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Handbook of Hydrometeorological Ensemble Forecasting

  • Qingyun Duan
  • Florian Pappenberger
  • Andy Wood
  • Hannah L. Cloke
  • John C. Schaake
Reference work

Table of contents

  1. Front Matter
    Pages i-xxxvi
  2. Introduction

    1. Front Matter
      Pages 1-1
    2. Joshua K. Roundy, Qingyun Duan, John C. Schaake
      Pages 3-31
  3. Overview of Meteorological Ensemble Forecasting

    1. Front Matter
      Pages 33-33
    2. Huiling Yuan, Zoltan Toth, Malaquias Peña, Eugenia Kalnay
      Pages 35-65
    3. Jun Du, Judith Berner, Roberto Buizza, Martin Charron, Peter Houtekamer, Dingchen Hou et al.
      Pages 99-149
    4. Roberto Buizza, Jun Du, Zoltan Toth, Dingchen Hou
      Pages 151-193
    5. Malaquias Peña, L. Gwen Chen, Huug van den Dool
      Pages 195-236
  4. Post-processing of Meteorological Ensemble Forecasting for Hydrological Applications

    1. Front Matter
      Pages 237-237
    2. Fredrik Wetterhall, Paul Smith
      Pages 239-253
    3. Andrew Schepen, Q. J. Wang, David E. Robertson
      Pages 255-283
  5. Hydrological Models

    1. Front Matter
      Pages 309-309
    2. Sharad K. Jain, Vijay P. Singh
      Pages 311-339
    3. Chong-Yu Xu, Lihua Xiong, Vijay P. Singh
      Pages 341-387
    4. Zhaofei Liu, Yamei Wang, Zongxue Xu, Qingyun Duan
      Pages 389-411
    5. Yangbo Chen
      Pages 413-436
    6. Michael B. Ek
      Pages 437-477
  6. Model Parameter Estimation and Uncertainty Analysis

    1. Front Matter
      Pages 479-479
    2. Tiantian Yang, Kuolin Hsu, Qingyun Duan, Soroosh Sorooshian, Chen Wang
      Pages 523-561
    3. Jasper A. Vrugt, Elias C. Massoud
      Pages 563-636
    4. Yanjun Gan, Qingyun Duan
      Pages 637-671
  7. Observation and Data Assimilation

    1. Front Matter
      Pages 673-673
    2. Hamid Moradkhani, Grey S. Nearing, Peyman Abbaszadeh, Sahani Pathiraja
      Pages 675-699
    3. Gabrielle Jacinthe Maria De Lannoy, Patricia de Rosnay, Rolf Helmut Reichle
      Pages 701-743
    4. Seong Jin Noh, Albrecht H. Weerts, Oldrich Rakovec, Haksu Lee, Dong-Jun Seo
      Pages 745-780
  8. Post-processing of Hydrological Ensemble Forecasts

    1. Front Matter
      Pages 781-781
    2. Thomas M. Hopson, Andy Wood, Albrecht H. Weerts
      Pages 783-793
    3. Marie-Amélie Boucher, Emmanuel Roulin, Vincent Fortin
      Pages 795-818
    4. Andy Wood, A. Sankarasubramanian, Pablo Mendoza
      Pages 819-845
  9. Verification of Hydrometeorological Ensemble Forecasts

    1. Front Matter
      Pages 847-847
    2. A. Allen Bradley, Julie Demargne, Kristie J. Franz
      Pages 849-892
    3. François Anctil, Maria-Helena Ramos
      Pages 893-922
    4. Eric Gilleland, Florian Pappenberger, Barbara Brown, Elizabeth Ebert, David Richardson
      Pages 923-951
    5. Katharina Liechti, Massimiliano Zappa
      Pages 953-975
    6. Luc Perreault, Jocelyn Gaudet, Louis Delorme, Simon Chatelain
      Pages 977-1012
    7. Kevin Werner, Jan S. Verkade, Thomas C. Pagano
      Pages 1013-1033
  10. Communication and Use of Ensemble Forecasts for Decision Making

    1. Front Matter
      Pages 1035-1035
    2. Jutta Thielen-del Pozo, Michael Bruen
      Pages 1037-1045
    3. Geoff Pegram, Damien Raynaud, Eric Sprokkereef, Martin Ebel, Silke Rademacher, Jonas Olsson et al.
      Pages 1047-1092
    4. Feyera A. Hirpa, Kayode Fagbemi, Ernest Afiesimam, Hassan Shuaib, Peter Salamon
      Pages 1109-1130
    5. David Demeritt, Elisabeth M. Stephens, Laurence Créton-Cazanave, Céline Lutoff, Isabelle Ruin, Sébastien Nobert
      Pages 1131-1160
    6. Narendra Kumar Tuteja, Senlin Zhou, Julien Lerat, Q. J. Wang, Daehyok Shin, David E. Robertson
      Pages 1161-1178
  11. Ensemble Forecast Application and Showcases

    1. Front Matter
      Pages 1179-1179
    2. Massimiliano Zappa, S. J. van Andel, Hannah L. Cloke
      Pages 1181-1185
    3. Florian Pappenberger, Thomas C. Pagano, J. D. Brown, Lorenzo Alfieri, D. A. Lavers, L. Berthet et al.
      Pages 1187-1221
    4. Lorenzo Alfieri, Marc Berenguer, Valentin Knechtl, Katharina Liechti, Daniel Sempere-Torres, Massimiliano Zappa
      Pages 1223-1260

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 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 make risk-based decisions. Recently, hydrometeorological ensemble forecast approaches have begun to be developed and used by operational hydrometeorological services. In contrast to deterministic forecasts, ensemble forecasts are 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.

 

Handbook of Hydrometeorological Ensemble Forecasting” is mainly contributed by the group of experts from HEPEX as a central reference work from this field.

 

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 forecasts 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. This book not only covers the theoretical and methodological aspects involved in hydrometeorological ensemble forecasting, but also presents a large number of successful application showcases. It should serves as an excellent reference book for researchers and practitioners in hydrometeorological forecasting.

Keywords

Ensemble Methods Floods and Droughts Hydrometeorological Forecasting Statistical pre-processing and Post-processing Water and Emergency Management

Editors and affiliations

  • Qingyun Duan
    • 1
  • Florian Pappenberger
    • 2
  • Andy Wood
    • 3
  • Hannah L. Cloke
    • 4
  • John C. Schaake
    • 5
  1. 1.Faculty of Geographical ScienceBeijing Normal UniversityBeijingChina
  2. 2.European Centre for Medium-Range Weather Forecasts, ECMWFReadingUK
  3. 3.National Center for Atmospheric ResearchBoulderUSA
  4. 4.Department of MeteorologyReading UniversityReadingUK
  5. 5.U.S. National Weather Service (retired)AnnapolisUSA

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