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Volume 25, issue 3 | Copyright
Nonlin. Processes Geophys., 25, 497-510, 2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 10 Jul 2018

Research article | 10 Jul 2018

Simple statistics for complex Earthquake time distributions

Teimuraz Matcharashvili1, Takahiro Hatano2, Tamaz Chelidze1, and Natalia Zhukova1 Teimuraz Matcharashvili et al.
  • 1M. Nodia Institute of Geophysics, Tbilisi State University, Tbilisi, Georgia
  • 2Earthquake Research Institute, the University of Tokyo, Tokyo, Japan

Abstract. Here we investigated a statistical feature of earthquake time distributions in the southern California earthquake catalog. As a main data analysis tool, we used a simple statistical approach based on the calculation of integral deviation times (IDT) from the time distribution of regular markers. The research objective is to define whether and when the process of earthquake time distribution approaches to randomness. Effectiveness of the IDT calculation method was tested on the set of simulated color noise data sets with the different extent of regularity, as well as for Poisson process data sets. Standard methods of complex data analysis have also been used, such as power spectrum regression, Lempel and Ziv complexity, and recurrence quantification analysis, as well as multiscale entropy calculations. After testing the IDT calculation method for simulated model data sets, we have analyzed the variation in the extent of regularity in the southern California earthquake catalog. Analysis was carried out for different periods and at different magnitude thresholds. It was found that the extent of the order in earthquake time distributions is fluctuating over the catalog. Particularly, we show that in most cases, the process of earthquake time distributions is less random in periods of strong earthquake occurrence compared to periods with relatively decreased local seismic activity. Also, we noticed that the strongest earthquakes occur in periods when IDT values increase.

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