The Science of NOAA's Operational Hydrologic Ensemble Forecast Service

Julie Demargne Office of Hydrologic Development, National Weather Service, NOAA, Silver Spring, Maryland, and HYDRIS Hydrologie, Saint Mathieu de Tréviers, France

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Limin Wu Office of Hydrologic Development, National Weather Service, NOAA, Silver Spring, Maryland, and LEN Technologies, Oak Hill, Virginia

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Satish K. Regonda Office of Hydrologic Development, National Weather Service, NOAA, Silver Spring, Maryland, and Riverside Technology, Inc., Fort Collins, Colorado

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James D. Brown Hydrologic Solutions Limited, Southampton, United Kingdom

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Haksu Lee Office of Climate, Water, and Weather Services, National Weather Service, NOAA, Silver Spring, Maryland, and LEN Technologies, Oak Hill, Virginia

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Minxue He Office of Hydrologic Development, National Weather Service, NOAA, Silver Spring, Maryland, and Riverside Technology, Inc., Fort Collins, Colorado

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Dong-Jun Seo Department of Civil Engineering, The University of Texas at Arlington, Arlington, Texas

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Robert Hartman California–Nevada River Forecast Center, National Weather Service, NOAA, Sacramento, California

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Henry D. Herr Office of Hydrologic Development, National Weather Service, NOAA, Silver Spring, Maryland

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Mark Fresch Office of Hydrologic Development, National Weather Service, NOAA, Silver Spring, Maryland

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John Schaake Consultant, Annapolis, Maryland

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Yuejian Zhu Environmental Modeling Center, National Centers for Environmental Prediction, National Weather Service, NOAA, College Park, Maryland

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NOAA's National 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.

CORRESPONDING AUTHOR: Dr. Julie Demargne, 5 avenue du Grand Chêne, 34270 Saint Mathieu de Tréviers, France, E-mail: julie@demargne.com

NOAA's National 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.

CORRESPONDING AUTHOR: Dr. Julie Demargne, 5 avenue du Grand Chêne, 34270 Saint Mathieu de Tréviers, France, E-mail: julie@demargne.com
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