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Statistical Methods in the Atmospheric Sciences

TextbookHandbook / Manual

Series: International Geophysics Series Volume: 100

By: Daniel S Wilks

688 pages, figures, tables

Academic Press

Hardback | Jul 2011 | Edition: 3 | #191228 | ISBN-13: 9780123850225
Availability: Usually dispatched within 7 days Details
NHBS Price: £60.99 $75/€69 approx

About this book

Fundamentally, statistics is concerned with managing data and making inferences and forecasts in the face of uncertainty. It should not be surprising, therefore, that statistical methods have a key role to play in the atmospheric sciences. It is the uncertainty in atmospheric behavior that continues to move research forward and drive innovations in atmospheric modeling and prediction. 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.

I would strongly recommend this book... To those who already posses the first edition and are satisfied users, you would be hard-pressed to do without the second edition.
- Bulletin of the American Meteorological Society

"What makes this book specific to meterology, and not just to applied statistics, are it's extensive examples and two chapters on statistcal forecasting and forecast evaluation."
- William (Matt) Briggs, Weill Medical College of Cornell University


I Preliminaries
Chapter 1 Introduction
Chapter 2 Review of Probability

II Univariate Statistics
Chapter 3 Empirical Distributions and Exploratory Data Analysis
Chapter 4 Parametric Probability Distributions
Chapter 5 Frequentist Statistical Inference
Chapter 6 Bayesian Inference
Chapter 7 Statistical Forecasting
Chapter 8 Forecast Verification
Chapter 9 Time Series

III Multivariate Statistics
Chapter 10 Matrix Algebra and Random Matrices
Chapter 11 The Multivariate Normal (MVN) Distribution
Chapter 12 Principal Component (EOF) Analysis
Chapter 13 Canonical Correlation Analysis (CCA)
Chapter 14 Discrimination and Classification
Chapter 15 Cluster Analysis

Appendix A Example Data Sets
Appendix B Probability Tables
Appendix C Answers to Exercises

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