Statistical Methods in the Atmospheric Sciences,

Edition 5

Editors: By Daniel S. Wilks

Publication Date: 10 Apr 2026

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Statistical Methods in the Atmospheric Sciences, Fifth Edition provides a structured exploration of the statistical techniques essential for analyzing atmospheric data. The book begins with foundational concepts in probability, setting the stage for more advanced topics. It then covers univariate statistics, including empirical distributions, parametric probability models, and both frequentist and Bayesian inference methods, offering tools for rigorous data analysis and interpretation. The text also addresses statistical forecasting and ensemble forecasting, along with methods for verifying forecast accuracy. In addition, time series analysis is explored in detail, enabling readers to understand temporal dependencies in atmospheric data.

The book advances into multivariate statistics, presenting matrix algebra and random matrices as mathematical foundations. It discusses the multivariate normal distribution, principal component analysis (EOF), and multivariate analysis of vector pairs to handle complex, multidimensional atmospheric datasets. Techniques for discrimination, classification, and cluster analysis are also examined, providing methods for categorizing and interpreting atmospheric patterns. Supplementary materials include example data sets, probability tables, and a glossary of symbols and acronyms, along with answers to exercises that reinforce learning.

Key Features

Facilitates understanding and use of applied statistical methods through rigorous yet conversational treatment of applied statistics
Offers a unique, statistical approach to forecasting, ensemble forecasting, and forecast evaluation
Allows readers to see the operation of various methods in an accessible and transparent way using small datasets

About the author

By Daniel S. Wilks, Cornell University, USA

1. Introduction
2. Review of Probability II Univariate Statistics
3. Empirical Distributions and Exploratory Data Analysis
4. Parametric Probability Distributions
5. Frequentist Statistical Inference
6. Bayesian Inference
7. Statistical Forecasting
8. Ensemble Forecasting
9. Forecast Verification
10. Time Series III Multivariate Statistics
11. Matrix Algebra and Random Matrices
12. The Multivariate Normal (MVN) Distribution
13. Principal Component (EOF) Analysis
14. Multivariate Analysis of Vector Pairs
15. Discrimination and Classification
16. Cluster Analysis

Appendix
A. Example Data Sets
B. Probability Tables
C. Symbols and Acronyms
D. Answers to Exercises

ISBN: 9780443490026

Page Count: 818

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Faculty, advanced undergraduate and graduate students, researchers, and practitioners in Atmospheric Sciences, Meteorology, Climatology, and Oceanography