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    An Improved Dual-Polarization Radar Rainfall Algorithm (DROPS2.0): Application in NASA IFloodS Field Campaign

    Source: Journal of Hydrometeorology:;2017:;Volume( 018 ):;issue: 004::page 917
    Author:
    Chen, Haonan
    ,
    Chandrasekar, V.
    ,
    Bechini, Renzo
    DOI: 10.1175/JHM-D-16-0124.1
    Publisher: American Meteorological Society
    Abstract: ompared to traditional single-polarization radar, dual-polarization radar has a number of advantages for quantitative precipitation estimation because more information about the drop size distribution and hydrometeor type can be gleaned. In this paper, an improved dual-polarization rainfall methodology is proposed, which is driven by a region-based hydrometeor classification mechanism. The objective of this study is to incorporate the spatial coherence and self-aggregation of dual-polarization observables in hydrometeor classification and to produce robust rainfall estimates for operational applications. The S-band dual-polarization data collected from the NASA Polarimetric (NPOL) radar during the GPM Iowa Flood Studies (IFloodS) ground validation field campaign are used to demonstrate and evaluate the proposed rainfall algorithm. Results show that the improved rainfall method provides better performance than a few single- and dual-polarization algorithms in previous studies. This paper also investigates the impact of radar beam broadening on various rainfall algorithms. It is found that the radar-based rainfall products are less correlated with ground disdrometer measurements as the distance from the radar increases.
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      An Improved Dual-Polarization Radar Rainfall Algorithm (DROPS2.0): Application in NASA IFloodS Field Campaign

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4225546
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    contributor authorChen, Haonan
    contributor authorChandrasekar, V.
    contributor authorBechini, Renzo
    date accessioned2017-06-09T17:17:15Z
    date available2017-06-09T17:17:15Z
    date copyright2017/04/01
    date issued2017
    identifier issn1525-755X
    identifier otherams-82432.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4225546
    description abstractompared to traditional single-polarization radar, dual-polarization radar has a number of advantages for quantitative precipitation estimation because more information about the drop size distribution and hydrometeor type can be gleaned. In this paper, an improved dual-polarization rainfall methodology is proposed, which is driven by a region-based hydrometeor classification mechanism. The objective of this study is to incorporate the spatial coherence and self-aggregation of dual-polarization observables in hydrometeor classification and to produce robust rainfall estimates for operational applications. The S-band dual-polarization data collected from the NASA Polarimetric (NPOL) radar during the GPM Iowa Flood Studies (IFloodS) ground validation field campaign are used to demonstrate and evaluate the proposed rainfall algorithm. Results show that the improved rainfall method provides better performance than a few single- and dual-polarization algorithms in previous studies. This paper also investigates the impact of radar beam broadening on various rainfall algorithms. It is found that the radar-based rainfall products are less correlated with ground disdrometer measurements as the distance from the radar increases.
    publisherAmerican Meteorological Society
    titleAn Improved Dual-Polarization Radar Rainfall Algorithm (DROPS2.0): Application in NASA IFloodS Field Campaign
    typeJournal Paper
    journal volume18
    journal issue4
    journal titleJournal of Hydrometeorology
    identifier doi10.1175/JHM-D-16-0124.1
    journal fristpage917
    journal lastpage937
    treeJournal of Hydrometeorology:;2017:;Volume( 018 ):;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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