Asymmetry in Earthquake Interevent Time Intervals

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. Plain Language Summary Earthquakes are often associated with non-equilibrium and nonlinear underlying processes which can lead to asymmetric behavior in metrics derived from earthquake records. By asymmetry we are referring to the tendency of more events to occur after a previous one than before the next one or vice versa. In earthquake sequences the main source of asymmetry is the occurrence of large numbers of aftershocks due to the earthquake triggering. We find here that the distributions of interevent time increments in real seismic catalogs are asymmetric and that the degree of asymmetry is characterized by a scaling function that exhibits a crossover, from a high asymmetry at short times to low asymmetry at long times. We suggest that different earthquake triggering processes are associated with these two distinct regimes of asymmetry. We apply the asymmetry analysis to an earthquake forecasting model-the Epidemic-Type Aftershock Sequence (ETAS) model and find that the new generalized ETAS model that includes both short- and long-term triggering mechanisms better reproduces the observed asymmetry than the standard ETAS model.

Automated summary

This study focuses on the asymmetry of interevent time series in earthquake catalogs, finding that there is a significant crossover from high to low asymmetry as lag index increases. Different earthquake triggering processes are associated with the two distinct regimes of asymmetry, and a new generalized ETAS model better reproduces the observed asymmetry compared to the standard ETAS model.