Extended-range Forecasting by a Statistical Procedure
Author : Elizabeth A. Kelley
Publisher :
Page : 72 pages
File Size : 45,83 MB
Release : 1958
Category : Long-range weather forecasting
ISBN :
Author : Elizabeth A. Kelley
Publisher :
Page : 72 pages
File Size : 45,83 MB
Release : 1958
Category : Long-range weather forecasting
ISBN :
Author : Stéphane Vannitsem
Publisher : Elsevier
Page : 364 pages
File Size : 30,61 MB
Release : 2018-05-17
Category : Science
ISBN : 012812248X
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
Author : United States. Navy. Weather Research Facility
Publisher :
Page : 44 pages
File Size : 50,89 MB
Release : 1963
Category : Numerical weather forecasting
ISBN :
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).
Author : Bovas Abraham
Publisher : John Wiley & Sons
Page : 474 pages
File Size : 14,94 MB
Release : 2009-09-25
Category : Mathematics
ISBN : 0470317299
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "This book, it must be said, lives up to the words on its advertising cover: 'Bridging the gap between introductory, descriptive approaches and highly advanced theoretical treatises, it provides a practical, intermediate level discussion of a variety of forecasting tools, and explains how they relate to one another, both in theory and practice.' It does just that!" -Journal of the Royal Statistical Society "A well-written work that deals with statistical methods and models that can be used to produce short-term forecasts, this book has wide-ranging applications. It could be used in the context of a study of regression, forecasting, and time series analysis by PhD students; or to support a concentration in quantitative methods for MBA students; or as a work in applied statistics for advanced undergraduates." -Choice Statistical Methods for Forecasting is a comprehensive, readable treatment of statistical methods and models used to produce short-term forecasts. The interconnections between the forecasting models and methods are thoroughly explained, and the gap between theory and practice is successfully bridged. Special topics are discussed, such as transfer function modeling; Kalman filtering; state space models; Bayesian forecasting; and methods for forecast evaluation, comparison, and control. The book provides time series, autocorrelation, and partial autocorrelation plots, as well as examples and exercises using real data. Statistical Methods for Forecasting serves as an outstanding textbook for advanced undergraduate and graduate courses in statistics, business, engineering, and the social sciences, as well as a working reference for professionals in business, industry, and government.
Author : Daniel S. Wilks
Publisher : Academic Press
Page : 698 pages
File Size : 34,3 MB
Release : 2011-05-20
Category : Mathematics
ISBN : 0123850223
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.
Author : Shirley McDavitt Lake
Publisher :
Page : 0 pages
File Size : 17,34 MB
Release : 1983
Category :
ISBN :
Author :
Publisher :
Page : 202 pages
File Size : 39,11 MB
Release : 1948
Category : Long-range weather forecasting
ISBN :
Author : Bovas Abraham
Publisher : John Wiley & Sons
Page : 472 pages
File Size : 48,81 MB
Release : 1983
Category : Mathematics
ISBN :
SEASONAL ADJUSTMENT. STATE SPACE MODELS. TIME SERIES MODELS. REGRESSION MODEL. STOCHASTIC TIME SERIES MODELS. SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE MODELS. EXPONENTIAL SMOOTHING METHODS. TRANSFER FUNCTION MODELS. GENERAL EXPONENTIAL SMOOTHING. INTERVENTION TIME SERIES MODELING. BAYESIAN FORECASTING. RALMAN FILTERING. ADAPTIVE FILTERING. TIME SERIES MODELS WITH TIME VARYING COEFFICIENTS. FORECAST EVALUATION. TRACKING SIGNALS.
Author : Rob J Hyndman
Publisher : OTexts
Page : 380 pages
File Size : 22,89 MB
Release : 2018-05-08
Category : Business & Economics
ISBN : 0987507117
Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Author : National Research Council
Publisher : National Academies Press
Page : 189 pages
File Size : 23,89 MB
Release : 1999-05-27
Category : Science
ISBN : 030917340X
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.