Overview
- Provides a reliable guide on how to use short time series in Earth and Solar Sciences
- Offers a mathematically correct way to reconstruct climate
- Contains many practical examples and recommendations
Part of the book series: Progress in Geophysics (PRGEO)
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Table of contents (15 chapters)
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Front Matter
Keywords
About this book
This book gives the reader the basic knowledge of the theory of random processes necessary for applying to study climatic time series. It contains many examples in different areas of time series analysis such as autoregressive modelling and spectral analysis, linear extrapolation, simulation, causality, relations between scalar components of multivariate time series, and reconstructions of climate data.
As an important feature, the book contains many practical examples and recommendations about how to deal and how not to deal with applied problems of time series analysis in climatology or any other science where the time series are short.
Authors and Affiliations
Bibliographic Information
Book Title: Time Series Analysis in Climatology and Related Sciences
Authors: Victor Privalsky
Series Title: Progress in Geophysics
DOI: https://doi.org/10.1007/978-3-030-58055-1
Publisher: Springer Cham
eBook Packages: Earth and Environmental Science, Earth and Environmental Science (R0)
Copyright Information: Springer Nature Switzerland AG 2021
Softcover ISBN: 978-3-030-58054-4Published: 23 November 2020
eBook ISBN: 978-3-030-58055-1Published: 22 November 2020
Series ISSN: 2523-8388
Series E-ISSN: 2523-8396
Edition Number: 1
Number of Pages: XIV, 245
Number of Illustrations: 117 b/w illustrations
Topics: Geophysics/Geodesy, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences, Climate, general