Complex networks in climate dynamics - Comparing linear and nonlinear network construction methods

Details Complex networks in climate dynamics - Comparing linear and nonlinear network construction methods Complex networks in climate dynamics - Comparing linear and nonlinear network construction methods

2009-07-24

arxiv.org/abs/0907.4359v1

Eur. Phys. J. Special Topics, 174, 2009, 157-179

Physics

Data Analysis, Statistics and Probability

24 pages, 10 figures

Scientific paper

10.1140/epjst/e2009-01098-2

Complex network theory provides a powerful framework to statistically investigate the topology of local and non-local statistical interrelationships, i.e. teleconnections, in the climate system. Climate networks constructed from the same global climatological data set using the linear Pearson correlation coefficient or the nonlinear mutual information as a measure of dynamical similarity between regions, are compared systematically on local, mesoscopic and global topological scales. A high degree of similarity is observed on the local and mesoscopic topological scales for surface air temperature fields taken from AOGCM and reanalysis data sets. We find larger differences on the global scale, particularly in the betweenness centrality field. The global scale view on climate networks obtained using mutual information offers promising new perspectives for detecting network structures based on nonlinear physical processes in the climate system.

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