Stochastic physics and climate modelling

Enviar para

Título:
Stochastic physics and climate modelling
Autor: Tim Palmer (Tim N.); Paul Williams 1952-
Assuntos: Meteorology -- Statistical methods; Meteorology -- Mathematical models; Climatology -- Statistical methods; Climatology -- Mathematical models; Weather forecasting; METEOROLOGIA (MODELOS MATEMÁTICOS); CLIMATOLOGIA (MODELOS MATEMÁTICOS)
Notas: Includes bibliographical references and index.
Descrição: Machine generated contents note: Preface Tim Palmer and Paul Williams; Introduction: stochastic physics and climate modelling Tim Palmer and Paul Williams; 1. Mechanisms of climate variability from years to decades Geoffrey Vallis; 2. Empirical model reduction and the modeling hierarchy in climate dynamics and the geosciences Sergey Kravtsov, Dmitri Kondrashov and Michael Ghil; 3. An applied mathematics perspective on stochastic modelling for climate Andrew J. Majda, Christian Franzke and Boualem Khouider; 4. Predictability in nonlinear dynamical systems with model uncertainty Jinqiao Duan; 5. On modelling physical systems with stochastic models: diffusion versus Le;vy processes Ce;cile Penland and Brian D. Ewald; 6. First passage time analysis for climate prediction Peter C. Chu; 7. Effects of stochastic parametrization on conceptual climate models Daniel S. Wilks; 8. Challenges in stochastic modelling of quasigeostrophic turbulence Timothy DelSole; 9. Orientation of eddy fluxes in geostrophic turbulence Balasubramanya T. Nadiga; 10. Stochastic theories for the irregularity of ENSO Richard Kleeman; 11. Stochastic models of the meridional overturning circulation: time scales and patters of variability Adam H. Monahan, Julie Alexander and Andrew J. Weaver; 12. A stochastic dynamical systems view of the Atlantic Multidecadal Oscillation Henk A. Dijkstra, Leela M. Frankcombe and Anna S. von der Heydt; 13. Centennial-to-millennial-scale Holocene climate variability in the North Atlantic region induced by noise Matthias Prange, Jochem I. Jongma and Michael Schulz; 14. Cloud radiative interactions and their uncertainty in climate models Adrian Tompkins and Francesca Di Giuseppe; 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 Doblas-Reyes, Tim Palmer, Glenn J. Shutts and Antje Weisheimer; 16. Rethinking convective quasi-equilibrium: o
"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"--Provided by publisher.
"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 parameterisation 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. 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. "--Provided by publisher.
Editor: Cambridge, UK Cambridge University Press New York
Data de criação/publicação: 2010
Formato: xv, 480 p ill 26 cm.
Idioma: Inglês

Links

Stochastic physics and climate modelling

Tim Palmer (Tim N.); Paul Williams 1952-

Cambridge, UK Cambridge University Press New York 2010

Buscando em bases de dados remotas. Favor aguardar.