Statistical Analysis in Climate Research
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Product details:
- Edition number New ed
- Publisher Cambridge University Press
- Date of Publication 21 February 2002
- ISBN 9780521012300
- Binding Paperback
- No. of pages496 pages
- Size 280x207x27 mm
- Weight 1120 g
- Language English
- Illustrations 221 b/w illus. 39 tables 0
Categories
Short description:
Self-contained, comprehensive book describing powerful tools in mathematical statistics that are used widely in climatological research.
MoreLong description:
Climatology is, to a large degree, the study of the statistics of our climate. The powerful tools of mathematical statistics therefore find wide application in climatological research. The purpose of this book is to help the climatologist understand the basic precepts of the statistician's art and to provide some of the background needed to apply statistical methodology correctly and usefully. The book is self contained: introductory material, standard advanced techniques, and the specialised techniques used specifically by climatologists are all contained within this one source. There are a wealth of real-world examples drawn from the climate literature to demonstrate the need, power and pitfalls of statistical analysis in climate research. Suitable for graduate courses on statistics for climatic, atmospheric and oceanic science, this book will also be valuable as a reference source for researchers in climatology, meteorology, atmospheric science, and oceanography.
' ... this book ... should form the centrepiece of the climate analyst's reference shelf'. Robert E. Livezey, Nature
Table of Contents:
1. Introduction; Part I. Fundamentals: 2. Probability theory; 3. Distributions of climate variables; 4. Concepts in statistical inference; 5. Estimation; Part II. Confirmation and Analysis: 6. The statistical test of a hypothesis; 7. Analysis of atmospheric circulation problems; Part III. Fitting Statistical Models: 8. Regression; 9. Analysis of variance; Part IV. Time Series: 10. Time series and stochastic processes; 11. Parameters of univariate and bivariate time series; 12. Estimating covariance functions and spectra; Part V. Eigen Techniques: 13. Empirical orthogonal functions; 14. Canonical correlation analysis; 15. POP analysis; 16. Complex eigentechniques; Part VI. Other Topics: 17. Specific statistical concepts in climate research; 18. Forecast quality evaluation; Part VII. Appendices.
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