This book introduces stochastic dynamical systems theory in order to synthesize our current knowledge of climate variability. Nonlinear processes, such as advection, radiation and turbulent mixing, play a central role in climate variability. These processes can give rise to transition phenomena, associated with tipping or bifurcation points, once external conditions are changed. The theory of dynamical systems provides a systematic way to study these transition phenomena. Its stochastic extension also forms the basis of modern (nonlinear) data analysis techniques, predictability studies and data assimilation methods. Early chapters apply the stochastic dynamical systems framework to a hierarchy of climate models to synthesize current knowledge of climate variability. Later chapters analyse phenomena such as the North Atlantic Oscillation, El Niño/Southern Oscillation, Atlantic Multidecadal Variability, Dansgaard-Oeschger events, Pleistocene ice ages and climate predictability. This book will prove invaluable for graduate students and researchers in climate dynamics, physical oceanography, meteorology and paleoclimatology.
This book introduces stochastic dynamical systems theory in order to synthesize our current knowledge of climate variability. Nonlinear processes, such as advection, radiation and turbulent mixing, play a central role in climate variability. These processes can give rise to transition phenomena, associated with tipping or bifurcation points, once external conditions are changed. The theory of dynamical systems provides a systematic way to study these transition phenomena. Its stochastic extension also forms the basis of modern (nonlinear) data analysis techniques, predictability studies and data assimilation methods. Early chapters apply the stochastic dynamical systems framework to a hierarchy of climate models to synthesize current knowledge of climate variability. Later chapters analyse phenomena such as the North Atlantic Oscillation, El Niño/Southern Oscillation, Atlantic Multidecadal Variability, Dansgaard-Oeschger events, Pleistocene ice ages and climate predictability. This book will prove invaluable for graduate students and researchers in climate dynamics, physical oceanography, meteorology and paleoclimatology.
Über den Autor
Henk A. Dijkstra is Professor of Dynamical Oceanography at the Institute for Marine and Atmospheric Research, Department of Physics and Astronomy, Utrecht University, The Netherlands. His main research interests are in the application of dynamical systems methods to problems in climate variability and climate modeling. He is the author of Nonlinear Physical Oceanography (2nd edition, 2005) and Dynamical Oceanography (2008). He is a member of the Dutch Royal Academy of Arts and Sciences. In 2005, he received the Lewis Fry Richardson medal from the European Geosciences Union and in 2009 he was elected a Fellow of the Society for Industrial and Applied Mathematics.
Inhaltsverzeichnis
1. Climate variability; 2. Deterministic dynamical systems; 3. Introduction to stochastic calculus; 4. Stochastic dynamical systems; 5. Analysing data from stochastic dynamical systems; 6. The climate modeling hierarchy; 7. The North Atlantic Oscillation; 8. El Niño variability; 9. Multidecadal variability; 10. Dansgaard-Oeschger events; 11. The Pleistocene ice ages; 12. Predictability.
