NH007-0003
Nowcasting earthquakes with Machine Learning:How Aftershocks and swarms may signal regional tectonic stress
Nowcasting earthquakes with Machine Learning:How Aftershocks and swarms may signal regional tectonic stress
Tuesday, 8 December 2020
Poster
Abstract:
Earthquake nowcasting is a method to evaluate the current state of seismic hazard from large earthquakes. In this paper, we connect the temporal occurrence of the largest and most potentially destructive earthquakes in California since 1984 with a readily observable property of small earthquake seismicity in the region. Our method involves the calculation of the time history of the average radius (horizontal size or extent) of "bursts" of small earthquakes, in the time leading up to and following major earthquakes in the region. We observe that the radius systematically and gradually decreases leading up to major earthquakes, increasing suddenly and discontinuously following the event. This observable pattern resembles the long-hypothesized cycle of regional tectonic stress buildup and release, or elastic rebound, associated with large destructive earthquakes. We propose that the radius of these bursts might be considered to be a proxy variable for the changing state of regional stress in Southern California. InSAR and GNSS observations could be used to examine candidate sites revealed by our seismic analysis.

