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    Comprehensive Framework for Assessment of Radar-Based Precipitation Data Estimates

    Source: Journal of Hydrologic Engineering:;2017:;Volume ( 022 ):;issue: 005
    Author:
    Ramesh S. V. Teegavarapu
    ,
    Aneesh Goly
    ,
    Qinglong Wu
    DOI: 10.1061/(ASCE)HE.1943-5584.0001277
    Publisher: American Society of Civil Engineers
    Abstract: Assessment of radar-based precipitation estimates using rain gauge observations is a critical exercise in evaluating pre-and postcorrected (gauge-adjusted) radar-based precipitation data. A comprehensive assessment framework combining several visual, quantitative, and statistical measures, indexes, and skill scores is proposed and developed for evaluation of radar-based precipitation estimates in space and time. Contingency measures, skill scores, and a few new metrics are proposed and are evaluated along with several indexes. Visual measures provide a quick check of agreement between radar and rain gauge data sets. Quantitative measures provide information about errors, and skill scores assess the quality of radar data for dichotomous (rain and no-rain) events. Summary statistics and hypothesis tests in statistical categories provide insights into distributional aspects of the rain gauge and radar data sets. The framework is used for evaluation of 15-min radar-based precipitation data obtained from the South Florida Water Management District (SFWMD). Four years of radar and rain gauge data available at 189 sites are used for analysis. Results suggest that radar data in the SFWMD region have progressively improved during the period of analysis. All indexes and skill scores used in the current study suggest that radar data are of good quality at different temporal resolutions and in agreement with rain gauge data. However, spatial bias evaluation suggests that radar data underestimate precipitation amounts in two areas of the SFWMD region.
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      Comprehensive Framework for Assessment of Radar-Based Precipitation Data Estimates

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    contributor authorRamesh S. V. Teegavarapu
    contributor authorAneesh Goly
    contributor authorQinglong Wu
    date accessioned2017-05-08T22:25:24Z
    date available2017-05-08T22:25:24Z
    date copyrightMay 2017
    date issued2017
    identifier other44399079.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/80355
    description abstractAssessment of radar-based precipitation estimates using rain gauge observations is a critical exercise in evaluating pre-and postcorrected (gauge-adjusted) radar-based precipitation data. A comprehensive assessment framework combining several visual, quantitative, and statistical measures, indexes, and skill scores is proposed and developed for evaluation of radar-based precipitation estimates in space and time. Contingency measures, skill scores, and a few new metrics are proposed and are evaluated along with several indexes. Visual measures provide a quick check of agreement between radar and rain gauge data sets. Quantitative measures provide information about errors, and skill scores assess the quality of radar data for dichotomous (rain and no-rain) events. Summary statistics and hypothesis tests in statistical categories provide insights into distributional aspects of the rain gauge and radar data sets. The framework is used for evaluation of 15-min radar-based precipitation data obtained from the South Florida Water Management District (SFWMD). Four years of radar and rain gauge data available at 189 sites are used for analysis. Results suggest that radar data in the SFWMD region have progressively improved during the period of analysis. All indexes and skill scores used in the current study suggest that radar data are of good quality at different temporal resolutions and in agreement with rain gauge data. However, spatial bias evaluation suggests that radar data underestimate precipitation amounts in two areas of the SFWMD region.
    publisherAmerican Society of Civil Engineers
    titleComprehensive Framework for Assessment of Radar-Based Precipitation Data Estimates
    typeJournal Paper
    journal volume22
    journal issue5
    journal titleJournal of Hydrologic Engineering
    identifier doi10.1061/(ASCE)HE.1943-5584.0001277
    treeJournal of Hydrologic Engineering:;2017:;Volume ( 022 ):;issue: 005
    contenttypeFulltext
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