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    Impacts of Beam Broadening and Earth Curvature on Storm-Scale 3D Variational Data Assimilation of Radial Velocity with Two Doppler Radars

    Source: Journal of Atmospheric and Oceanic Technology:;2009:;volume( 027 ):;issue: 004::page 617
    Author:
    Ge, Guoqing
    ,
    Gao, Jidong
    ,
    Brewster, Keith
    ,
    Xue, Ming
    DOI: 10.1175/2009JTECHA1359.1
    Publisher: American Meteorological Society
    Abstract: The radar ray path and beam broadening equations are important for assimilation of radar data into numerical weather prediction (NWP) models. They can be used to determine the physical location of each radar measurement and to properly map the atmospheric state variables from the model grid to the radar measurement space as part of the forward observation operators. Historically, different degrees of approximations have been made with these equations; however, no systematic evaluation of their impact exists, at least in the context of variational data assimilation. This study examines the effects of simplifying ray path and ray broadening calculations on the radar data assimilation in a 3D variational data assimilation (3DVAR) system. Several groups of Observational System Simulation Experiments (OSSEs) are performed to test the impact of these equations to radar data assimilation with an idealized tornadic thunderstorm case. This study shows that the errors caused by simplifications vary with the distance between the analyzed storm and the radar. For single time level wind analysis, as the surface range increases, the impact of beam broadening on analyzed wind field becomes evident and can cause relatively large error for distances beyond 150 km. The impact of the earth?s curvature is more significant, even for distances beyond 60 km, because it places the data at the wrong vertical location. The impact of refractive index gradient is also tested. It is shown that the variations of refractive index gradient have a very small impact on the wind analysis results. Two time series of 1-h-long data assimilation experiments are further conducted to illustrate the impact of the beam broadening and earth curvature on all retrieved model variables. It is shown that all model variables can be retrieved to some degrees in all data assimilation experiments. Similar to the wind analysis experiments, the impacts of both factors are not obvious when radars are relatively close to the storm. When the radars are far from the storm (especially beyond 150 km), overlooking beam broadening degrades the accuracy of assimilation results slightly, whereas ignoring the earth?s curvature leads to significant errors.
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      Impacts of Beam Broadening and Earth Curvature on Storm-Scale 3D Variational Data Assimilation of Radial Velocity with Two Doppler Radars

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4211041
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    contributor authorGe, Guoqing
    contributor authorGao, Jidong
    contributor authorBrewster, Keith
    contributor authorXue, Ming
    date accessioned2017-06-09T16:31:25Z
    date available2017-06-09T16:31:25Z
    date copyright2010/04/01
    date issued2009
    identifier issn0739-0572
    identifier otherams-69379.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4211041
    description abstractThe radar ray path and beam broadening equations are important for assimilation of radar data into numerical weather prediction (NWP) models. They can be used to determine the physical location of each radar measurement and to properly map the atmospheric state variables from the model grid to the radar measurement space as part of the forward observation operators. Historically, different degrees of approximations have been made with these equations; however, no systematic evaluation of their impact exists, at least in the context of variational data assimilation. This study examines the effects of simplifying ray path and ray broadening calculations on the radar data assimilation in a 3D variational data assimilation (3DVAR) system. Several groups of Observational System Simulation Experiments (OSSEs) are performed to test the impact of these equations to radar data assimilation with an idealized tornadic thunderstorm case. This study shows that the errors caused by simplifications vary with the distance between the analyzed storm and the radar. For single time level wind analysis, as the surface range increases, the impact of beam broadening on analyzed wind field becomes evident and can cause relatively large error for distances beyond 150 km. The impact of the earth?s curvature is more significant, even for distances beyond 60 km, because it places the data at the wrong vertical location. The impact of refractive index gradient is also tested. It is shown that the variations of refractive index gradient have a very small impact on the wind analysis results. Two time series of 1-h-long data assimilation experiments are further conducted to illustrate the impact of the beam broadening and earth curvature on all retrieved model variables. It is shown that all model variables can be retrieved to some degrees in all data assimilation experiments. Similar to the wind analysis experiments, the impacts of both factors are not obvious when radars are relatively close to the storm. When the radars are far from the storm (especially beyond 150 km), overlooking beam broadening degrades the accuracy of assimilation results slightly, whereas ignoring the earth?s curvature leads to significant errors.
    publisherAmerican Meteorological Society
    titleImpacts of Beam Broadening and Earth Curvature on Storm-Scale 3D Variational Data Assimilation of Radial Velocity with Two Doppler Radars
    typeJournal Paper
    journal volume27
    journal issue4
    journal titleJournal of Atmospheric and Oceanic Technology
    identifier doi10.1175/2009JTECHA1359.1
    journal fristpage617
    journal lastpage636
    treeJournal of Atmospheric and Oceanic Technology:;2009:;volume( 027 ):;issue: 004
    contenttypeFulltext
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