Statistical Methods in the Atmospheric Sciences
An Introduction
1st Edition
Published on 1. March 1995
467 pages
978-0-08-054172-3 (ISBN)
Description
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
More details
Other editions
New editions
D. S. Wilks | Daniel S. Wilks
Statistical Methods in the Atmospheric Sciences
E-Book
05/2014
2nd Edition
Academic Press
€68.95
Available for download
Additional editions
Book
03/1995
Academic Press
€54.46
Article exhausted; check different version
Person
Daniel S. Wilks is a Professor Emeritus at Cornell University and has been a Member of the Atmospheric Sciences faculty since 1987. His research focuses on the application of statistical methods for the quantification and analysis of uncertainty in meteorological and climatological data and forecasts. Dr. Wilks has taught courses on statistics in the atmospheric sciences and has been an Author or Coauthor of more than 100 peer-reviewed research articles.
Content
Introduction. Review of Probability. Empirical Distributions and Exploratory Data Analysis. Theoretical Probability Distributions. Hypothesis Testing. Statistical Weather Forecasting. Forecast Verification. Time Series. Methodsfor Multivariate Data. Chapter Exercises. Appendices: Example Data Sets. Selected Probability Tables. Answers to Exercises. References. Subject Index.
