- Pub. Date:
- Cambridge University Press
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 modelled. 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 modelling and climate change.
|Publisher:||Cambridge University Press|
|Product dimensions:||6.90(w) x 9.80(h) x 1.10(d)|
Table of Contents
List of contributors vii
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