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    An Idealized Study of Coupled Atmosphere–Ocean 4D-Var in the Presence of Model Error

    Source: Monthly Weather Review:;2016:;volume( 144 ):;issue: 010::page 4007
    Author:
    Fowler, Alison M.
    ,
    Lawless, Amos S.
    DOI: 10.1175/MWR-D-15-0420.1
    Publisher: American Meteorological Society
    Abstract: tmosphere-only and ocean-only variational data assimilation (DA) schemes are able to use window lengths that are optimal for the error growth rate, nonlinearity, and observation density of the respective systems. Typical window lengths are 6?12 h for the atmosphere and 2?10 days for the ocean. However, in the implementation of coupled DA schemes it has been necessary to match the window length of the ocean to that of the atmosphere, which may potentially sacrifice the accuracy of the ocean analysis in order to provide a more balanced coupled state. This paper investigates how extending the window length in the presence of model error affects both the analysis of the coupled state and the initialized forecast when using coupled DA with differing degrees of coupling.Results are illustrated using an idealized single-column model of the coupled atmosphere?ocean system. It is found that the analysis error from an uncoupled DA scheme can be smaller than that from a coupled analysis at the initial time, due to faster error growth in the coupled system. However, this does not necessarily lead to a more accurate forecast due to imbalances in the coupled state. Instead coupled DA is more able to update the initial state to reduce the impact of the model error on the accuracy of the forecast. The effect of model error is potentially most detrimental in the weakly coupled formulation due to the inconsistency between the coupled model used in the outer loop and uncoupled models used in the inner loop.
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      An Idealized Study of Coupled Atmosphere–Ocean 4D-Var in the Presence of Model Error

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4230880
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    contributor authorFowler, Alison M.
    contributor authorLawless, Amos S.
    date accessioned2017-06-09T17:33:42Z
    date available2017-06-09T17:33:42Z
    date copyright2016/10/01
    date issued2016
    identifier issn0027-0644
    identifier otherams-87233.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4230880
    description abstracttmosphere-only and ocean-only variational data assimilation (DA) schemes are able to use window lengths that are optimal for the error growth rate, nonlinearity, and observation density of the respective systems. Typical window lengths are 6?12 h for the atmosphere and 2?10 days for the ocean. However, in the implementation of coupled DA schemes it has been necessary to match the window length of the ocean to that of the atmosphere, which may potentially sacrifice the accuracy of the ocean analysis in order to provide a more balanced coupled state. This paper investigates how extending the window length in the presence of model error affects both the analysis of the coupled state and the initialized forecast when using coupled DA with differing degrees of coupling.Results are illustrated using an idealized single-column model of the coupled atmosphere?ocean system. It is found that the analysis error from an uncoupled DA scheme can be smaller than that from a coupled analysis at the initial time, due to faster error growth in the coupled system. However, this does not necessarily lead to a more accurate forecast due to imbalances in the coupled state. Instead coupled DA is more able to update the initial state to reduce the impact of the model error on the accuracy of the forecast. The effect of model error is potentially most detrimental in the weakly coupled formulation due to the inconsistency between the coupled model used in the outer loop and uncoupled models used in the inner loop.
    publisherAmerican Meteorological Society
    titleAn Idealized Study of Coupled Atmosphere–Ocean 4D-Var in the Presence of Model Error
    typeJournal Paper
    journal volume144
    journal issue10
    journal titleMonthly Weather Review
    identifier doi10.1175/MWR-D-15-0420.1
    journal fristpage4007
    journal lastpage4030
    treeMonthly Weather Review:;2016:;volume( 144 ):;issue: 010
    contenttypeFulltext
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