This book introduces and explains the statistical methods used to describe, analyze, test, and forecast atmospheric data. It will be useful to students, scientists, and other professionals who seek to make sense of the scientific literature in meteorology, climatology, or other geophysical disciplines, or to understand and communicate what their atmospheric data sets have to say. The book includes chapters on exploratory data analysis, probability distributions, hypothesis testing, statistical weather forecasting, forecast verification, time(series analysis, and multivariate data analysis. Worked examples, exercises, and illustrations facilitate understanding of the material; an extensive and up-to-date list of references allows the reader to pursue selected topics in greater depth. Key Features* Presents and explains techniques used in atmospheric data summarization, analysis, testing, and forecasting* Includes extensive and up-to-date references* Features numerous worked examples and exercises* Contains over 130 illustrations
Author(s): Daniel S. Wilks (Eds.)
Series: International Geophysics 59
Publisher: Elsevier, Academic Press
Year: 1995
Language: English
Pages: 1-464
Tags: Науки о Земле;Метеорология и климатология;Методы обработки метеорологических данных;
Content:
Preface
Page xi
Daniel S. Wilks
Chapter 1 Introduction
Pages 1-5
Chapter 2 Review of probability
Pages 6-20
Chapter 3 Empirical distributions and exploratory data analysis
Pages 21-63
Chapter 4 Theoretical probability distributions
Pages 64-113
Chapter 5 Hypothesis testing
Pages 114-158
Chapter 6 Statistical weather forecasting
Pages 159-232
Chapter 7 Forecast verification
Pages 233-283
Chapter 8 Time series
Pages 284-358
Chapter 9 Methods for multivariate data
Pages 359-428
Appendix A Example data sets
Pages 429-431
Appendix B Probability tables
Pages 432-438
Appendix C Answers to exercises
Pages 439-443
References
Pages 444-453
Index
Pages 455-464