The European Physical Journal Special Topics

, Volume 174, Issue 1, pp 157–179

Complex networks in climate dynamics

Comparing linear and nonlinear network construction methods

Authors

    • Potsdam Institute for Climate Impact Research
    • Institute of Physics, University of Potsdam
  • Y. Zou
    • Potsdam Institute for Climate Impact Research
  • N. Marwan
    • Potsdam Institute for Climate Impact Research
  • J. Kurths
    • Potsdam Institute for Climate Impact Research
    • Department of PhysicsHumboldt University
Article

DOI: 10.1140/epjst/e2009-01098-2

Cite this article as:
Donges, J., Zou, Y., Marwan, N. et al. Eur. Phys. J. Spec. Top. (2009) 174: 157. doi:10.1140/epjst/e2009-01098-2

Abstract

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.

Copyright information

© EDP Sciences and Springer 2009