Statistical Postprocessing of Ensemble Forecasts

Statistical Postprocessing of Ensemble Forecasts

Author: Stéphane Vannitsem

Publisher: Elsevier

Published: 2018-05-22

Total Pages: 0

ISBN-13: 9780128123720

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Statistical Postprocessing of Ensemble Forecasts brings together chapters contributed by international subject-matter experts describing the current state of the art in the statistical postprocessing of ensemble forecasts. The book illustrates the use of these methods in several important applications including weather, hydrological and climate forecasts, and renewable energy forecasting. After an introductory section on ensemble forecasts and prediction systems, the second section of the book is devoted to exposition of the methods available for statistical postprocessing of ensemble forecasts: univariate and multivariate ensemble postprocessing are first reviewed by Wilks (Chapters 3), then Schefzik and Möller (Chapter 4), and the more specialized perspective necessary for postprocessing forecasts for extremes is presented by Friederichs, Wahl, and Buschow (Chapter 5). The second section concludes with a discussion of forecast verification methods devised specifically for evaluation of ensemble forecasts (Chapter 6 by Thorarinsdottir and Schuhen). The third section of this book is devoted to applications of ensemble postprocessing. Practical aspects of ensemble postprocessing are first detailed in Chapter 7 (Hamill), including an extended and illustrative case study. Chapters 8 (Hemri), 9 (Pinson and Messner), and 10 (Van Schaeybroeck and Vannitsem) discuss ensemble postprocessing specifically for hydrological applications, postprocessing in support of renewable energy applications, and postprocessing of long-range forecasts from months to decades. Finally, Chapter 11 (Messner) provides a guide to the ensemble-postprocessing software available in the R programming language, which should greatly help readers implement many of the ideas presented in this book. Edited by three experts with strong and complementary expertise in statistical postprocessing of ensemble forecasts, this book assesses the new and rapidly developing field of ensemble forecast postprocessing as an extension of the use of statistical corrections to traditional deterministic forecasts. Statistical Postprocessing of Ensemble Forecasts is an essential resource for researchers, operational practitioners, and students in weather, seasonal, and climate forecasting, as well as users of such forecasts in fields involving renewable energy, conventional energy, hydrology, environmental engineering, and agriculture.


A Historical Survey of Statistical Weather Prediction

A Historical Survey of Statistical Weather Prediction

Author: United States. Navy. Weather Research Facility

Publisher:

Published: 1963

Total Pages: 44

ISBN-13:

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This work presents the history of the use of statistics in weather forecasting and describes the evolution of the more important statistical methods in this field: graphical techniques, periodicity, empirical orthogonal functions, and multiple discriminant analysis. A bibliography consisting of 141 references, divided by topics, and an appendix listing these references chronologically are included. (Author).


Weather Analysis and Forecasting

Weather Analysis and Forecasting

Author: Christo Georgiev

Publisher: Elsevier

Published: 2005-07-05

Total Pages: 198

ISBN-13: 0080455263

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Weather Analysis and Forecasting is a practical guide to using potential vorticity fields and water vapor imagery from satellites to elucidate complex weather patterns and train meteorologists to improve operational forecasting. In particular, it details the use of the close relationship between satellite imagery and the potential vorticity fields in the upper troposphere and lower stratosphere. It shows how to interpret water vapor patterns in terms of dynamical processes in the atmosphere and their relation to diagnostics available from weather prediction models. The book explores topics including: a dynamical view of synoptic development; the interpretation problem of satellite water vapor imagery; practical use of water vapor imagery and dynamical fields; significant water vapor imagery features associated with synoptic dynamical structures; and use of water vapor imagery for assessing NWP model behavior and improving forecasts. Applications are illustrated with color images based on real meteorological situations. The book's step-by-step pedagogy makes this an essential training manual for forecasters in meteorological services worldwide, and a valuable text for graduate students in atmospheric physics and satellite meteorology. * Shows how to analyze current satellite images for assessing weather models' behavior and improving forecasts * Provides step-by-step pedagogy for understanding and interpreting meteorological processes * Includes full-color throughout to highlight "real-world" models, patterns, and examples


Statistical Methods in the Atmospheric Sciences

Statistical Methods in the Atmospheric Sciences

Author: Daniel S. Wilks

Publisher: Academic Press

Published: 2011-05-20

Total Pages: 698

ISBN-13: 0123850223

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This revised and expanded text explains the latest statistical methods that are being used to describe, analyze, test, and forecast atmospheric data. It features numerous worked examples, illustrations, equations, and exercises with separate solutions. The book will help advanced students and professionals understand and communicate what their data sets have to say, and make sense of the scientific literature in meteorology, climatology, and related disciplines.


Making Climate Forecasts Matter

Making Climate Forecasts Matter

Author: National Research Council

Publisher: National Academies Press

Published: 1999-05-27

Total Pages: 189

ISBN-13: 030917340X

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El Nino has been with us for centuries, but now we can forcast it, and thus can prepare far in advance for the extreme climatic events it brings. The emerging ability to forecast climate may be of tremendous value to humanity if we learn how to use the information well. How does society cope with seasonal-to-interannual climatic variations? How have climate forecasts been usedâ€"and how useful have they been? What kinds of forecast information are needed? Who is likely to benefit from forecasting skill? What are the benefits of better forecasting? This book reviews what we know about these and other questions and identifies research directions toward more useful seasonal-to-interannual climate forecasts. In approaching their recommendations, the panel explores: Vulnerability of human activities to climate. State of the science of climate forecasting. How societies coevolved with their climates and cope with variations in climate. How climate information should be disseminated to achieve the best response. How we can use forecasting to better manage the human consequences of climate change.


Attribution of Extreme Weather Events in the Context of Climate Change

Attribution of Extreme Weather Events in the Context of Climate Change

Author: National Academies of Sciences, Engineering, and Medicine

Publisher: National Academies Press

Published: 2016-07-28

Total Pages: 187

ISBN-13: 0309380979

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As climate has warmed over recent years, a new pattern of more frequent and more intense weather events has unfolded across the globe. Climate models simulate such changes in extreme events, and some of the reasons for the changes are well understood. Warming increases the likelihood of extremely hot days and nights, favors increased atmospheric moisture that may result in more frequent heavy rainfall and snowfall, and leads to evaporation that can exacerbate droughts. Even with evidence of these broad trends, scientists cautioned in the past that individual weather events couldn't be attributed to climate change. Now, with advances in understanding the climate science behind extreme events and the science of extreme event attribution, such blanket statements may not be accurate. The relatively young science of extreme event attribution seeks to tease out the influence of human-cause climate change from other factors, such as natural sources of variability like El Niño, as contributors to individual extreme events. Event attribution can answer questions about how much climate change influenced the probability or intensity of a specific type of weather event. As event attribution capabilities improve, they could help inform choices about assessing and managing risk, and in guiding climate adaptation strategies. This report examines the current state of science of extreme weather attribution, and identifies ways to move the science forward to improve attribution capabilities.