Hydrometeorological prediction involves the forecasting of the state and variation of hydrometeorological elements -- including precipitation, temperature, humidity, soil moisture, river discharge, groundwater, etc.-- at different space and time scales. Such forecasts form an important scientific basis for informing public of natural hazards such as cyclones, heat waves, frosts, droughts and floods. Traditionally, and at most currently operational centers, hydrometeorological forecasts are deterministic, "single-valued" outlooks: i.e., the weather and hydrological models provide a single best…mehr
Hydrometeorological prediction involves the forecasting of the state and variation of hydrometeorological elements -- including precipitation, temperature, humidity, soil moisture, river discharge, groundwater, etc.-- at different space and time scales. Such forecasts form an important scientific basis for informing public of natural hazards such as cyclones, heat waves, frosts, droughts and floods. Traditionally, and at most currently operational centers, hydrometeorological forecasts are deterministic, "single-valued" outlooks: i.e., the weather and hydrological models provide a single best guess of the magnitude and timing of the impending events. These forecasts suffer the obvious drawback of lacking uncertainty information that would help decision-makers assess the risks of forecast use. Recently, hydrometeorological ensemble forecast approaches have begun to be developed and used by operational hydrometeorological services. In contrast to deterministic forecasts, ensemble forecasts are a multiple forecasts of the same events. The ensemble forecasts are generated by perturbing uncertain factors such as model forcings, initial conditions, and/or model physics. Ensemble techniques are attractive because they not only offer an estimate of the most probable future state of the hydrometeorological system, but also quantify the predictive uncertainty of a catastrophic hydrometeorological event occurring. The Hydrological Ensemble Prediction Experiment (HEPEX), initiated in 2004, has signaled a new era of collaboration toward the development of hydrometeorological ensemble forecasts. By bringing meteorologists, hydrologists and hydrometeorological forecast users together, HEPEX aims to improve operational hydrometeorological forecast approaches to a standard that can be used with confidence by emergencies and water resources managers. HEPEX advocates a hydrometeorological ensemble prediction system (HEPS) framework that consists of several basic building blocks. These components include:(a) an approach (typically statistical) for addressing uncertainty in meteorological inputs and generating statistically consistent space/time meteorological inputs for hydrological applications; (b) a land data assimilation approach for leveraging observation to reduce uncertainties in the initial and boundary conditions of the hydrological system; (c) approaches that address uncertainty in model parameters (also called 'calibration'); (d) a hydrologic model or other approach for converting meteorological inputs into hydrological outputs; and finally (e) approaches for characterizing hydrological model output uncertainty. Also integral to HEPS is a verification system that can be used to evaluate the performance of all of its components. HEPS frameworks are being increasingly adopted by operational hydrometeorological agencies around the world to support risk management related to flash flooding, river and coastal flooding, drought, and water management. Real benefits of ensemble forecasts have been demonstrated in water emergence management decision making, optimization of reservoir operation, and other applications.
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Autorenporträt
Qingyun Duan (EIC): National Chair Professor and Chief Scientist of College of Global Change and Earth System Science at Beijing Normal University, author of 70 peer reviewed scientific papers. He is currently on editorial boards of several scientific journals and was the lead editor of the American Geophysical Union Water Science and Applications Monograph series "Calibration of Watershed Models". He is a Fellow of American Geophysical Union.
Florian Pappenberger(Co-EIC):senior scientist at European Center for Medium Range Weather Forecasting, author of over 70 peer reviewed scientific publications in international journals in the field of hydrometeorology. He is editor of the prestigious journal of Hydrology and Earth System Sciences and has received the outstanding editor award in 2010. He has guest edited journals in the field of hydrological ensemble forecasting in Hydrological Processes and Journal of Hydrology.
Jutta Thielen(Co-EIC): senior scientist at the Joint Research Centre of the European Commission. She is action leader for the Climate Risk Management Unit and has been responsible for the development and operational implementation of the European Flood Awareness System (EFAS).. Her work is documented in publications in both meteorological and hydrological international journals and books. She is co-editor of Atmospheric Science Letters, a journal of the Royal Meteorological Society, for which she also received the ASL award for 2008. She is co-chairing the Hydrological Ensemble Prediction Experiment initiative (HEPEX).
Andy Wood(Co-EIC):a Development and Operations Hydrologist for the U.S. National Weather Service, Dr. Wood is also the Chair of the Hydrology Committee of the American Meteorological Society (AMS), an associate editor of the AMS Journal of Hydrometeorology, and a co-leader of the Hydrologic Ensemble Prediction Experiment (HEPEX). He previously worked as a research professor at the University of Washington Department of Civil and Environmental Engineering, and as the lead Scientist of a private renewable energy prediction firm, and has co-authored over 40 scientific publications focusing on hydrologic prediction, downscaling and climate change impact assessment, drought and other topics.
Hannah L. Cloke (co-EIC): Reader and Associate Professor in Hydrology at the University of Reading. She has international recognition as one of the leading scientists in hydrometeorological ensemble forecasting and has presented and published extensively in this field. She is editor of the journals Meteorological Applications, Hydrology Research, and Hydrology and Earth System Sciences and edited the Special Issue of Hydrological Processes on Hydrological Ensemble Prediction Systems (2013).
John Schaake (co-EIC): formerly Chief Scientist with Office of Hydrologic Development, NOAA National Weather Service. He retired from National Weather Service after over 20 years of service in 2001. In retirement, he initiated the Hydrologic Ensemble Prediction Experiment (HEPEX) in 2004 and served as the inaugural co-chair for HEPEX scientific steering committee. Dr. Schaake is an internationally recognized expert on hydrometeorological ensemble forecasting and published extensively on hydrometeorological ensemble forecasting. Prior to his service in NOAA, he was an Associate Professor at Massachusetts Institute of Technology and University of Florida. He has served on editorial boards of various hydrology and water resources journals and various leadership posts of international organizations. He has been elected a Fellow of American Geophysical Union and American Meteorological Society.
Inhaltsangabe
Introduction.- Overview of Meteorological Ensemble Forecasting.- Post-processing of Meteorological Ensemble Forecasting for Hydrological Applications.- Hydrological Models.- Model Parameter Estimation and Uncertainty Analysis.- Observation and data assimilation.- Post-processing of Hydrological Ensemble Forecasts.- Verification of Hydrometeorological Ensemble Forecasts.- Communication and Use of Ensemble Forecasts for Decision Making.- Ensemble Forecast Application Showcases.- Mathematical and Statistical Fundamentals for Hydrometeorological Ensemble Forecasting.
Introduction.- Overview of Meteorological Ensemble Forecasting.- Post-processing of Meteorological Ensemble Forecasting for Hydrological Applications.- Hydrological Models.- Model Parameter Estimation and Uncertainty Analysis.- Observation and data assimilation.- Post-processing of Hydrological Ensemble Forecasts.- Verification of Hydrometeorological Ensemble Forecasts.- Communication and Use of Ensemble Forecasts for Decision Making.- Ensemble Forecast Application Showcases.- Mathematical and Statistical Fundamentals for Hydrometeorological Ensemble Forecasting.
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