Daniel S. Wilks

Statistical Methods in the Atmospheric Sciences (eBook, ePUB)

• Format: ePub

Produktbeschreibung

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.

• Accessible presentation and explanation of techniques for atmospheric data summarization, analysis, testing and forecasting
• Many worked examples
• End-of-chapter exercises, with answers provided

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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 704
• Erscheinungstermin: 4. Juli 2011
• Englisch
• ISBN-13: 9780123850232
• Artikelnr.: 47274592

Autorenporträt

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.

Inhaltsangabe

I Preliminaries1. Introduction2. Review of Probability
II Univariate Statistics3. Empirical Distributions and Exploratory Data
Analysis4. Parametric Probability Distributions5. Frequentist Statistical
Inference6. Bayesian Inference7. Statistical Forecasting8. Forecast
Verification9. Time Series
III Multivariate Statistic10. Matrix Algebra and Random Matrices11. The
Multivariate Normal (MVN) Distribution12. Principal Component (EOF)
Analysis13. Canonical Correlation Analysis (CCA)14. Discrimination and
Classification15. Cluster Analysis
AppendixA. Example Data SetsB. Probability TablesC. Answers to Exercises