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    Characterizing AMV Height-Assignment Error by Comparing Best-Fit Pressure Statistics from the Met Office and ECMWF Data Assimilation Systems

    Source: Journal of Applied Meteorology and Climatology:;2014:;volume( 054 ):;issue: 001::page 225
    Author:
    Salonen, Kirsti
    ,
    Cotton, James
    ,
    Bormann, Niels
    ,
    Forsythe, Mary
    DOI: 10.1175/JAMC-D-14-0025.1
    Publisher: American Meteorological Society
    Abstract: o ensure realistic use of atmospheric motion vector (AMV) observations in data assimilation, the error characteristics of the observation type need to be known and carefully taken into account. Assigning a height to the tracked feature is one of the most significant error sources for AMV observations. In this article, the characteristics of the AMV height-assignment error are studied by comparing model best-fit pressure statistics between the Met Office and ECMWF data assimilation systems. The aim is to provide detailed uncertainty estimates for the assigned pressure and to demonstrate that the best-fit pressure enables reliable estimation of the uncertainties in the AMV height assignment. Typical values for the standard deviation of the difference between the assigned pressure and the best-fit pressure are 50?80 hPa at high levels, 115?165 hPa at midlevels, and 60?125 hPa at low levels, depending on satellite, channel, and height-assignment method. Observed minus best-fit pressure biases are mostly within the range of ±50 hPa. The results are very similar for the Met Office and ECMWF systems, suggesting that the pressure differences are not strongly dependent on the data assimilation system. Furthermore, the findings are in good agreement with the expected characteristics of the height-assignment methods and quality of the observations. Thus, best-fit pressure statistics give reliable information about the uncertainties in the AMV height assignment.
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      Characterizing AMV Height-Assignment Error by Comparing Best-Fit Pressure Statistics from the Met Office and ECMWF Data Assimilation Systems

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    contributor authorSalonen, Kirsti
    contributor authorCotton, James
    contributor authorBormann, Niels
    contributor authorForsythe, Mary
    date accessioned2017-06-09T16:50:15Z
    date available2017-06-09T16:50:15Z
    date copyright2015/01/01
    date issued2014
    identifier issn1558-8424
    identifier otherams-75033.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4217325
    description abstracto ensure realistic use of atmospheric motion vector (AMV) observations in data assimilation, the error characteristics of the observation type need to be known and carefully taken into account. Assigning a height to the tracked feature is one of the most significant error sources for AMV observations. In this article, the characteristics of the AMV height-assignment error are studied by comparing model best-fit pressure statistics between the Met Office and ECMWF data assimilation systems. The aim is to provide detailed uncertainty estimates for the assigned pressure and to demonstrate that the best-fit pressure enables reliable estimation of the uncertainties in the AMV height assignment. Typical values for the standard deviation of the difference between the assigned pressure and the best-fit pressure are 50?80 hPa at high levels, 115?165 hPa at midlevels, and 60?125 hPa at low levels, depending on satellite, channel, and height-assignment method. Observed minus best-fit pressure biases are mostly within the range of ±50 hPa. The results are very similar for the Met Office and ECMWF systems, suggesting that the pressure differences are not strongly dependent on the data assimilation system. Furthermore, the findings are in good agreement with the expected characteristics of the height-assignment methods and quality of the observations. Thus, best-fit pressure statistics give reliable information about the uncertainties in the AMV height assignment.
    publisherAmerican Meteorological Society
    titleCharacterizing AMV Height-Assignment Error by Comparing Best-Fit Pressure Statistics from the Met Office and ECMWF Data Assimilation Systems
    typeJournal Paper
    journal volume54
    journal issue1
    journal titleJournal of Applied Meteorology and Climatology
    identifier doi10.1175/JAMC-D-14-0025.1
    journal fristpage225
    journal lastpage242
    treeJournal of Applied Meteorology and Climatology:;2014:;volume( 054 ):;issue: 001
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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