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Table of contents

  1. Kevin Werner, Jan S Verkade, Thomas C Pagano
  2. Andrew Schepen, Q. J. Wang, David E. Robertson
  3. Seong Jin Noh, Albrecht H. Weerts, Oldrich Rakovec, Haksu Lee, Dong-Jun Seo
  4. A. Allen Bradley, Julie Demargne, Kristie J. Franz
  5. Chong-Yu Xu, Lihua Xiong, Vijay P. Singh
  6. Caroline Wittwer, C. de Saint-Aubin, C. Ardilouze
  7. David Demeritt, Elisabeth M. Stephens, Laurence Créton-Cazanave, Céline Lutoff, Isabelle Ruin, Sébastien Nobert
  8. Zhaofei Liu, Yamei Wang, Zongxue Xu, Qingyun Duan
  9. Jun Du, Judith Berner, Roberto Buizza, Martin Charron, Peter Houtekamer, Dingchen Hou et al.
  10. Marie-Amélie Boucher, Maria-Helena Ramos
  11. Lorenzo Alfieri, Marc Berenguer, Valentin Knechtl, Katharina Liechti, Daniel Sempere-Torres, Massimiliano Zappa
  12. Hamid Moradkhani, Grey Nearing, Peyman Abbaszadeh, Sahani Pathiraja
  13. Guangsheng Wang, Zhijie Yin, Jianqing Yang, Yuhong Yan
  14. F. Pappenberger, T. C. Pagano, J. D. Brown, L. Alfieri, D. A. Lavers, L. Berthet et al.
  15. Joshua K. Roundy, Qingyun Duan, John Schaake
  16. Carlos E. M. Tucci, Walter Collischonn, Fernando Mainardi Fan, Dirk Schwanenberg
  17. Malaquias Peña, L. Gwen Chen, Huug van den Dool
  18. Roberto Buizza, Jun Du, Zoltan Toth, Dingchen Hou
  19. Jutta Thielen-del Pozo, Peter Salamon, Peter Burek, Florian Pappenberger, C. Alionte Eklund, E. Sprokkereef et al.
  20. Tiantian Yang, Kuolin Hsu, Qingyun Duan, Soroosh Sorooshian, Chen Wang
  21. Thomas M. Hopson, Andrew W. Wood, Albrecht H. Weerts
  22. Narendra Kumar Tuteja, Senlin Zhou, Julien Lerat, Q. J. Wang, Daehyok Shin, David E. Robertson
  23. Huiling Yuan, Zoltan Toth, Malaquias Peña, Eugenia Kalnay
  24. A. Mueller, C. Baugh, P. Bates, F. Pappenberger
  25. Dennis Meißner, Bastian Klein
  26. Zengchao Hao, Vijay P. Singh, Wei Gong
  27. Feyera A. Hirpa, Kayode Fagbemi, Ernest Afiesimam, Hassan Shuaib, Peter Salamon
  28. Eric F. Wood, Xing Yuan, Joshua K. Roundy, Ming Pan, Lifeng Luo
  29. Andrew W. Wood, A. Sankarasubramanian, Pablo Mendoza
  30. Yanjun Gan, Qingyun Duan
  31. M. -A. Boucher, Emmanuel Roulin, Vincent Fortin
  32. Gabrielle Jacinthe Maria de Lannoy, Patricia de Rosnay, Rolf Helmut Reichle
  33. François Anctil, Maria-Helena Ramos
  34. Luc Perreault, Jocelyn Gaudet, Louis Delorme, Simon Chatelain
  35. Eric Gilleland, Florian Pappenberger, Barbara Brown, Elizabeth Ebert, David Richardson

About this book

Introduction

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 collection of 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.

Editors and affiliations

  • Qingyun Duan
    • 1
  • Florian Pappenberger
    • 2
  • Jutta Thielen
    • 3
  • Andy Wood
    • 4
  • Hannah L. Cloke
    • 5
  • John C. Schaake
    • 6
  1. 1.Beijing Normal UniversityBeijingChina
  2. 2.European Centre for Medium-Range Weather ForecastsReadingUnited Kingdom
  3. 3.European Commission DG Joint Research CeIspraItaly
  4. 4.National Center for Atmospheric ResearchBoulderUSA
  5. 5.University of ReadingReadingUnited Kingdom
  6. 6.Consulting HydrologistAnnapolisUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-40457-3
  • Copyright Information Springer-Verlag GmbH Germany, part of Springer Nature 2018
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Earth and Environmental Science
  • Online ISBN 978-3-642-40457-3
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