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A Community Stress Drop Validation Study using the 2019 Ridgecrest Earthquake Dataset

Annemarie S. Baltay, Rachel E. Abercrombie, & Taka'aki Taira

Published April 19, 2021, SCEC Contribution #11825

We introduce a community stress drop validation study using the 2019 Ridgecrest earthquake sequence, in which we invite researchers to use a common dataset to estimate earthquake stress drop. Earthquake stress drop is a key parameter in many ground motion, rupture simulation, and source physics problems in earthquake science; in theory it relates the average slip on a fault to rupture area, and in practice it inherently indicates the high-frequency energetics of an earthquake. We seek to understand the physical controls and methodological reasons for similarity or differences in stress drop estimates, so that they can be used more reliably by the earthquake science community. We develop a common dataset consisting of 2 weeks of earthquakes following the 2019 Ridgecrest M6.4 earthquake, including nearly 13,000 earthquakes of M1 and greater, recorded on stations within 100 km; this dataset is available for all to use. We are soliciting stress drop estimates from community participants on any subset of these events, using a variety of methods. We are correlating and comparing these resulting stress drop calculations as they are made available in a meta-analysis, to understand why similarities or differences arise. We will first examine which earthquakes or methods generate grossly similar or different results. Initial results from a few preliminary datasets show only weak correlation between various methods, so we next consider the details of the methods, assumptions and data selection criteria. As a community study, all are invited to join!

Baltay, A. S., Abercrombie, R. E., & Taira, T. (2021, 04). A Community Stress Drop Validation Study using the 2019 Ridgecrest Earthquake Dataset. Poster Presentation at 2021 Virtual SSA Annual Meeting, April 19 - 23.