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Multi-scale event synchronization analysis for unravelling climate processes: a wavelet-based approach

机译：揭示气候过程的多尺度事件同步分析：基于小波的方法

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摘要

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 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.
机译：气候过程的时间动态分布在不同的时间尺度上，因此，仅在一个选定的时间尺度上对这些过程进行研究可能无法揭示（子）过程内部和之间的完整机制和相互作用。为了捕获气候事件之间的非线性相互作用，事件同步方法近来受到越来越多的关注。当前的事件同步估计的主要缺点是它仅限于在一个参考时标上分析时间序列。研究多尺度事件同步对于理解被调查气候过程的动力学将具有极大的兴趣。结合小波变换和事件同步，提出了基于小波的多尺度事件同步方法。小波被广泛地用于理解多尺度过程以及跨不同时间尺度的过程动力学。所提出的方法可以研究跨不同时标的时空模式。该方法在合成时间序列和实际时间序列上进行了测试，以检查其可重复性和适用性。结果表明，MSES能够捕获不同时间范围内流程之间存在的关系。

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