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Nonlinear Processes in Geophysics An interactive open-access journal of the European Geosciences Union
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Volume 21, issue 2 | Copyright

Special issue: Complex network approaches to analyzing and modeling nonlinear...

Nonlin. Processes Geophys., 21, 451-462, 2014
https://doi.org/10.5194/npg-21-451-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 01 Apr 2014

Research article | 01 Apr 2014

Regional and inter-regional effects in evolving climate networks

J. Hlinka1, D. Hartman1, N. Jajcay1, M. Vejmelka1, R. Donner2, N. Marwan2, J. Kurths2, and M. Paluš1 J. Hlinka et al.
  • 1Department of Nonlinear Dynamics and Complex Systems, Institute of Computer Science, Academy of Sciences of the Czech Republic, Pod vodarenskou vezi 2, 182 07 Prague 8, Czech Republic
  • 2Potsdam Institute for Climate Impact Research (PIK), 14473 Potsdam, Germany

Abstract. Complicated systems composed of many interacting subsystems are frequently studied as complex networks. In the simplest approach, a given real-world system is represented by an undirected graph composed of nodes standing for the subsystems and non-oriented unweighted edges for interactions present among the nodes; the characteristic properties of the graph are subsequently studied and related to the system's behaviour. More detailed graph models may include edge weights, orientations or multiple types of links; potential time-dependency of edges is conveniently captured in so-called evolving networks. Recently, it has been shown that an evolving climate network can be used to disentangle different types of El Niño episodes described in the literature. The time evolution of several graph characteristics has been compared with the intervals of El Niño and La Niña episodes. In this study we identify the sources of the evolving network characteristics by considering a reduced-dimensionality description of the climate system using network nodes given by rotated principal component analysis. The time evolution of structures in local intra-component networks is studied and compared to evolving inter-component connectivity.

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