The Science of NOAA's Operational Hydrologic Ensemble Forecast Service

被引:208
作者
Demargne, Julie [1 ,2 ]
Wu, Limin [1 ,3 ]
Regonda, Satish K. [1 ,4 ]
Brown, James D. [5 ]
Lee, Haksu [3 ,6 ]
He, Minxue [1 ,4 ]
Seo, Dong-Jun [7 ]
Hartman, Robert [8 ]
Herr, Henry D. [1 ]
Fresch, Mark [1 ]
Schaake, John
Zhu, Yuejian [9 ]
机构
[1] NOAA, Natl Weather Serv, Off Hydrol Dev, Silver Spring, MD 20910 USA
[2] HYDRIS Hydrol, St Mathieu De Treviers, France
[3] LEN Technol, Oak Hill, VA USA
[4] Riverside Technol Inc, Ft Collins, CO USA
[5] Hydrol Solut Ltd, Southampton, Hants, England
[6] NOAA, Natl Weather Serv, Off Climate Water & Weather Serv, Silver Spring, MD 20910 USA
[7] Univ Texas Arlington, Dept Civil Engn, Arlington, TX 76019 USA
[8] NOAA, Calif Nevada River Forecast Ctr, Natl Weather Serv, Sacramento, CA USA
[9] NOAA, Environm Modeling Ctr, Natl Ctr Environm Predict, Natl Weather Serv, College Pk, MD USA
基金
美国海洋和大气管理局;
关键词
MODEL CONDITIONAL PROCESSOR; BIAS CORRECTION; NONPARAMETRIC POSTPROCESSOR; PRECIPITATION FORECASTS; PREDICTIVE UNCERTAINTY; OUTPUT STATISTICS; DATA ASSIMILATION; SOIL-MOISTURE; STREAMFLOW; SYSTEM;
D O I
10.1175/BAMS-D-12-00081.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
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.
引用
收藏
页码:79 / 98
页数:20
相关论文
共 86 条
[1]   An operational hydrological ensemble prediction system for the city of Zurich (Switzerland): skill, case studies and scenarios [J].
Addor, N. ;
Jaun, S. ;
Fundel, F. ;
Zappa, M. .
HYDROLOGY AND EARTH SYSTEM SCIENCES, 2011, 15 (07) :2327-2347
[2]   The european flood alert system EFAS - Part 2: Statistical skill assessment of probabilistic and deterministic operational forecasts [J].
Bartholmes, J. C. ;
Thielen, J. ;
Ramos, M. H. ;
Gentilini, S. .
HYDROLOGY AND EARTH SYSTEM SCIENCES, 2009, 13 (02) :141-153
[3]   Multiscale error analysis, correction, and predictive uncertainty estimation in a flood forecasting system [J].
Bogner, K. ;
Pappenberger, F. .
WATER RESOURCES RESEARCH, 2011, 47
[4]   Error-correction methods and evaluation of an ensemble based hydrological forecasting system for the Upper Danube catchment [J].
Bogner, K. ;
Kalas, M. .
ATMOSPHERIC SCIENCE LETTERS, 2008, 9 (02) :95-102
[5]   Evaluation of a nonparametric post-processor for bias correction and uncertainty estimation of hydrologic predictions [J].
Brown, James D. ;
Seo, Dong-Jun .
HYDROLOGICAL PROCESSES, 2013, 27 (01) :83-105
[6]   Verification of Precipitation Forecasts from NCEP's Short-Range Ensemble Forecast (SREF) System with Reference to Ensemble Streamflow Prediction Using Lumped Hydrologic Models [J].
Brown, James D. ;
Seo, Dong-Jun ;
Du, Jun .
JOURNAL OF HYDROMETEOROLOGY, 2012, 13 (03) :808-836
[7]   A Nonparametric Postprocessor for Bias Correction of Hydrometeorological and Hydrologic Ensemble Forecasts [J].
Brown, James D. ;
Seo, Dong-Jun .
JOURNAL OF HYDROMETEOROLOGY, 2010, 11 (03) :642-665
[8]   The Ensemble Verification System (EVS): A software tool for verifying ensemble forecasts of hydrometeorological and hydrologic variables at discrete locations [J].
Brown, James D. ;
Demargne, Julie ;
Seo, Dong-Jun ;
Liu, Yuqiong .
ENVIRONMENTAL MODELLING & SOFTWARE, 2010, 25 (07) :854-872
[9]   Visualizing flood forecasting uncertainty: some current European EPS platforms-COST731 working group 3 [J].
Bruen, M. ;
Krahe, P. ;
Zappa, M. ;
Olsson, J. ;
Vehvilainen, B. ;
Kok, K. ;
Daamen, K. .
ATMOSPHERIC SCIENCE LETTERS, 2010, 11 (02) :92-99
[10]   A comparison of the ECMWF, MSC, and NCEP global ensemble prediction systems [J].
Buizza, R ;
Houtekamer, PL ;
Toth, Z ;
Pellerin, G ;
Wei, MZ ;
Zhu, YJ .
MONTHLY WEATHER REVIEW, 2005, 133 (05) :1076-1097