Abstract
Here we focus on a basic statistical measure of earthquake catalogs that has not been studied before, the asymmetry of interevent time series (e.g., reflecting the tendency to have more aftershocks than spontaneous earthquakes). We define the asymmetry metric as the ratio between the number of positive interevent time increments minus negative increments and the total (positive plus negative) number of increments. Such asymmetry commonly exists in time series data for nonlinear geophysical systems like river flow which decays slowly and increases rapidly. We find that earthquake interevent time series are significantly asymmetric, where the asymmetry function exhibits a significant crossover to weak asymmetry at large lag index. We suggest that the Omori law can be associated with the large asymmetry at short time intervals below the crossover whereas overlapping aftershock sequences and the spontaneous events can be associated with a fast decay of asymmetry above the crossover. We show that the asymmetry is better reproduced by a recently modified Epidemic-Type Aftershock Sequence (ETAS) model with two triggering processes in comparison to the standard ETAS model which only has one.
Original language | English |
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Article number | e2021JB022454 |
Journal | Journal of Geophysical Research: Solid Earth |
Volume | 126 |
Issue number | 9 |
DOIs | |
State | Published - Sep 2021 |
Bibliographical note
Publisher Copyright:© 2021. American Geophysical Union. All Rights Reserved.
Funding
The authors thank for the financial support by the EU H2020 project RISE, the Israel Science Foundation (Grants No. 189/19), DTRA, the Pazy Foundation, the Joint China‐Israel Science Foundation (Grants No. 3132/19), and the BIU Center for Research in Applied Cryptography and Cyber Security. The authors thank the Israel ministry of energy and the Yunnan Province Computational Physics and Applied Science and Technology Innovation Team. The authors thank for the financial support by the EU H2020 project RISE, the Israel Science Foundation (Grants No. 189/19), DTRA, the Pazy Foundation, the Joint China-Israel Science Foundation (Grants No. 3132/19), and the BIU Center for Research in Applied Cryptography and Cyber Security. The authors thank the Israel ministry of energy and the Yunnan Province Computational Physics and Applied Science and Technology Innovation Team.
Funders | Funder number |
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EU H2020 | |
Israel ministry of energy and the Yunnan Province Computational Physics | |
Joint China-Israel Science Foundation | |
Joint China‐Israel Science Foundation | 3132/19 |
Defense Threat Reduction Agency | |
Horizon 2020 Framework Programme | 821115 |
Israel Science Foundation | 189/19 |
PAZY Foundation |