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Characterizing Flows by Complex Network Methods

Urheber*innen
/persons/resource/Reik.Donner

Donner,  Reik V.
Potsdam Institute for Climate Impact Research;

/persons/resource/Michael.Lindner

Lindner,  Michael
Potsdam Institute for Climate Impact Research;

Tupikina,  L.
External Organizations;

Molkenthin,  N.
External Organizations;

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Zitation

Donner, R. V., Lindner, M., Tupikina, L., Molkenthin, N. (2019): Characterizing Flows by Complex Network Methods. - In: Macau, E. E. N. (Ed.), A Mathematical Modeling Approach from Nonlinear Dynamics to Complex Systems, Cham : Springer, 197-226.
https://doi.org/10.1007/978-3-319-78512-7_11


Zitierlink: https://publications.pik-potsdam.de/pubman/item/item_22274
Zusammenfassung
During the last years, complex network approaches have demonstrated their great potentials as versatile tools for exploring the structural as well as dynamical properties of complex systems from a variety of different fields. Among others, recent successful examples include their application to studying flow systems in both, abstract mathematical and real-world geophysical contexts. In this context, two recent developments are particularly notable: on the one hand, correlation-based functional network approaches allow inferring statistical interrelationships, for example between macroscopic regions of the Earth’s climate system, which are hidden to more classical statistical analysis techniques. On the other hand, Lagrangian flow networks provide a new tool to identify dynamically relevant structures in atmosphere, ocean or, more generally, the phase space of complex systems. This chapter summarizes these recent developments and provides some illustrative examples highlighting the application of both concepts to selected paradigmatic low-dimensional model systems.