TY  - JOUR
A1  - Donges, Jonathan Friedemann
A1  - Zou, Yong
A1  - Marwan, Norbert
A1  - Kurths, Jürgen
T1  - Complex networks in climate dynamics : comparing linear and nonlinear network construction methods
N2  - 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.
Y1  - 2009
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/31628
UR  - http://www.springerlink.com/content/1951-6355
SN  - 1951-6355
ER  -