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Evaluating the Impact of Location Errors on Magnitude Estimates Through Epic

Description: 

Earthquake early warning (EEW) programs like ShakeAlert, can send timely alerts to regions prior to damaging shaking. These alerts allow people to take protective action such as to drop, cover, and hold on, and mitigate their seismic risk. EPIC, a network-based point source algorithm used in ShakeAlert, determines the location and magnitude of earthquakes using data from the first few seconds after P-wave arrival at local to regional stations. While EPIC has reliably provided estimates of locations and magnitudes for many recent earthquakes, some poorly constrained events exist particularly at the edges of the ShakeAlert reporting region. Because EPIC relies on station-epicenter scaling laws to aid in calculating the magnitude, poorly located earthquakes can also lead to an increased error in magnitude estimates. In this presentation, we identify the degree that recent high location error events have affected the resultant event magnitude and what effect these events have on EPIC’s overall magnitude uncertainty. Using a retrospective catalog of recent events, we also show how recently developed algorithms that improve EPIC’s location estimates for edge of network events have improved related magnitude errors. Improvements in both location and magnitude estimates limit the likelihood of a missed event, or conversely an overestimate leading to an erroneous error.

Session: Earthquake Early Warning Optimization and Efficacy [Poster]

Type: Poster

Date: 4/20/2023

Presentation Time: 08:00 AM (local time)

Presenting Author: Amy L. Williamson

Student Presenter: No

Invited Presentation: 

Authors