Survey of Available Systems for Identifying Systematic Errors in Numerical Model Weather Forecasts PDF Download
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Author: Patrick A. Harr Publisher: ISBN: Category : Numerical weather forecasting Languages : en Pages : 98
Book Description
A generalized and flexible software plane to identify systematic errors in numerical forecast models is described. The plan is applicable to different types of models and can be altered to operate in different modes. Examined are various techniques which can be used within the plan, in terms of advantages and disadvantages. Estimates are made of possible impacts upon an existing operational environment and of the useage of resources needed by a system for identifying systematic errors. (Author).
Author: Patrick A. Harr Publisher: ISBN: Category : Numerical weather forecasting Languages : en Pages : 98
Book Description
A generalized and flexible software plane to identify systematic errors in numerical forecast models is described. The plan is applicable to different types of models and can be altered to operate in different modes. Examined are various techniques which can be used within the plan, in terms of advantages and disadvantages. Estimates are made of possible impacts upon an existing operational environment and of the useage of resources needed by a system for identifying systematic errors. (Author).
Author: Patrick A. Harr Publisher: ISBN: Category : Numerical weather forecasting Languages : en Pages : 59
Book Description
Many numerical model verification systems are handicapped by their inability to separate random errors, defined as scales of motion smaller than the concerned scale, and systematic errors. Random errors may be eliminated by time averaging over a minimum allowable data period. Statistical methods are implemented to determine a minimum data period needed to constitute a time scale within which numerical forecasts errors are truly systematic and not smoothed fields of rapidly varying random errors for a synoptic scale event. Long term or model climatological error patterns of a specific event are compared with randomly determined shorter term error patterns through statistical tests and measures to provide results which indicate a minimum case number needed to sufficiently smooth out unwanted random errors.
Author: Stéphane Vannitsem Publisher: Elsevier ISBN: 9780128123720 Category : Science Languages : en Pages : 0
Book Description
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.
Author: United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch Publisher: ISBN: Category : Science Languages : en Pages : 1080
Author: Tong Lee Publisher: Frontiers Media SA ISBN: 2889631184 Category : Science Languages : en Pages : 783
Book Description
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Author: Patrick A. Harr
Author: Patrick A. Harr
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Author: Patrick A. Harr
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Author: Stéphane Vannitsem
Author: United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch
Author: 
Author: Tong Lee
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