The PLUM Earthquake Early Warning Algorithm: A Retrospective Case Study of West Coast, USA, Data

Autor: Julian Bunn, Yuki Kodera, Mitsuyuki Hoshiba, Sarah E. Minson, Elizabeth S. Cochran, C. T. O'Rourke, Debi Kilb, J. K. Saunders, Annemarie S. Baltay
Rok vydání: 2021
Předmět:
Zdroj: Journal of Geophysical Research: Solid Earth. 126
ISSN: 2169-9356
2169-9313
DOI: 10.1029/2020jb021053
Popis: The PLUM (Propagation of Local Undamped Motion) earthquake early warning (EEW) algorithm differs from typical source-based EEW algorithms as it predicts shaking directly from observed shaking without first deriving earthquake source information (e.g., magnitude and epicenter). Here, we determine optimal PLUM event detection thresholds for U.S. West Coast earthquakes using two data sets: 558 M3.5+ earthquakes (California, Oregon, Washington; 2012–2017) and the ShakeAlert test suite of historic and problematic signals (1999–2015). PLUM computes Modified Mercalli Intensity (I_(MMI)) using velocity and acceleration data, leveraging co-located sensors to avoid problematic signals. An event detection is issued when the observed I_(MMI) exceeds a given threshold(s). We find a two-station detection method using I_(MMI) trigger thresholds of 4.0 and 3.0 for the first and second stations, respectively, is optimal for detecting M4.5+ earthquakes. PLUM detected 79 events in the 2012–2017 data set, reporting (not including telemetry or alert dissemination) detection times on par, and sometimes faster than current EEW methods (mean 8 s; median 6 s). As expected, detection times were slower for the older 1999–2015 earthquakes (N = 21; mean 11 s; median 6 s) when station coverage was sparser. Of the 31 PLUM detected M5+ events (10 2012–2017; 21 1999–2015), theoretically 20 (∼65%) could provide timely warnings. PLUM issued no false detections and avoided issuing detections for all calibration/anomalous signals, regional and teleseismic events. We conclude PLUM can successfully identify I_(MMI) 4+ shaking from local earthquakes and could complement and enhance EEW in the U.S.
Databáze: OpenAIRE
Externí odkaz: