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    Retrieval of Snow Properties for Ku- and Ka-Band Dual-Frequency Radar

    Source: Journal of Applied Meteorology and Climatology:;2016:;volume( 055 ):;issue: 009::page 1845
    Author:
    Liao, Liang
    ,
    Meneghini, Robert
    ,
    Tokay, Ali
    ,
    Bliven, Larry F.
    DOI: 10.1175/JAMC-D-15-0355.1
    Publisher: American Meteorological Society
    Abstract: he focus of this study is on the estimation of snow microphysical properties and the associated bulk parameters such as snow water content and water equivalent snowfall rate for Ku- and Ka-band dual-frequency radar. This is done by exploring a suitable scattering model and the proper particle size distribution (PSD) assumption that accurately represent, in the electromagnetic domain, the micro-/macrophysical properties of snow. The scattering databases computed from simulated aggregates for small-to-moderate particle sizes are combined with a simple scattering model for large particle sizes to characterize snow-scattering properties over the full range of particle sizes. With use of the single-scattering results, the snow retrieval lookup tables can be formed in a way that directly links the Ku- and Ka-band radar reflectivities to snow water content and equivalent snowfall rate without use of the derived PSD parameters. A sensitivity study of the retrieval results to the PSD and scattering models is performed to better understand the dual-wavelength retrieval uncertainties. To aid in the development of the Ku- and Ka-band dual-wavelength radar technique and to further evaluate its performance, self-consistency tests are conducted using measurements of the snow PSD and fall velocity acquired from the Snow Video Imager/Particle Image Probe (SVI/PIP) during the winter of 2014 at the NASA Wallops Flight Facility site in Wallops Island, Virginia.
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      Retrieval of Snow Properties for Ku- and Ka-Band Dual-Frequency Radar

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4217646
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    contributor authorLiao, Liang
    contributor authorMeneghini, Robert
    contributor authorTokay, Ali
    contributor authorBliven, Larry F.
    date accessioned2017-06-09T16:51:14Z
    date available2017-06-09T16:51:14Z
    date copyright2016/09/01
    date issued2016
    identifier issn1558-8424
    identifier otherams-75322.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4217646
    description abstracthe focus of this study is on the estimation of snow microphysical properties and the associated bulk parameters such as snow water content and water equivalent snowfall rate for Ku- and Ka-band dual-frequency radar. This is done by exploring a suitable scattering model and the proper particle size distribution (PSD) assumption that accurately represent, in the electromagnetic domain, the micro-/macrophysical properties of snow. The scattering databases computed from simulated aggregates for small-to-moderate particle sizes are combined with a simple scattering model for large particle sizes to characterize snow-scattering properties over the full range of particle sizes. With use of the single-scattering results, the snow retrieval lookup tables can be formed in a way that directly links the Ku- and Ka-band radar reflectivities to snow water content and equivalent snowfall rate without use of the derived PSD parameters. A sensitivity study of the retrieval results to the PSD and scattering models is performed to better understand the dual-wavelength retrieval uncertainties. To aid in the development of the Ku- and Ka-band dual-wavelength radar technique and to further evaluate its performance, self-consistency tests are conducted using measurements of the snow PSD and fall velocity acquired from the Snow Video Imager/Particle Image Probe (SVI/PIP) during the winter of 2014 at the NASA Wallops Flight Facility site in Wallops Island, Virginia.
    publisherAmerican Meteorological Society
    titleRetrieval of Snow Properties for Ku- and Ka-Band Dual-Frequency Radar
    typeJournal Paper
    journal volume55
    journal issue9
    journal titleJournal of Applied Meteorology and Climatology
    identifier doi10.1175/JAMC-D-15-0355.1
    journal fristpage1845
    journal lastpage1858
    treeJournal of Applied Meteorology and Climatology:;2016:;volume( 055 ):;issue: 009
    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
    yabeshDSpacePersian