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Handbook of Hydrometeorological Ensemble Forecasting

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Cover of 'Handbook of Hydrometeorological Ensemble Forecasting'

Table of Contents

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    Book Overview
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    Chapter 2 Attributes of Forecast Quality
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    Chapter 3 Verification Metrics for Hydrological Ensemble Forecasts
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    Chapter 4 Verification of Meteorological Forecasts for Hydrological Applications
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    Chapter 5 Verification of Short-Range Hydrological Forecasts
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    Chapter 6 Verification of Medium- to Long-Range Hydrological Forecasts
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    Chapter 7 Application of Hydrological Forecast Verification Information
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    Chapter 8 Hydrological Predictability, Scales, and Uncertainty Issues
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    Chapter 10 Overview of Weather and Climate Systems
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    Chapter 11 Numerical Weather Prediction Basics: Models, Numerical Methods, and Data Assimilation
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    Chapter 12 Intraseasonal to Interannual Climate Variability and Prediction
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    Chapter 13 Ensemble Methods for Meteorological Predictions
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    Chapter 14 Major Operational Ensemble Prediction Systems (EPS) and the Future of EPS
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    Chapter 15 Hydrological Challenges in Meteorological Post-processing
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    Chapter 18 Application to Post-processing of Meteorological Seasonal Forecasting
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    Chapter 19 Multi-model Combination and Seamless Prediction
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    Chapter 20 Hydrological Cycles, Models, and Applications to Forecasting
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    Chapter 21 Black-Box Hydrological Models
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    Chapter 22 Conceptual Hydrological Models
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    Chapter 23 Distributed Hydrological Models
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    Chapter 24 Land Surface Hydrological Models
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    Chapter 25 Parameter Estimation and Predictive Uncertainty Quantification in Hydrological Modelling
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    Chapter 26 Methods to Estimate Optimal Parameters
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    Chapter 27 Uncertainty Quantification of Complex System Models: Bayesian Analysis
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    Chapter 30 Fundamentals of Data Assimilation and Theoretical Advances
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    Chapter 32 Soil Moisture Data Assimilation
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    Chapter 33 Assimilation of Streamflow Observations
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    Chapter 36 Motivation and Overview of Hydrological Ensemble Post-processing
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    Chapter 37 Seasonal Ensemble Forecast Post-processing
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    Chapter 39 Present and Future Requirements for Using and Communicating Hydrometeorological Ensemble Prediction Systems for Short-, Medium-, and Long-Term Applications
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    Chapter 40 Overview of Forecast Communication and Use of Ensemble Hydrometeorological Forecasts
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    Chapter 42 Best Practice in Communicating Uncertainties in Flood Management in the USA
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    Chapter 43 Saving Lives: Ensemble-Based Early Warnings in Developing Nations
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    Chapter 44 Communicating and Using Ensemble Flood Forecasts in Flood Incident Management: Lessons from Social Science
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    Chapter 45 Introduction to Ensemble Forecast Applications and Showcases
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    Chapter 47 Hydrological Ensemble Prediction Systems Around the Globe
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    Chapter 49 Flash Flood Forecasting Based on Rainfall Thresholds
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    Chapter 51 Medium Range Flood Forecasting Example EFAS
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    Chapter 52 Seasonal Drought Forecasting on the Example of the USA
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    Chapter 54 Ensemble Streamflow Forecasts for Hydropower Systems
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    Chapter 55 Hydropower Forecasting in Brazil
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    Chapter 56 New York City’s Operations Support Tool: Utilizing Hydrologic Forecasts for Water Supply Management
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    Chapter 58 Probabilistic Shipping Forecast
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    Chapter 59 Probabilistic Inundation Forecasting
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    Chapter 61 Probability and Statistical Theory for Hydrometeorology
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    Chapter 62 Estimation of Probability Distributions for Hydrometeorological Applications
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    Chapter 63 Regression Techniques Used in Hydrometeorology
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    Chapter 65 Sensitivity Analysis Methods
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    Chapter 71 Short-Range Ensemble Forecast Post-processing
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    Chapter 72 Challenges of Decision Making in the Context of Uncertain Forecasts in France
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    Chapter 73 Overview of Communication Strategies for Uncertainty in Hydrological Forecasting in Australia
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    Chapter 74 Hydrological Ensemble Prediction Applied in China
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Title
Handbook of Hydrometeorological Ensemble Forecasting
Published by
Springer-Verlag Berlin Heidelberg, January 2018
DOI 10.1007/978-3-642-39925-1
ISBNs
978-3-64-239925-1, 978-3-64-239926-8, 978-3-64-239924-4
Editors

Qingyun Duan, Florian Pappenberger, Jutta Thielen, Andy Wood, Hannah L. Cloke, John C. Schaake

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 3 23%
Researcher 2 15%
Student > Ph. D. Student 2 15%
Unknown 6 46%
Readers by discipline Count As %
Environmental Science 2 15%
Engineering 2 15%
Earth and Planetary Sciences 1 8%
Agricultural and Biological Sciences 1 8%
Unknown 7 54%