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    The Science of NOAA's Operational Hydrologic Ensemble Forecast Service

    Source: Bulletin of the American Meteorological Society:;2013:;volume( 095 ):;issue: 001::page 79
    Author:
    Demargne, Julie
    ,
    Wu, Limin
    ,
    Regonda, Satish K.
    ,
    Brown, James D.
    ,
    Lee, Haksu
    ,
    He, Minxue
    ,
    Seo, Dong-Jun
    ,
    Hartman, Robert
    ,
    Herr, Henry D.
    ,
    Fresch, Mark
    ,
    Schaake, John
    ,
    Zhu, Yuejian
    DOI: 10.1175/BAMS-D-12-00081.1
    Publisher: American Meteorological Society
    Abstract: tional Weather Service (NWS) is implementing a short- to long-range Hydrologic Ensemble Forecast Service (HEFS). The HEFS addresses the need to quantify uncertainty in hydrologic forecasts for flood risk management, water supply management, streamflow regulation, recreation planning, and ecosystem management, among other applications. The HEFS extends the existing hydrologic ensemble services to include short-range forecasts, incorporate additional weather and climate information, and better quantify the major uncertainties in hydrologic forecasting. It provides, at forecast horizons ranging from 6 h to about a year, ensemble forecasts and verification products that can be tailored to users' needs. Based on separate modeling of the input and hydrologic uncertainties, the HEFS includes 1) the Meteorological Ensemble Forecast Processor, which ingests weather and climate forecasts from multiple numerical weather prediction models to produce bias-corrected forcing ensembles at the hydrologic basin scales; 2) the Hydrologic Processor, which inputs the forcing ensembles into hydrologic, hydraulic, and reservoir models to generate streamflow ensembles; 3) the hydrologic Ensemble Postprocessor, which aims to account for the total hydrologic uncertainty and correct for systematic biases in streamflow; 4) the Ensemble Verification Service, which verifies the forcing and streamflow ensembles to help identify the main sources of skill and error in the forecasts; and 5) the Graphics Generator, which enables forecasters to create a large array of ensemble and related products. Examples of verification results from multiyear hind-casting illustrate the expected performance and limitations of HEFS. Finally, future scientific and operational challenges to fully embrace and practice the ensemble paradigm in hydrology and water resources services are discussed.
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      The Science of NOAA's Operational Hydrologic Ensemble Forecast Service

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    contributor authorDemargne, Julie
    contributor authorWu, Limin
    contributor authorRegonda, Satish K.
    contributor authorBrown, James D.
    contributor authorLee, Haksu
    contributor authorHe, Minxue
    contributor authorSeo, Dong-Jun
    contributor authorHartman, Robert
    contributor authorHerr, Henry D.
    contributor authorFresch, Mark
    contributor authorSchaake, John
    contributor authorZhu, Yuejian
    date accessioned2017-06-09T16:44:30Z
    date available2017-06-09T16:44:30Z
    date copyright2014/01/01
    date issued2013
    identifier issn0003-0007
    identifier otherams-73291.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4215388
    description abstracttional Weather Service (NWS) is implementing a short- to long-range Hydrologic Ensemble Forecast Service (HEFS). The HEFS addresses the need to quantify uncertainty in hydrologic forecasts for flood risk management, water supply management, streamflow regulation, recreation planning, and ecosystem management, among other applications. The HEFS extends the existing hydrologic ensemble services to include short-range forecasts, incorporate additional weather and climate information, and better quantify the major uncertainties in hydrologic forecasting. It provides, at forecast horizons ranging from 6 h to about a year, ensemble forecasts and verification products that can be tailored to users' needs. Based on separate modeling of the input and hydrologic uncertainties, the HEFS includes 1) the Meteorological Ensemble Forecast Processor, which ingests weather and climate forecasts from multiple numerical weather prediction models to produce bias-corrected forcing ensembles at the hydrologic basin scales; 2) the Hydrologic Processor, which inputs the forcing ensembles into hydrologic, hydraulic, and reservoir models to generate streamflow ensembles; 3) the hydrologic Ensemble Postprocessor, which aims to account for the total hydrologic uncertainty and correct for systematic biases in streamflow; 4) the Ensemble Verification Service, which verifies the forcing and streamflow ensembles to help identify the main sources of skill and error in the forecasts; and 5) the Graphics Generator, which enables forecasters to create a large array of ensemble and related products. Examples of verification results from multiyear hind-casting illustrate the expected performance and limitations of HEFS. Finally, future scientific and operational challenges to fully embrace and practice the ensemble paradigm in hydrology and water resources services are discussed.
    publisherAmerican Meteorological Society
    titleThe Science of NOAA's Operational Hydrologic Ensemble Forecast Service
    typeJournal Paper
    journal volume95
    journal issue1
    journal titleBulletin of the American Meteorological Society
    identifier doi10.1175/BAMS-D-12-00081.1
    journal fristpage79
    journal lastpage98
    treeBulletin of the American Meteorological Society:;2013:;volume( 095 ):;issue: 001
    contenttypeFulltext
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