Refine
Year of publication
Document Type
- Article (280)
- Monograph/Edited Volume (8)
- Postprint (7)
- Preprint (6)
- Other (1)
Language
- English (302) (remove)
Is part of the Bibliography
- yes (302) (remove)
Keywords
- Complex networks (5)
- Event synchronization (4)
- precipitation (3)
- synchronization (3)
- Amazon rainforest (2)
- Extreme rainfall (2)
- Synchronization (2)
- channel (2)
- classification (2)
- climate networks (2)
Institute
- Institut für Physik und Astronomie (225)
- Interdisziplinäres Zentrum für Dynamik komplexer Systeme (44)
- Institut für Geowissenschaften (21)
- Department Psychologie (13)
- Institut für Biochemie und Biologie (4)
- Extern (3)
- Department Linguistik (2)
- Institut für Informatik und Computational Science (2)
- Mathematisch-Naturwissenschaftliche Fakultät (2)
- Department Sport- und Gesundheitswissenschaften (1)
In recent years, complex network analysis facilitated the identification of universal and unexpected patterns in complex climate systems. However, the analysis and representation of a multiscale complex relationship that exists in the global climate system are limited. A logical first step in addressing this issue is to construct multiple networks over different timescales. Therefore, we propose to apply the wavelet multiscale correlation (WMC) similarity measure, which is a combination of two state-of-the-art methods, viz. wavelet and Pearson’s correlation, for investigating multiscale processes through complex networks. Firstly we decompose the data over different timescales using the wavelet approach and subsequently construct a corresponding network by Pearson’s correlation. The proposed approach is illustrated and tested on two synthetics and one real-world example. The first synthetic case study shows the efficacy of the proposed approach to unravel scale-specific connections, which are often undiscovered at a single scale. The second synthetic case study illustrates that by dividing and constructing a separate network for each time window we can detect significant changes in the signal structure. The real-world example investigates the behavior of the global sea surface temperature (SST) network at different timescales. Intriguingly, we notice that spatial dependent structure in SST evolves temporally. Overall, the proposed measure has an immense potential to provide essential insights on understanding and extending complex multivariate process studies at multiple scales.
We propose a new autonomous dynamical system of dimension N=4 that demonstrates the regime of stable two- frequency motions and period-doubling bifurcations of a two-dimensional torus. It is shown that the period-doubling bifurcation of the two-dimensional torus is not followed by the resonance phenomenon, and the two-dimensional ergodic torus undergoes a period-doubling bifurcation. The interaction of two generators is also analyzed. The phenomenon of external and mutual synchronization of two-frequency oscillations is observed, for which winding number locking on a two- dimensional torus takes place