Handbook of Hydrometeorological Ensemble Forecasting

Handbook of Hydrometeorological Ensemble Forecasting

*A proposal for a “Handbook of Hydrometeorological Ensemble Forecasting” has been submitted to Springer as major reference work (We are still waiting to get formal approval from and sign a contract with Springer)*

Editorial Board Members: Qingyun Duan, Florian Pappenberger, Jutta Thielen, Andy Wood, Hannah Cloke, John Schaake

imagesSection Editors:  to be recruited (contact Qingyun Duan to express interest).

Want to contribute a chapter?  (contact Qingyun Duan to express interest)

Rationale
Remarkable advances have been achieved in hydrometeorological ensemble forecasting over the recent years. These advances are enabled by scientific and technological progress in numerical weather, climate and hydrological modeling, new forecasting methodologies, new observational technologies and data assimilation techniques, and more powerful computational software and hardware. As the results of these advances, related literature has proliferated over the recent years. However, the literature comprises mostly specialist publications in various scientific journals, There is not a single standard reference book or a textbook that teaches the fundamental theories behind hydrometeorological ensemble forecasting and furnishes examples of modern applications. The lack of such a handbook presently hinders the advancement of research and practice in the field. First, researchers and practitioners who are new to the field lack organized source materials to help understand this relatively new forecasting framework. Second, it creates difficulty in communicating the ensemble forecast information to users and decision makers, who needs education to understand the paradigm shift in forecasting approach. Third, it hinders the spread of hydrometeorological ensemble forecasting methodologies to regions where hydrometeorological forecasting is still basic or has yet to take root. The need for a good reference book on hydrometeorological ensemble forecasting is obvious and urgent.

Sections (Each section will have section editors)
(1) Introduction: provides broad rationales behind ensemble forecasting, historical perspectives including the Hydrological Ensemble Prediction Experiment and an overview of the individual chapters

(2) Meteorological ensemble forecasting: reviews the meteorological ensemble generation approaches and describe various statistical techniques for calibrating and post-processing (pre-processing for hydrological forecasting) raw meteorological ensemble forecasts.
Tentative Chapters: (i) Weather and climate forecasting basics, (ii) Ensemble generation methods, (iii) predictability at different time and space scales, (iv) dynamical and statistical downscaling methods, (v) post-processing of raw meteorological ensemble forecasting.

(3) Hydrometeorological observations and data assimilation: addresses data requirements for hydrometeorological forecasting, and presents various data assimilation techniques that are used to improve the representation of initial and boundary conditions.
Tentative Chapters: (i) Observation needs for hydrometeorological ensemble forecasting, (ii) In-situ and remote sensing measurements of hydrometeorological variables, (iii) Ensemble data assimilation methods.

(4) Model parametric uncertainty analysis: discusses various issues related to model calibration and specific model calibration/validation techniques.
Tentative Chapters: (i) Issues in model uncertainty analysis, (ii) Sensitivity analysis methods, (iii) Deterministic optimization methods, (iv) Stochastic optimization methods

(5) Hydrological modeling: describes different hydrological modeling approaches and various types of models, including lumped and distributed, conceptual type or physically based.
Tentative Chapters: (i) Modeling of hydrological system, (ii) Conceptual hydrological models, (iii) Distributed hydrological models, (iv) System-mathematical hydrological models

(6) Hydrological post-processing: covers different statistical post-processing techniques and different ensemble hydrological forecast products.
Tentative Chapters: (i) Parametric statistical post-processing methods (Regression, Bayesian,…), (ii) Non-parametric statistical post-processing methods (ANNs, Wavelets,…), (iii) Multi-model averaging methods

(7) Verification of hydrometeorological ensemble forecasts: describes various metrics for measuring the performance of the ensemble forecast system against observations.
Tentative Chapters: (i) Verification of deterministic hydrometeorological forecasts, (ii) Verification of ensemble hydrometeorological forecasting

(8) Communication and decision making: focuses on topics related to communicating probabilistic forecasting information to users and decision makers.
Tentative Chapters: (i) Users’ needs and perspectives, (ii) Communicating ensemble forecast information to forecast users and decision makers, (iii) Decision making

(9) Application showcases: focuses on different ensemble systems in practice and applications of various ensemble forecasting methods for a variety of purposes, including those for meteorological and river forecasts, water resources management, and water quality monitoring, drought monitoring, etc.
Tentative Chapters:(i) Ensemble forecasting for flood forecasting, (ii) Ensemble forecasting for reservoir operation, (iii) Ensemble forecasting for drought monitoring, (iv) Ensemble forecasting for risk-based emergency management decision making, (v) Ensemble forecasting for food security applications, (vi) Energy, Insurance, …

(10) Mathematical methods: presents the fundamental mathematics and statistical techniques that are needed by ensemble forecasting.
Tentative Chapters: (i) Probability and statistics basics, (ii) Regression Methods, (iii) Bayesian learning methods, (iv) Artificial Neural Networks (ANNs), (v) Wavelets, (vi), others, …

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