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    The National Meteorological Center's Spectral Statistical-Interpolation Analysis System 

    Source: Monthly Weather Review:;1992:;volume( 120 ):;issue: 008:;page 1747
    Author(s): Parrish, David F.; Derber, John C.
    Publisher: American Meteorological Society
    Abstract: At the National Meteorological Center (NMC), a new analysis system is being extensively tested for possible use in the operational global data assimilation system. This analysis system is called the spectral statistical- ...
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    Evolution of the NMC Data Assimilation System: September 1978–January 1982 

    Source: Monthly Weather Review:;1982:;volume( 110 ):;issue: 010:;page 1335
    Author(s): Kistler, Robert E.; Parrish, David F.
    Publisher: American Meteorological Society
    Abstract: The evolution of the NMC global data assimilation system in the period 1978?81 is presented. The improvements include revisions to the analysis programs and the replacement of the initialization and the prediction model. ...
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    The Behavior of Forecast Error Covariances for a Kalman Filter in Two Dimensions 

    Source: Monthly Weather Review:;1990:;volume( 119 ):;issue: 008:;page 1757
    Author(s): Cohn, Stephen E.; Parrish, David F.
    Publisher: American Meteorological Society
    Abstract: A Kalman filter algorithm is implemented for a linearized shallow-water model over the continental United States. It is used to assimilate simulated data from the existing radiosonde network, from the demonstration network ...
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    Three-Dimensional Variational Analysis with Spatially Inhomogeneous Covariances 

    Source: Monthly Weather Review:;2002:;volume( 130 ):;issue: 012:;page 2905
    Author(s): Wu, Wan-Shu; Purser, R. James; Parrish, David F.
    Publisher: American Meteorological Society
    Abstract: In this study, a global three-dimensional variational analysis system is formulated in model grid space. This formulation allows greater flexibility (e.g., inhomogeneity and anisotropy) for background error statistics. A ...
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    Retrieval of Moisture from Simulated GPS Slant-Path Water Vapor Observations Using 3DVAR with Anisotropic Recursive Filters 

    Source: Monthly Weather Review:;2007:;volume( 135 ):;issue: 004:;page 1506
    Author(s): Liu, Haixia; Xue, Ming; Purser, R. James; Parrish, David F.
    Publisher: American Meteorological Society
    Abstract: Anisotropic recursive filters are implemented within a three-dimensional variational data assimilation (3DVAR) framework to efficiently model the effect of flow-dependent background error covariance. The background error ...
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    Regional Ensemble–Variational Data Assimilation Using Global Ensemble Forecasts 

    Source: Weather and Forecasting:;2016:;volume( 032 ):;issue: 001:;page 83
    Author(s): Wu, Wan-Shu; Parrish, David F.; Rogers, Eric; Lin, Ying
    Publisher: American Meteorological Society
    Abstract: t the National Centers for Environmental Prediction, the global ensemble forecasts from the ensemble Kalman filter scheme in the Global Forecast System are applied in a regional three-dimensional (3D) and a four dimensional ...
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    The New Global Operational Analysis System at the National Meteorological Center 

    Source: Weather and Forecasting:;1991:;volume( 006 ):;issue: 004:;page 538
    Author(s): Derber, John C.; Parrish, David F.; Lord, Stephen J.
    Publisher: American Meteorological Society
    Abstract: At the National Meteorological Center (NMC), a new analysis system was implemented into the operational Global Data Assimilation System on 25 June 1991. This analysis system is referred to as Spectral Statistical Interpolation ...
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    GSI 3DVar-Based Ensemble–Variational Hybrid Data Assimilation for NCEP Global Forecast System: Single-Resolution Experiments 

    Source: Monthly Weather Review:;2013:;volume( 141 ):;issue: 011:;page 4098
    Author(s): Wang, Xuguang; Parrish, David; Kleist, Daryl; Whitaker, Jeffrey
    Publisher: American Meteorological Society
    Abstract: n ensemble Kalman filter?variational hybrid data assimilation system based on the gridpoint statistical interpolation (GSI) three-dimensional variational data assimilation (3DVar) system was developed. The performance of ...
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    Four-Dimensional Variational Data Assimilation for the Blizzard of 2000 

    Source: Monthly Weather Review:;2002:;volume( 130 ):;issue: 008:;page 1967
    Author(s): Zupanski, Milija; Zupanski, Dusanka; Parrish, David F.; Rogers, Eric; DiMego, Geoffrey
    Publisher: American Meteorological Society
    Abstract: Four-dimensional variational (4DVAR) data assimilation experiments for the East Coast winter storm of 25 January 2000 (i.e., ?blizzard of 2000?) were performed. This storm has received wide attention in the United States, ...
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    The Use of Bred Vectors in the NCEP Global 3D Variational Analysis System 

    Source: Weather and Forecasting:;1997:;volume( 012 ):;issue: 003:;page 689
    Author(s): Pu, Zhao-Xia; Kalnay, Eugenia; Parrish, David; Wu, Wanshu; Toth, Zoltan
    Publisher: American Meteorological Society
    Abstract: The errors in the first-guess (forecast field) of an analysis system vary from day to day, but, as in all current operational data assimilation systems, forecast error covariances are assumed to be constant in time in the ...
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    DSpace software copyright © 2002-2015  DuraSpace
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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
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