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Stress drop estimation of aftershocks of the 2019 Ridgecrest earthquake using an EGF approach

Rachel E. Abercrombie, Christine J. Ruhl, & Peter M. Shearer

Submitted September 11, 2022, SCEC Contribution #12529, 2022 SCEC Annual Meeting Poster #062

The large uncertainties and scatter in stress drop estimates affect strong ground motion prediction and limit our understanding of the physics of earthquake rupture. Reasons for this including the simplifying assumptions concerning the source, path and site contributions, and the lack of sufficient frequency content in the data to resolve inherent tradeoffs. In connection with the ongoing SCEC Community Stress Drop Validation Study, we apply a stacked empirical Green’s function (EGF) approach to selected earthquakes from the Ridgecrest aftershock sequences; we investigate how the selection of EGF events, and other modeling choices affect the results.
We follow the approach developed by Abercrombie et al. (2017), Ruhl et al. (2017) and Abercrombie et al. (2020), with modifications following previous SCEC work by Shearer et al. (2019). This method uses EGF events to isolate the earthquake source, and then spectral fitting assuming a simple circular source model to estimate a corner frequency and resulting source dimension. These values are combined with independent measurements of the seismic moment to obtain an estimate of the stress drop. For the target events identified by the Community Experiment we select potential EGF events based on epicentral distance separation, and relative magnitude only. We calculate the spectral ratio and relative source time functions for each target event at each station for P and S waves independently, as available, using up to 100 EGF events. We then investigate how different analysis choices affect the results, including the selection of the EGFs based on their magnitude range, cross-correlation and depth similarity compared to their respective target event, and azimuthally weighting the stacking. We also use the source time functions to investigate source directivity and complexity, and the systematic bias these can produce when a simple source model is a relatively poor assumption for a particular earthquake. We compare our results with those from other studies, including the recent study of earthquake stress drop variation in Southern California (Shearer et al., 2022).

Key Words
stress drop, Ridgecrest, uncertainties

Abercrombie, R. E., Ruhl, C. J., & Shearer, P. M. (2022, 09). Stress drop estimation of aftershocks of the 2019 Ridgecrest earthquake using an EGF approach . Poster Presentation at 2022 SCEC Annual Meeting.

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