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    Comparison of Surface Wind and Temperature Analyses from an Ensemble Kalman Filter and the NWS Real-Time Mesoscale Analysis System

    Source: Weather and Forecasting:;2014:;volume( 029 ):;issue: 004::page 1058
    Author:
    Ancell, Brian C.
    ,
    Mass, Clifford F.
    ,
    Cook, Kirby
    ,
    Colman, Brad
    DOI: 10.1175/WAF-D-13-00139.1
    Publisher: American Meteorological Society
    Abstract: perational, high-resolution analyses are a vital part of the National Weather Service (NWS) forecasting process. Currently, the Real-Time Mesoscale Analysis (RTMA) system fills this need by providing hourly analyses using a two-dimensional variational assimilation scheme. While success has been shown with the RTMA, an ensemble Kalman filter (EnKF) approach should outperform the RTMA, since the EnKF utilizes purely flow-dependent covariances during assimilation. The purpose of this study is to compare surface wind and temperature analyses from an EnKF to those of the RTMA to determine the relative skill of each approach. To reveal the influence of complex terrain, comparisons are performed for both the U.S. Pacific Northwest and Midwest. As expected, EnKF analysis increments reveal structures that align with the instantaneous flow, particularly regarding the wind field, for which the EnKF produces superior analyses. The EnKF is no better than the RTMA in strongly varying terrain, which may be a result of enhanced representativeness error in such regions. In contrast, temperature analysis increments are far less sensitive to flow dependence and are similar for both the EnKF and RTMA. RTMA temperature analyses possess slightly better skill than those produced by the EnKF, likely due to sampling error within the EnKF. Similar results for wind and temperature are found when assimilating significantly more and less observations in both systems. The implications of these results for operational production of finescale analyses are discussed.
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      Comparison of Surface Wind and Temperature Analyses from an Ensemble Kalman Filter and the NWS Real-Time Mesoscale Analysis System

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4231737
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    contributor authorAncell, Brian C.
    contributor authorMass, Clifford F.
    contributor authorCook, Kirby
    contributor authorColman, Brad
    date accessioned2017-06-09T17:36:32Z
    date available2017-06-09T17:36:32Z
    date copyright2014/08/01
    date issued2014
    identifier issn0882-8156
    identifier otherams-88004.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4231737
    description abstractperational, high-resolution analyses are a vital part of the National Weather Service (NWS) forecasting process. Currently, the Real-Time Mesoscale Analysis (RTMA) system fills this need by providing hourly analyses using a two-dimensional variational assimilation scheme. While success has been shown with the RTMA, an ensemble Kalman filter (EnKF) approach should outperform the RTMA, since the EnKF utilizes purely flow-dependent covariances during assimilation. The purpose of this study is to compare surface wind and temperature analyses from an EnKF to those of the RTMA to determine the relative skill of each approach. To reveal the influence of complex terrain, comparisons are performed for both the U.S. Pacific Northwest and Midwest. As expected, EnKF analysis increments reveal structures that align with the instantaneous flow, particularly regarding the wind field, for which the EnKF produces superior analyses. The EnKF is no better than the RTMA in strongly varying terrain, which may be a result of enhanced representativeness error in such regions. In contrast, temperature analysis increments are far less sensitive to flow dependence and are similar for both the EnKF and RTMA. RTMA temperature analyses possess slightly better skill than those produced by the EnKF, likely due to sampling error within the EnKF. Similar results for wind and temperature are found when assimilating significantly more and less observations in both systems. The implications of these results for operational production of finescale analyses are discussed.
    publisherAmerican Meteorological Society
    titleComparison of Surface Wind and Temperature Analyses from an Ensemble Kalman Filter and the NWS Real-Time Mesoscale Analysis System
    typeJournal Paper
    journal volume29
    journal issue4
    journal titleWeather and Forecasting
    identifier doi10.1175/WAF-D-13-00139.1
    journal fristpage1058
    journal lastpage1075
    treeWeather and Forecasting:;2014:;volume( 029 ):;issue: 004
    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
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