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Manfred Mudelsee
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Climate Time Series Analysis: Classical Statistical and Bootstrap Methods: v. 42 (Atmospheric and Oceanographic Sciences Library) Hardcover – 1 Sept. 2010

by Manfred Mudelsee (Author)
3.7 3.7 out of 5 stars 2 ratings
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Climate is a paradigm of a complex system. Analysing climate data is an exciting challenge, which is increased by non-normal distributional shape, serial dependence, uneven spacing and timescale uncertainties. This book presents bootstrap resampling as a computing-intensive method able to meet the challenge. It shows the bootstrap to perform reliably in the most important statistical estimation techniques: regression, spectral analysis, extreme values and correlation.

This book is written for climatologists and applied statisticians. It explains step by step the bootstrap algorithms (including novel adaptions) and methods for confidence interval construction. It tests the accuracy of the algorithms by means of Monte Carlo experiments. It analyses a large array of climate time series, giving a detailed account on the data and the associated climatological questions. This makes the book self-contained for graduate students and researchers.

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  1. ISBN-10
    9048194814
  2. ISBN-13
    978-9048194810
  3. Edition
    2010th
  4. Publisher
    Springer
  5. Publication date
    1 Sept. 2010
  6. Language
    English
  7. Dimensions
    15.6 x 2.86 x 23.4 cm
  8. Print length
    510 pages
  9. See all details
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Product description

From the Back Cover

Climate is a paradigm of a complex system. Analysing climate data is an excitingchallenge, which is increased by non-normal distributional shape, serial dependence,uneven spacing and timescale uncertainties. This book presents bootstrapresampling as a computing-intensive method able to meet the challenge. It showsthe bootstrap to perform reliably in the most important statistical estimationtechniques: regression, spectral analysis, extreme values and correlation.

This book is written for climatologists and applied statisticians. It explains stepby step the bootstrap algorithms (including novel adaptions) and methods forconfidence interval construction. It tests the accuracy of the algorithms by meansof Monte Carlo experiments. It analyses a large array of climate time series,giving a detailed account on the data and the associated climatological questions.This makes the book self-contained for graduate students and researchers.

Manfred Mudelsee received his diploma in Physics from the University of Heidelberg and his doctoral degree in Geology from the University of Kiel. He was then postdoc in Statisticsat the University of Kent at Canterbury, research scientist in Meteorology at the University of Leipzig and visiting scholar in Earth Sciences at Boston University; currently he does climate research at the Alfred Wegener Institute for Polar and Marine Research, Bremerhaven. His science focuses on climate extremes, time series analysis and mathematical simulation methods. He has authored over 50 peer-reviewed articles. In his 2003 Nature paper, Mudelsee introduced the bootstrap method to flood risk analysis. In 2005, he founded the company Climate Risk Analysis.

About the Author

Manfred Mudelsee received his diploma in Physics from the University of Heidelberg and his doctoral degree in Geology from the University of Kiel. He was then postdoc in Statistics at the University of Kent at Canterbury, research scientist in Meteorology at the University of Leipzig and visiting scholar in Earth Sciences at Boston University; currently he does climate research at the Alfred Wegener Institute for Polar and Marine Research, Bremerhaven. His science focuses on climate extremes, time series analysis and mathematical simulation methods. He has authored over 50 peer-reviewed articles. In his 2003 Nature paper, Mudelsee introduced the bootstrap method to flood risk analysis. In 2005, he founded the company Climate Risk Analysis.

Product details

  • Publisher ‏ : ‎ Springer; 2010th edition (1 Sept. 2010)
  • Language ‏ : ‎ English
  • Hardcover ‏ : ‎ 510 pages
  • ISBN-10 ‏ : ‎ 9048194814
  • ISBN-13 ‏ : ‎ 978-9048194810
  • Dimensions ‏ : ‎ 15.6 x 2.86 x 23.4 cm
  • Customer reviews:
    3.7 3.7 out of 5 stars 2 ratings

About the author

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Manfred Mudelsee

Manfred Mudelsee

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Research Fields

============

● Statistical Analysis of Climate Data

● Risk Analysis

● Mathematical Simulation Methods

Career

=====

● since 10/2007

Visiting/Research Scientist, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany

● since 07/2009

Eingetragener Kaufmann (HRA 201394, Amtsgericht Hannover, Germany)

● since 01/2005

CEO and Founder, Climate Risk Analysis

● 03/2011–06/2011

Guest Scientist, MARUM – Center for Marine Environmental Sciences, University of Bremen, Germany

● 09/2003–08/2004

Visiting Scholar, Department of Earth Sciences, Boston University, USA

● 09/1999–09/2007

Research Scientist, Institute of Meteorology, University of Leipzig, Germany

● 09/1997–08/1999

Postdoc, Institute of Mathematics and Statistics, University of Kent, Canterbury, United Kingdom

● 04/1996–08/1997

Research Fellow, Geological Institute, University of Kiel, Germany

Education

========

● 03/1996

PhD in Geology (magna cum laude), University of Kiel, Germany; Advisor: K. Stattegger

● 06/1990

Diploma in Physics, University of Heidelberg, Germany; Advisor: A. Mangini

Customer reviews

3.7 out of 5 stars
2 global ratings

Top reviews from United Kingdom

cp
3.0 out of 5 stars Colin Burke
Reviewed in the United Kingdom on 22 May 2012
Verified Purchase
This is mainly a book on time series concepts illustrated with applications of bootstrapping methods. Stochastic climate theory is mentioned as the rationale for restricting attention to AR(1) models but stochastic climate theory is not described in any detail (though there are references). Outlining the theory in more depth would add to the readers understanding. Fourier methods are menntioned but not developed in much detail.

Overall, much of the material is common to any time series book however the bootstrapping angle is novel and interesting. An interesting omission for a book on climate time series is the lack of an analysis of global warming temperature trends.
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Dr Valerie Livina
5.0 out of 5 stars Excellent book
Reviewed in the United Kingdom on 9 March 2012
The book by Manfred Mudelsee is a comprehensive description of the modern statistical methods in time series analysis. It does what the title says: provides the overview of the methods of time series analysis in climatology, which is one of the most important fields with applications for time series analysis. In most branches of climatology there are observational records (time series), with the underlying dynamical system being unknown - here time series analysis is one of the few (and maybe even the only) ways of studying such records. This is why the methodology is so important, and this is why a good book on this topic, as the one written by Mudelsee, is so very important.

This book is mathematically advanced, but it is written in clear and accessible language, with directed logic and is easy to follow through all chapters (I know how many science books I abandoned after several good initial chapters then followed by overly specialised applications that were interesting only to authors).

Obviously, it is not a book for "general public": it is not fiction. But I believe it is a book suitable for a very general scientific audience interested in time series analysis and/or climatology, because it provides a modern outlook of the methodology and solid analysis for records that may be of general origin (for instance, researchers working with medical records may well benefit from the book). It could be especially valuable for undergraduate and postgraduate students studying climatology, dynamical systems and time series analysis, because it contains especially useful for beginners practicals and clear algorithm for estimation of confidence intervals and uncertainties. What is particularly important is that the uncertainties are estimated in both data and time scale, which is a serious issue in studying paleorecords.

The book is an excellent introduction into contemporary time series analysis for students and a useful compendium for the active researchers in the field. The book is not cheap. But it is worth its price once you recognize that it will serve you a long time with:

(1) algorithms ready to implement on your computer,
(2) many references to groundbreaking work in climatology and statistics and
(3) a fresh, multidisciplinary look on climate!
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