A new method to identify earthquake swarms applied to seismicity near the San Jacinto Fault, California

Abstract

Understanding earthquake clustering in space and time is important but also challenging because of complexities in earthquake patterns and the large and diverse nature of earthquake catalogues. Swarms are of particular interest because they likely result from physical changes in the crust, such as slow slip or fluid flow. Both swarms and clusters resulting from aftershock sequences can span a wide range of spatial and temporal scales. Here we test and implement a new method to identify seismicity clusters of varying sizes and discriminate them from randomly occurring background seismicity. Our method searches for the closest neighbouring earthquakes in space and time and compares the number of neighbours to the background events in larger space/time windows. Applying our method to California's San Jacinto Fault Zone (SJFZ), we find a total of 89 swarm-like groups. These groups range in size from 0.14 to 7.23 km and last from 15 min to 22 d. The most striking spatial pattern is the larger fraction of swarms at the northern and southern ends of the SJFZ than its central segment, which may be related to more normal-faulting events at the two ends. In order to explore possible driving mechanisms, we study the spatial migration of events in swarms containing at least 20 events by fitting with both linear and diffusion migration models. Our results suggest that SJFZ swarms are better explained by fluid flow because their estimated linear migration velocities are far smaller than those of typical creep events while large values of best-fitting hydraulic diffusivity are found.