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Stochastic Physics and Climate Modelling

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Overview

This is the first book to promote the use of stochastic, or random, processes to understand, model and predict our climate system. One of the most important applications of this technique is in the representation of comprehensive climate models of processes which, although crucial, are too small or fast to be explicitly modeled. The book shows how stochastic methods can lead to improvements in climate simulation and prediction, compared with more conventional bulk-formula parameterization procedures. Beginning with expositions of the relevant mathematical theory, the book moves on to describe numerous practical applications. It covers the complete range of time scales of climate variability, from seasonal to decadal, centennial, and millennial. With contributions from leading experts in climate physics, this book is invaluable to anyone working on climate models, including graduate students and researchers in the atmospheric and oceanic sciences, numerical weather forecasting, climate prediction, climate modeling, and climate change.

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Editorial Reviews

From the Publisher
"...a timely thought-provoking book on one of the most challenging and paradoxical scientific issues: stochastic physics may well be the key to substantial progress being made in climate change modelling and rediction, and to resolve the large uncertainties that exist. It is therefore a must for anyone having a keen interest in climate modelling, especially graduate students and researchers involved in climate studies." - Nonlinear Processes in Geophysics

"The book does a very good job of reviewing the state of the art of stochastic physics in climate modeling, and can be wholeheartedly recommended to any researcher seriously interested in that line of research" - Philip Sura, Bulletin of the American Meteorological Society, October 2010

"...the articles cover a lot of ground in very different and important areas of climate research. Climate scientists should take notice of the many important contributions coming out of a relatively small and diverse community dealing with stochastic processes. Thus, this book serves a very useful purpose in providing a broad and current review of stochastic methods used in climate research. ... the book does a very good job of reviewing the state of the art of stochastic physics in climate modeling, and can be wholeheartedly recommended to any researcher seriously interested in that line of research." Bulletin of the American Meteorological Society

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Product Details

  • ISBN-13: 9780521761055
  • Publisher: Cambridge University Press
  • Publication date: 12/31/2009
  • Language: Italian
  • Pages: 496
  • Sales rank: 1,045,744
  • Product dimensions: 6.90 (w) x 9.80 (h) x 1.10 (d)

Meet the Author

Tim Palmer is Head of the Probability Forecasting and Diagnostics Division at the European Centre for Medium-Range Weather Forecasts (ECMWF). He has won the Royal Society Esso Energy Award, the Royal Meteorological Society Adrian Gill Prize, and the American Meteorological Society Jule Charney Award. He is a fellow of the Royal Society, the Royal Meteorological Society, the American Meteorological Society, and Academia Europaea. He is a lead author of the Intergovernmental Panel on Climate Change (IPCC), co-chair of the Scientific Steering Group of the UN World Meteorological Organisation's Climate Variability and Predictability (CLIVAR) project, and coordinator of two European Union climate prediction projects (PROVOST and DEMETER). He has had numerous appearances on radio and TV, in relation to weather, climate and chaos theory, and has co-edited another book with Cambridge University Press - Predictability of Weather and Climate - in 2006.

Paul Williams is a Research Fellow at the Department of Meteorology, University of Reading. He has won the Royal Astronomical Society Blackwell Prize (2004) and the Royal Meteorological Society Rupert Ford Award (2005), and has received a prestigious Crucible Fellowship from the National Endowment for Science, Technology and the Arts (2007). He was the lead author of a climate change report commissioned and published by the European Parliament (2004). He is a Fellow of the Royal Meteorological Society, the Institute of Physics, and the Royal Astronomical Society. His research findings have been reported widely in the media, including feature articles in New Scientist and the Financial Times, and a panel discussion on BBC Radio 4.

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Table of Contents

List of contributors vii

Preface xi

1 Mechanisms of climate variability from years to decades Geoffrey K. Vallis 1

2 Empirical model reduction and the modelling hierarchy in climate dynamics and the geosciences Sergey Kravtsov Dmitri Kondrashov Michael Ghil 35

3 An applied mathematics perspective on stochastic modelling for climate Andrew J. Majda Christian Franzke Boualem Khouider 73

4 Predictability, in nonlinear dynamical systems with model uncertainty Jinqiao Duan 105

5 On modelling physical systems with stochastic models: diffusion versus L?vy processes C?cile Penland Brian D. Ewald 133

6 First passage time analysis for climate prediction Peter C. Chu 157

7 Effects of stochastic parameterisation on conceptual climate models Daniel S. Wilks 191

8 Challenges in stochastic modelling of quasi-geostrophic turbulence Timothy DelSole 207

9 Stochastic versus deterministic backscatter of potential enstrophy in geostrophic turbulence Balasubramanya T. Nadiga 231

10 Stochastic theories for the irregularity of ENSO Richard Kleeman 248

11 Stochastic models of the meridional overturning circulation: time scales and patterns of variability Adam H. Monahan Julie Alexander Andrew J. Weaver 266

12 The Atlantic Multidecadal Oscillation: a stochastic dynamical systems view Leela M. Frankcombe Henk A. Dijkstra Anna S. von der Heydt 287

13 Centennial-to-millennial-scale Holocene climate variability in .the North Atlantic region induced by noise Matthias Prange Jochem I. Jongma Michael Schulz 307

14 Cloud-radiation interactions and their uncertainty in climate models Adrian M. Tompkins Francesca Di Giuseppe 327

15 Impact of a quasi-stochastic cellular automaton backscatter scheme on the systematic error and seasonal prediction skill of a global climate model Judith Berner Francisco J. Doblas-Reyes Tim N. Palmer Glenn J. Shutts Antje Weisheimer 375

16 Rethinking convective quasi-equilibrium: observational constraints for stochastic convective schemes in climate models J. David Neelin Ole Peters Johnny W.-B. Lin Katrina Hales Christopher E. Holloway 396

17 Comparison of stochastic parameterisation approaches in a single-column model Michael A. Ball Robert S. Plant 424

18 Stochastic parameterisation of multiscale processes using techniques from computer game physics Thomas Allen Glenn J. Shutts Christopher J. Smith 446

Index 464

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