SCEC Award Number 18086 View PDF
Proposal Category Collaborative Proposal (Integration and Theory)
Proposal Title Testing and Reconciling Stress Drop and Attenuation Models for Southern California
Investigator(s)
Name Organization
Rachel Abercrombie Boston University Peter Shearer University of California, San Diego
Other Participants partial support for grad student (TBN) at UCSD
SCEC Priorities 1d, 4a, 2e SCEC Groups Seismology, FARM, GM
Report Due Date 03/15/2020 Date Report Submitted 04/08/2019
Project Abstract
 The aim of our collaborative work is to improve the quality and reliability of stress drop estimates for southern California, and beyond. Our goal is to investigate the reliability of existing catalogs of stress drop, and regional attenuation models. We study two complementary approaches to investigate sources of consistency and discrepancies in stress drop estimates, and quantify uncertainties: (1) the spectral decomposition method, a large-scale approach involving stacking and averaging spectra to obtain parameters for large catalogs of events; and (2) the smaller-scale empirical Green's function (EGF), spectral-ratio method, designed to obtain optimal results for the best-recorded earthquakes, analyzed individually. We apply the two methods independently to clusters of earthquakes in Southern California. We find strong correlation between the results, but also significant differences. We compare the EGF spectral ratios with the corresponding ratios of event-terms from the spectral decomposition and find them to be very similar, implying that the discrepancies result from the different modeling approaches.
We then analyze the results in detail to investigate the most likely sources of discrepancy. We find that (a) spatially varying global EGFs are needed even within a cluster to remove systematic bias in the spectral decomposition approach, for example, an artificial dependence on depth, (b) the magnitude and frequency range of the regional network data are insufficient to resolve observed trade-offs between source model and stress drop scaling, and (c) the lack of constraints on the EGF corner frequency in the spectral-ratio method can cause systematic bias and increased uncertainties.
Intellectual Merit Earthquake stress drop is a fundamental source parameter, implicit in many of the science goals of SCEC 5. Stress drops are now commonly estimated from seismic data, but are hard to measure reliably and well. The large uncertainties and scatter in results affect strong ground motion prediction, and also limit our understanding of the physics of the earthquake rupture process, including distinguishing induced seismicity from natural seismicity. Our detailed investigation of two complementary methods has revealed:
-Empirical Green's Function (EGF) approaches to resolve earthquake corner frequency suffer from insufficiently acknowledged parameter tradeoffs
-The spectral ratio method for estimating corner frequency can produce biased results if the smaller event corner frequency is unconstrained
-Relative stress drop measurements in compact seismicity clusters are well resolved and reveal changes in average stress drop over short distances
-Assuming a single EGF for a wide depth range can map structural variation into source variation.
Broader Impacts The aim of our collaborative work is to improve the quality and reliability of earthquake stress drop estimates, which are fundamental to studies of earthquake physics, and also seismic hazard prediction. We have presented our results at SCEC and AGU, and also have a peer-reviewed publication in press with Journal of Geophysical Research – Solid Earth (SCEC Contribution #8916). The results of our comparison are already being implemented as improvements to a number of ongoing analyses, because both PIs are collaborating with multiple groups and analyzing earthquakes in many parts of the world. Our work therefore meets the both the specific and broader goals of SCEC, to use Southern California as a natural laboratory to improve our understanding of earthquake processes in Southern California and beyond.
Exemplary Figure Figure 2: Regional Network Data are inadequate to resolve deviation from earthquake self-similarity
Stacked event term spectra and fits to a global EGF function for the Landers seismicity cluster. (a) Event-term stacks from spectral decomposition. Terms are averaged within bins of 0.25 in relative log amplitude (proportional to log M0); n is the number of contributing earthquakes. The dashed lines indicate stacks with n<10, not included in the EGF fitting. (b) The best-fitting non-self-similar Brune model, the global EGF function in green, EGF stacks (solid) and model fit (dashed). (c) The best-fitting self-similar Brune model. (d) (e) & (f) alternative lower and higher stress drop models with statistically indistinguishable fits to the data.

Shearer, P. M., Abercrombie, R. E., Trugman, D. T., & Wang, W. (2019). Comparing EGF Methods for Estimating Corner Frequency and Stress Drop from P-wave Spectra. Journal of Geophysical Research, (accepted). SCEC Contribution 8916.