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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.show moreshow less

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Metadaten
Author:Ankit AgarwalORCiDGND, Norbert MarwanORCiD, Maheswaran Rathinasamy, Bruno MerzORCiD, Jürgen KurthsORCiDGND
DOI:https://doi.org/10.5194/npg-24-599-2017
ISSN:1023-5809
Parent Title (English):Nonlinear processes in geophysics
Publisher:Copernicus
Place of publication:Göttingen
Document Type:Article
Language:English
Year of first Publication:2017
Year of Completion:2017
Release Date:2020/04/20
Volume:24
Pagenumber:13
First Page:599
Last Page:611
Funder: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 Erd- und Umweltwissenschaften
Peer Review:Referiert