The European Physical Journal Special Topics

, Volume 174, Issue 1, pp 157-179

First online:

Complex networks in climate dynamics

Comparing linear and nonlinear network construction methods
  • J. F. DongesAffiliated withPotsdam Institute for Climate Impact ResearchInstitute of Physics, University of Potsdam Email author 
  • , Y. ZouAffiliated withPotsdam Institute for Climate Impact Research
  • , N. MarwanAffiliated withPotsdam Institute for Climate Impact Research
  • , J. KurthsAffiliated withPotsdam Institute for Climate Impact ResearchDepartment of Physics, Humboldt University

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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.