Statistical Methods in the Atmospheric Sciences: Volume 100

Statistical Methods in the Atmospheric Sciences: Volume 100

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Statistical Methods in the Atmospheric Sciences, Third Edition, explains the latest statistical methods used to describe, analyze, test, and forecast atmospheric data. This revised and expanded text is intended to help students understand and communicate what their data sets have to say, or to make sense of the scientific literature in meteorology, climatology, and related disciplines.

In this new edition, what was a single chapter on multivariate statistics has been expanded to a full six chapters on this important topic. Other chapters have also been revised and cover exploratory data analysis, probability distributions, hypothesis testing, statistical weather forecasting, forecast verification, and time series analysis. There is now an expanded treatment of resampling tests and key analysis techniques, an updated discussion on ensemble forecasting, and a detailed chapter on forecast verification. In addition, the book includes new sections on maximum likelihood and on statistical simulation and contains current references to original research. Students will benefit from pedagogical features including worked examples, end-of-chapter exercises with separate solutions, and numerous illustrations and equations.

This book will be of interest to researchers and students in the atmospheric sciences, including meteorology, climatology, and other geophysical disciplines.
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Product details

  • Hardback | 704 pages
  • 195.58 x 236.22 x 33.02mm | 1,383.45g
  • Academic Press Inc
  • San Diego, United States
  • English
  • 3rd edition
  • Illustrations, maps
  • 0123850223
  • 9780123850225
  • 92,279

Table of contents

I Preliminaries
Ch. 1 Introduction
Ch. 2 Review of Probability
II Univariate Statistics
Ch. 3 Empirical Distributions and Exploratory Data Analysis
Ch. 4 Parametric Probability Distributions
Ch. 5 Frequentist Statistical Inference
Ch. 6 Bayesian Inference
Ch. 7 Statistical Forecasting
Ch. 8 Forecast Verification
Ch. 9 Time Series
III Multivariate Statistics
Ch. 10 Matrix Algebra and Random Matrices
Ch. 11 The Multivariate Normal (MVN) Distribution
Ch. 12 Principal Component (EOF) Analysis
Ch. 13 Canonical Correlation Analysis (CCA)
Ch. 14 Discrimination and Classification
Ch. 15 Cluster Analysis
Appendix A Example Data Sets
Appendix B Probability Tables
Appendix C Answers to Exercises
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Review quote

"I would strongly recommend this book... To those who already posses the first would be hard-pressed to do without the second."
--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
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About Daniel S. Wilks

Has been a member of the Atmospheric Sciences faculty at Cornell University since 1987, and is the author of Statistical Methods in the Atmospheric Sciences (2011, Academic Press), which is in its third edition and has been continuously in print since 1995. Research areas include statistical forecasting, forecast postprocessing, and forecast evaluation.
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Rating details

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