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Automated Detection and Characterization of Swarms and Mainshock-Aftershock in Southern Mexico

Description: 

The Mexican subduction zone is considered a natural laboratory for studying slip processes due to the relatively short trench-to-coast distance which brings broad portions of the seismogenic and transition zones inland. Fasola et al. (2019) found that SSEs also occur correlated with swarms on a crustal sliver fault that accommodates partitioning of oblique convergence into dip-slip and strike-slip. Hence, this region provides an opportunity to pursue detailed characterizations of potential relationships between seismicity and aseismic slip on a complex plate boundary system. Considering that previous detection of swarms was focused on 2012 and earlier, we use an automated detection algorithm to characterize sequences in the catalog from 2006 to 2022. The algorithm identifies clusters of events using the nearest neighbor distances in the space-time-energy domain (Zaliapin and Ben-Zion, 2013). The algorithm then characterizes sequences on a spectrum from swarms to traditional mainshock-aftershocks using quantitative forms of these characteristics: (1) the magnitude difference between the largest event and the next largest events, (2) the percentage of the sequence after the largest event, (3) the slope of seismicity rate over time, and (4) the magnitude range divided by the number of events in the sequence. The algorithm has been fine-tuned via comparison to manual inspection and discernment based on prior work (Ventura-Valentin and Brudzinski, 2021). Given the larger number of sequences detected and categorized via automated processing, we will describe the statistically significant spatial, temporal, and magnitude-frequency patterns associated with these swarms and aftershock sequences. For example, we find that the majority of newly detected swarms cluster along the trace of the sliver fault.

Session: Deciphering Earthquake Clustering for the Better Understanding of Crustal Deformation Mechanisms [Poster]

Type: Poster

Date: 4/20/2023

Presentation Time: 08:00 AM (local time)

Presenting Author: Wilnelly A. Ventura-Valentin

Student Presenter: Yes

Invited Presentation: 

Authors