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Room: Exhibit Hall

Date: 5/3/2024

Session Time: 8:00 AM to 5:45 PM (local time)

Earthquakes source parameters such as stress drop, magnitude and moment tensors are fundamental terms used to describe earthquakes. They are also key ingredients in earthquake ground motion modeling, rupture simulation, source physics analysis and statistical seismology. For this reason, the estimation of these parameters is often the first step in any analysis of earthquakes, but due to variability in site characterization, network capability and resources different procedures and methods are often used in their estimation. These issues and uncertainties depend on length scale, and therefore vary across magnitudes. For example, high frequency (>10 Hz) shallow site effects will strongly affect smaller earthquakes (M<3), while larger events are more strongly affected by issues at lower frequencies. This variability in method and inconsistencies across magnitude scales can yield artifacts which mask physical trends, leading to contrasting interpretations of earthquake scaling relationships, and earthquake dynamic rupture processes. For example, catalog magnitude estimation varies regionally, and by event size and network capability, producing artifacts that can influence important statistics like magnitude exceedance probabilities. Source parameters quantifying stress and energy release are fundamental to understanding fault strength and dynamic rupture propagation but can vary by orders of magnitude among studies. Estimating these parameters accurately, or at least uniformly, is needed to understand earthquake mechanics and ground motion hazard. 
 
We seek all interested researchers to compare and validate source parameter estimates for any magnitude. We encourage studies that aim to quantify the uncertainties of these measurements, comparative studies of multiple methods and those that focus on reliable interpretation of results. 

Conveners:
Rachel E. Abercrombie, Boston University (rea@bu.edu)
Shanna Chu, U.S. Geological Survey (schu@usgs.gov)
Sydney Gable, University of Michigan (gablesyd@umich.edu)
Gene Ichinose, Lawrence Livermore National Laboratory (ichinose1@llnl.gov)
Colin N. Pennington, Lawrence Livermore National Laboratory (pennington6@llnl.gov)

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