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Statistical Methods for Climate Scientists PDF

545 Pages·2021·8.0487 MB·other
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by Timothy DelSole, Michael Tippett| 2021| 545 pages| 8.0487| other

About Statistical Methods for Climate Scientists

<span>A comprehensive introduction to the most commonly used statistical methods relevant in atmospheric, oceanic and climate sciences. Each method is described step-by-step using plain language, and illustrated with concrete examples, with relevant statistical and scientific concepts explained as needed. Particular attention is paid to nuances and pitfalls, with sufficient detail to enable the reader to write relevant code. Topics covered include hypothesis testing, time series analysis, linear regression, data assimilation, extreme value analysis, Principal Component Analysis, Canonical Correlation Analysis, Predictable Component Analysis, and Covariance Discriminant Analysis. The specific statistical challenges that arise in climate applications are also discussed, including model selection problems associated with Canonical Correlation Analysis, Predictable Component Analysis, and Covariance Discriminant Analysis. Requiring no previous background in statistics, this is a highly accessible textbook and reference for students and early-career researchers in the climate sciences.</span>

Detailed Information

Author:Timothy DelSole, Michael Tippett
Publication Year:2021
ISBN:1108472419
Pages:545
Language:other
File Size:8.0487
Format:PDF
Price:FREE
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