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.
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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.
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Hardcover. Condition: new. Hardcover. 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 Nino/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. Climate variability is controlled by nonlinear processes, which can give rise to transition behavior due to tipping points and extreme behavior. This book presents stochastic dynamical systems theory, synthesizing our current knowledge of climate variability. An invaluable resource for graduate students and researchers in climate dynamics, physical oceanography, meteorology and paleoclimatology. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780521879170
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