SCEC Award Number 23107 View PDF
Proposal Category Collaborative Proposal (Integration and Theory)
Proposal Title Year 3 of a Technical Activity Group for the Community Stress Drop Validation Study using the 2019 Ridgecrest Earthquake Dataset
Name Organization
Annemarie Baltay United States Geological Survey Rachel Abercrombie Boston University Shanna Chu United States Geological Survey Taka'aki Taira University of California, Berkeley Peter Shearer University of California, San Diego
Other Participants other TAG members
SCEC Priorities 1d, 2d, 4a SCEC Groups Seismology, FARM, GM
Report Due Date 03/15/2024 Date Report Submitted 04/17/2024
Project Abstract
We report on Year 3, 2023, of the Community Stress Drop Validation Technical Activity Group. The TAG sought to understand the physical controls and methodological reasons for similarity or differences in estimates of earthquake stress drops, so that they can be used reliably by the earthquake science community. Under the TAG, many researchers from the community independently calculated and submitted stress drop estimates using a consistent dataset of the 2019 Ridgecrest sequence of earthquakes. The TAG itself had three main tasks: (1) Coordination of the TAG, which includes workshop organization, hosting monthly Zoom meetups, distribution of datasets, and designing and coordinating benchmarks; (2) Analysis of Ridgecrest stress drops by individual PIs; and (3) Meta-analysis of the individual stress drops, to understand the sources of variability. Since the start of the TAG in 2021, co-PIs Abercrombie and Baltay have gathered the global community through a website, mailing list, monthly Zoom calls, conference sessions and meet-ups, and four successful workshops. In Year 1, 2021, TAG co-PI Taka’aki Taira generated, distributed, and trouble-shot a common waveform and metadata database of ~13,000 earthquakes recorded on ~100 stations, based on a two-week subset of M >1 and larger earthquakes which occurred in the Ridgecrest vicinity, and a subset of 55 events. To date, we have received results from 20 unique research groups for a total of 48 submissions, including 18 iterations with different choices and constraints on the depth, distance, velocity model and spectral type from one author.
Intellectual Merit SCEC seeks to understand both the characteristics and uncertainty of earthquake stress drop as it relates to basic source physics, rupture modeling and ground motion prediction, and has a focus on collaborative stress drop studies. This supports SCEC Priority 4.1.3: Collaborative Earthquake Stress Drop and Source Study and furthermore meets the call for training the next generation of users, as we have successfully included many early career researchers and specifically involved stress drop users, who are not analysts, in the workshop.
The motivation for the SCEC Community Stress Drop Validation TAG is focused on understanding the nature and causes of discrepancies in earthquake stress drop, as well as where random and physical variability arises. In this context, the main goals for the TAG are to use a common data set of records from the 2019 Ridgecrest earthquake sequence (consisting of over 12,000 events of M1 to M7.1) to address the questions:
● How do differing methods and model assumptions affect stress drop estimates?
● How do different researchers approach similar methods?
● How do data quantity, quality, selection and processing affect stress drop estimates?
● How do physical source (mechanism, depth, radiation pattern, directivity), path (geometrical spreading, attenuation), and site (soil conditions, site attenuation) features affect the estimates?
● What measurements, and uncertainties, would be most useful for the broader community?
Broader Impacts Through outreach and use of virtual platforms, we have been able to create a large, diverse, global community interested in resolving the issue of stress drop estimation. For example, we regularly hold our monthly Zoom calls twice in the same day, approximately 8 hours apart, to draw global participation (including researchers from the US, Europe, Japan, Israel, Saudi Arabia, Korea, Taiwan, Columbia, Australia, Hong Kong and Mexico). The monthly Zooms are also popular for students and early-career researchers as they can comfortably listen in and are given opportunities to introduce themselves, share their work, and meet the other participants. Six early-career researchers who have submitted results to the project are taking the lead convening a project-focused special session at the 2023 Seismological Society of America Annual Meeting. To date, of the 48 submitted results, one was directly led by an undergraduate and four by graduate students. We also received submission of four results from groups in Europe. Our most recent workshop in January 2024 held virtually and was attended by 105 individuals, 64 of whom joined both morning and afternoon sessions, with participants from 20 countries and hailing from North America, South America, Europe, Africa, Asia, Oceania and India. 70% were from the United States. Graduate student Neupane was directly funded by this SCEC Award to work on the TAG project and attend the 2022 AGU Fall Meeting in Chicago in person, where he participated in career development workshops and met with collaborators. At workshops, our keynote talks are by early-career researchers: Colin Pennington (postdoc) at Workshop #1, Hao Guo (postdoc) at Workshop #2, and Jamie Neely (postdoc) at Workshop #3 (there was no keynote speaker at Workshop #4!). We also strive to have a representative set of researchers from students to late career and with gender and geographic diversity for our workshop panelists. Our in-person Workshop #2 in Palm Springs drew attendees who had not attended the SCEC annual meeting ever (or in a long while), so the TAG is helping to broaden SCEC participation. Along with PIs Abercrombie and Baltay, the guest editors for the BSSA special issue (Adrien Oth and Takahiko Uchide) are outside of the US and not regular SCEC participants. We have had many inquiries from scientists who wish to be able to estimate stress drops themselves or be able to understand better under the hood what the methods do.
Exemplary Figure Figure 3. All submitted corner frequencies for the selected 55 events, from 48 submissions, with different submissions/authors shown in different symbol shapes/colors. Average corner frequency in black circles, and best fit constant stress drop line in dashed. (left) initial submissions. (Right) Submissions adjusted with a per-author/per-submission trend (function of magnitude and depth) removed.