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    Variational Assimilation of Precipitation Data Using Moist Convective Parameterization Schemes: A 1D-Var Study

    Source: Monthly Weather Review:;1997:;volume( 125 ):;issue: 011::page 2917
    Author:
    Fillion, Luc
    ,
    Errico, Ronald
    DOI: 10.1175/1520-0493(1997)125<2917:VAOPDU>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: Some basic aspects related to the problem of incorporating moist convective processes in a variational data assimilation framework are considered. The methodology is based on inverse problem theory and is formulated in its simplest context where the adjustment of temperature and humidity fields take place only in the vertical. In contrast to previous studies on the subject, the impact of error statistics from prior information and data sources of information is clarified. The accuracy of linearization of convection operators and the resulting impact in a minimization procedure are examined. The former was investigated using Monte Carlo methods. Versions of two schemes are examined: the Kuo?Anthes scheme and the relaxed Arakawa?Schubert scheme (RAS). It is found, in general, that for nonpathological convective points (i.e., points where convection always remains active during the minimization process), a significant adjustment of convection (and precipitation rate) is realizable within the range of realistic background temperature and specific humidity errors and precipitation rate observation errors. Typically, three to five iterations are sufficient for convergence of the variational algorithm for both convective schemes. The degree of nonlinearity of both schemes appears comparable. The vertical correlation length for the background error temperature field is shown to produce a strong interaction with the RAS scheme in the minimization process where significantly different vertical structures of analysis increments for the temperature field are generated in the vicinity of a critical value of the correlation length.
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      Variational Assimilation of Precipitation Data Using Moist Convective Parameterization Schemes: A 1D-Var Study

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4203960
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    contributor authorFillion, Luc
    contributor authorErrico, Ronald
    date accessioned2017-06-09T16:11:36Z
    date available2017-06-09T16:11:36Z
    date copyright1997/11/01
    date issued1997
    identifier issn0027-0644
    identifier otherams-63004.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4203960
    description abstractSome basic aspects related to the problem of incorporating moist convective processes in a variational data assimilation framework are considered. The methodology is based on inverse problem theory and is formulated in its simplest context where the adjustment of temperature and humidity fields take place only in the vertical. In contrast to previous studies on the subject, the impact of error statistics from prior information and data sources of information is clarified. The accuracy of linearization of convection operators and the resulting impact in a minimization procedure are examined. The former was investigated using Monte Carlo methods. Versions of two schemes are examined: the Kuo?Anthes scheme and the relaxed Arakawa?Schubert scheme (RAS). It is found, in general, that for nonpathological convective points (i.e., points where convection always remains active during the minimization process), a significant adjustment of convection (and precipitation rate) is realizable within the range of realistic background temperature and specific humidity errors and precipitation rate observation errors. Typically, three to five iterations are sufficient for convergence of the variational algorithm for both convective schemes. The degree of nonlinearity of both schemes appears comparable. The vertical correlation length for the background error temperature field is shown to produce a strong interaction with the RAS scheme in the minimization process where significantly different vertical structures of analysis increments for the temperature field are generated in the vicinity of a critical value of the correlation length.
    publisherAmerican Meteorological Society
    titleVariational Assimilation of Precipitation Data Using Moist Convective Parameterization Schemes: A 1D-Var Study
    typeJournal Paper
    journal volume125
    journal issue11
    journal titleMonthly Weather Review
    identifier doi10.1175/1520-0493(1997)125<2917:VAOPDU>2.0.CO;2
    journal fristpage2917
    journal lastpage2942
    treeMonthly Weather Review:;1997:;volume( 125 ):;issue: 011
    contenttypeFulltext
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