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    Tensor Formulation of Ensemble-Based Background Error Covariance Matrix Factorization

    Source: Monthly Weather Review:;2015:;volume( 143 ):;issue: 012::page 4963
    Author:
    Ishibashi, Toshiyuki
    DOI: 10.1175/MWR-D-15-0014.1
    Publisher: American Meteorological Society
    Abstract: actorization of a background error covariance matrix (B factorization) constructed from localization matrices and a small ensemble that obeys background error statistics is an efficient method for introducing flow-dependent background error statistics into variational form data assimilation systems. Although there are four types of matrix formulations of B factorization, their derivation processes and relationships are not clarified, and mathematical operability is limited because of their complex matrix forms. In this paper, B factorization in the tensor (component) form is formulated to overcome these shortcomings. The tensor formulation is very simple and directly connects the background error covariance matrix with its factorization. All existing matrix formulations are derived from the tensor formulation as their specific matrix form representations. Using the simplicity of the tensor formulation, the relationships between the strong-constraint four-dimensional variational data assimilation (4DVAR), 4DVAR with the four-dimensional background error covariance, and the weak-constraint 4DVAR are clarified.
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      Tensor Formulation of Ensemble-Based Background Error Covariance Matrix Factorization

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    contributor authorIshibashi, Toshiyuki
    date accessioned2017-06-09T17:32:57Z
    date available2017-06-09T17:32:57Z
    date copyright2015/12/01
    date issued2015
    identifier issn0027-0644
    identifier otherams-87074.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4230703
    description abstractactorization of a background error covariance matrix (B factorization) constructed from localization matrices and a small ensemble that obeys background error statistics is an efficient method for introducing flow-dependent background error statistics into variational form data assimilation systems. Although there are four types of matrix formulations of B factorization, their derivation processes and relationships are not clarified, and mathematical operability is limited because of their complex matrix forms. In this paper, B factorization in the tensor (component) form is formulated to overcome these shortcomings. The tensor formulation is very simple and directly connects the background error covariance matrix with its factorization. All existing matrix formulations are derived from the tensor formulation as their specific matrix form representations. Using the simplicity of the tensor formulation, the relationships between the strong-constraint four-dimensional variational data assimilation (4DVAR), 4DVAR with the four-dimensional background error covariance, and the weak-constraint 4DVAR are clarified.
    publisherAmerican Meteorological Society
    titleTensor Formulation of Ensemble-Based Background Error Covariance Matrix Factorization
    typeJournal Paper
    journal volume143
    journal issue12
    journal titleMonthly Weather Review
    identifier doi10.1175/MWR-D-15-0014.1
    journal fristpage4963
    journal lastpage4973
    treeMonthly Weather Review:;2015:;volume( 143 ):;issue: 012
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian