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Books > Science & Mathematics > Physics > Applied physics & special topics > Atmospheric physics
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Statistical Postprocessing of Ensemble Forecasts (Paperback)
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Statistical Postprocessing of Ensemble Forecasts (Paperback)
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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 Moeller (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.
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