A Refined Earthquake Focal Mechanism Catalog for Southern California Derived with Deep Learning Algorithms

Yifang Cheng, Egill Hauksson, & Yehuda Ben-Zion

Under Review December 18, 2022, SCEC Contribution #12676

Earthquake focal mechanisms, determined with P-wave polarities and S/P amplitude ratios, are primary data for analyzing fault zone geometry, sense of slip, and the crustal stress field. Solving for the focal mechanisms of small earthquakes is often challenging because phase arrivals and first-motion polarities are hard to be separated from noise. To overcome this challenge, we implement CNN algorithms (Ross et al., 2018a, b) to detect additional phases and polarities. Using both existing and these new data we build a high-quality focal mechanism catalog of 297,478 events that occurred from 1981 to 2021 in southern California with the HASH method of Hardebeck and Shearer (2002, 2003). The new focal mechanism catalog is overall consistent with the standard catalog (Yang et al., 2012) but includes 40% more focal mechanisms, and is more consistent with moment tensor solutions derived using waveform-fitting methods. We apply the new catalog to identify changes in focal mechanism properties caused by the occurrence of large mainshocks such as 2010 Mw7.2 El Mayor and 2019 Mw7.1 RidgecestRidgecrest. Such changes may be associated with co-seismic stress drops, post-seismic deformations, and static stress changes on a regional scale. The new high-resolution catalog will contribute to improved understanding of the crustal stress field, earthquake triggering mechanisms, fault zone geometry, and sense of slip on faults in southern California.

Citation
Cheng, Y., Hauksson, E., & Ben-Zion, Y. (2022). A Refined Earthquake Focal Mechanism Catalog for Southern California Derived with Deep Learning Algorithms. J. Geophys. Res, (under review).