Statistical Postprocessing of Ensemble Forecasts

Nonfiction, Science & Nature, Science, Other Sciences, Meteorology, Biological Sciences, Environmental Science
Cover of the book Statistical Postprocessing of Ensemble Forecasts by , Elsevier Science
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9780128122488
Publisher: Elsevier Science Publication: May 17, 2018
Imprint: Elsevier Language: English
Author:
ISBN: 9780128122488
Publisher: Elsevier Science
Publication: May 17, 2018
Imprint: Elsevier
Language: English

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.

  • Consolidates, for the first time, the methodologies and applications of ensemble forecasts in one succinct place
  • Provides real-world examples of methods used to formulate forecasts
  • Presents the tools needed to make the best use of multiple model forecasts in a timely and efficient manner
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

More books from Elsevier Science

Cover of the book Advanced Persistent Threat by
Cover of the book Studies in Natural Products Chemistry by
Cover of the book Handbook of Grape Processing By-Products by
Cover of the book Analytical Modelling of Fuel Cells by
Cover of the book Emerging Nanotechnologies for Manufacturing by
Cover of the book Global Seagrass Research Methods by
Cover of the book Braking of Road Vehicles by
Cover of the book Vaccines for Biodefense and Emerging and Neglected Diseases by
Cover of the book Fuel Cells by
Cover of the book Practical Approaches to Biological Inorganic Chemistry by
Cover of the book Optimising Sweet Taste in Foods by
Cover of the book The Endocannabinoid System by
Cover of the book Membrane Distillation by
Cover of the book Advances in Quantum Chemistry by
Cover of the book Academic Press Library in Biomedical Applications of Mobile and Wireless Communications: Wireless UWB Body Area Networks by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy