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Nonlinear and Stochastic Climate Dynamics
Cambridge | English | 2017 | ISBN-10: 110711814X | 468 pages | PDF | 49.76 mb
by Christian L. E. Franzke (Editor), Terence J. O'Kane (Editor)
It is now widely recognized that the climate system is governed by nonlinear, multi-scale processes, whereby memory effects and stochastic forcing by fast processes, such as weather and convective systems, can induce regime behavior. Motivated by present difficulties in understanding the climate system and to aid the improvement of numerical weather and climate models, this book gathers contributions from mathematics, physics and climate science to highlight the latest developments and current research questions in nonlinear and stochastic climate dynamics. Leading researchers discuss some of the most challenging and exciting areas of research in the mathematical geosciences, such as the theory of tipping points and of extreme events including spatial extremes, climate networks, data assimilation and dynamical systems. This book provides graduate students and researchers with a broad overview of the physical climate system and introduces powerful data analysis and modeling methods for climate scientists and applied mathematicians.
Book Description
This edited volume presents the latest developments and current research questions in nonlinear and stochastic climate dynamics. It provides graduate students and researchers with a broad overview of the physical climate system and introduces powerful data analysis and modeling methods for climate scientists and applied mathematicians.
About the Author
Christian L. E. Franzke is a research scientist at Universität Hamburg. His research interests include nonlinear atmospheric and climate dynamics, weather and climate risks, dynamics of extreme events, and stochastic and multi-scale modelling. He has developed new methods for the nonlinear analysis of paleoclimate data, station data and climate model data, and has developed nonlinear stochastic climate models.
Terence J. O'Kane is an Australian Research Council Future Fellow, a principal research scientist at the Commonwealth Scientific and Industrial Research Organisation, Canberra, and Adjunct Professor in Mathematics at the University of Tasmania. His research interests include the statistical mechanics and dynamics of geophysical flows, climate dynamics and variability, ensemble prediction and data assimilation, and time series analysis. He has worked on all aspects of weather prediction including the theory, modelling and operational implementation of ensemble systems. In 2013 he was awarded the J. H. Michell Medal by the Australian Mathematics Society for outstanding research.
Subjects: Applied Atmospheric Sciences, Meteorology
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