Multi-scale event synchronization analysis for unravelling climate processes: a wavelet-based approach
- The temporal dynamics of climate processes are spread across different timescales and, as such, the study of these processes at only one selected timescale might not reveal the complete mechanisms and interactions within and between the (sub-) processes. To capture the non-linear interactions between climatic events, the method of event synchronization has found increasing attention recently. The main drawback with the present estimation of event synchronization is its restriction to analysing the time series at one reference timescale only. The study of event synchronization at multiple scales would be of great interest to comprehend the dynamics of the investigated climate processes. In this paper, the wavelet-based multi-scale event synchronization (MSES) method is proposed by combining the wavelet transform and event synchronization. Wavelets are used extensively to comprehend multi-scale processes and the dynamics of processes across various timescales. The proposed method allows the study of spatio-temporal patterns acrossThe temporal dynamics of climate processes are spread across different timescales and, as such, the study of these processes at only one selected timescale might not reveal the complete mechanisms and interactions within and between the (sub-) processes. To capture the non-linear interactions between climatic events, the method of event synchronization has found increasing attention recently. The main drawback with the present estimation of event synchronization is its restriction to analysing the time series at one reference timescale only. The study of event synchronization at multiple scales would be of great interest to comprehend the dynamics of the investigated climate processes. In this paper, the wavelet-based multi-scale event synchronization (MSES) method is proposed by combining the wavelet transform and event synchronization. Wavelets are used extensively to comprehend multi-scale processes and the dynamics of processes across various timescales. The proposed method allows the study of spatio-temporal patterns across different timescales. The method is tested on synthetic and real-world time series in order to check its replicability and applicability. The results indicate that MSES is able to capture relationships that exist between processes at different timescales.…
Author details: | Ankit AgarwalORCiDGND, Norbert MarwanORCiDGND, Rathinasamy MaheswaranORCiD, Bruno MerzORCiDGND, Jürgen KurthsORCiDGND |
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DOI: | https://doi.org/10.5194/npg-24-599-2017 |
ISSN: | 1023-5809 |
Title of parent work (English): | Nonlinear processes in geophysics |
Publisher: | Copernicus |
Place of publishing: | Göttingen |
Publication type: | Article |
Language: | English |
Year of first publication: | 2017 |
Publication year: | 2017 |
Release date: | 2020/04/20 |
Volume: | 24 |
Number of pages: | 13 |
First page: | 599 |
Last Page: | 611 |
Funding institution: | Deutsche Forschungsgemeinschaft (DFG) within graduate research training group Natural risk in a changing world (NatRiskChange) at the University of Potsdam [GRK 2043/1]; RSF support (Russian Science Foundation) [16-12-10198]; Inspire Faculty Award, Department of Science and Technology, India |
Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften |
Peer review: | Referiert |
Institution name at the time of the publication: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Erd- und Umweltwissenschaften |