensemble is used.
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      Assimilation of Geosat Altimeter Data for the Agulhas Current Using the Ensemble Kalman Filter with a Quasigeostrophic Model

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4203574
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    • Monthly Weather Review

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    contributor authorEvensen, Geir
    contributor authorvan Leeuwen, Peter Jan
    date accessioned2017-06-09T16:10:37Z
    date available2017-06-09T16:10:37Z
    date copyright1996/01/01
    date issued1996
    identifier issn0027-0644
    identifier otherams-62658.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4203574
    description abstractThe ring-shedding process in the Agulhas Current is studied using the ensemble Kalman filter to assimilate Geosat altimeter data into a two-layer quasigeostrophic ocean model. The properties of the ensemble Kalman filter are further explored with focus on the analysis scheme and the use of gridded data. The Geosat data consist of 10 fields of gridded sea surface height anomalies separated 10 days apart that are added to a climatic mean field. This corresponds to a huge number of data values, and a data reduction scheme must be applied to increase the efficiency of the analysis procedure. Further, it is illustrated how one can resolve the rank problem occurring when a too large dataset or a small ensemble is used.
    publisherAmerican Meteorological Society
    titleAssimilation of Geosat Altimeter Data for the Agulhas Current Using the Ensemble Kalman Filter with a Quasigeostrophic Model
    typeJournal Paper
    journal volume124
    journal issue1
    journal titleMonthly Weather Review
    identifier doi10.1175/1520-0493(1996)124<0085:AOGADF>2.0.CO;2
    journal fristpage85
    journal lastpage96
    treeMonthly Weather Review:;1996:;volume( 124 ):;issue: 001
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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