Henk A. Dijkstra

Networks in Climate (eBook, ePUB)

• Format: ePub

Produktbeschreibung

Over the last two decades the complex network paradigm has proven to be a fruitful tool for the investigation of complex systems in many areas of science; for example, the Internet, neural networks and social networks. This book provides an overview of applications of network theory to climate variability, such as the El Nino/Southern Oscillation and the Indian Monsoon, presenting recent important results obtained with these techniques and showing their potential for further development and research. The book is aimed at researchers and graduate students in climate science. A basic background in physics and mathematics is required. Several of the methodologies presented here will also be valuable to a broader audience of those interested in network science, for example, from biomedicine, ecology and economics.

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Produktdetails

• Verlag: Cambridge University Press
• Erscheinungstermin: 28. Februar 2019
• Englisch
• ISBN-13: 9781108657778
• Artikelnr.: 57069184

Autorenporträt

Henk A. Dijkstra is a Professor of Dynamical Oceanography at the Institute for Marine and Atmospheric Research within the Department of Physics and Astronomy at the University of Utrecht, The Netherlands. His research focuses mainly on the stability of the ocean circulation and on the physics of climate variability. He is author of the books Nonlinear Physical Oceanography, (Second edition, 2005), Dynamical Oceanography (2008), and Nonlinear Climate Dynamics (Cambridge, 2013). He is a member of the Netherlands Royal Academy of Arts and Sciences (KNAW). He was awarded the Lewis Fry Richardson Medal from the European Geosciences Union in 2005, and he was elected a Fellow of the Society for Industrial and Applied Mathematics (SIAM) in 2009.

Inhaltsangabe

Preface
Acknowledgments
1. The climate system
2. Climate variability
3. Climate data analysis
4. Climate networks: construction methods and analysis
5. Computational tools for network analysis
6. Applications to atmospheric variability
7. Applications to oceanic variability
8. Climate tipping behaviour
9. Network-based prediction
References
Index.