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Rapid Earthquake Discrimination for Earthquake Early Warning: A Bayesian Probabilistic Approach Using Three-Component Single‐Station Waveforms and Seismicity Forecast

Yin, Lucy and Andrews, Jennifer and Heaton, Thomas (2018) Rapid Earthquake Discrimination for Earthquake Early Warning: A Bayesian Probabilistic Approach Using Three-Component Single‐Station Waveforms and Seismicity Forecast. Bulletin of the Seismological Society of America, 108 (4). pp. 2054-2067. ISSN 0037-1106. https://resolver.caltech.edu/CaltechAUTHORS:20180815-160549100

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Abstract

The utility of Earthquake Early Warning (EEW) relies on the robust and rapid classification of near‐site earthquake source signals from noise and teleseismic arrivals. To achieve this goal, we propose using the three‐component acceleration and velocity waveform data and epidemic‐type aftershock sequence (ETAS) seismicity forecast information in parallel, which will produce a posterior prediction by combining the predictions from the heterogeneous sources using a Bayesian probabilistic approach. We collected 2481 three‐component strong‐motion records for training and testing. The rapid prediction is available as quickly as 0.5 s after the trigger at a single station and updates every 0.5 s up to 3.0 s, achieving a precision rate of 94.7% at the first prediction with the classification accuracy increasing with time. The leave‐one‐out cross‐validation method also demonstrates confidence of robust performance for future earthquake signal detections. We compared the method with the τ_c−P_d EEW classification criterion and find that our prediction is 83% faster. Because the method evaluates two independent sources of information simultaneously under an ensemble model, the new strategy has shown fast predictions with promising results and the implementation of this methodology could provide significantly faster and more reliable EEW warnings to regions near the earthquake’s epicenter, where the strongest shaking is observed.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1785/0120170138DOIArticle
ORCID:
AuthorORCID
Andrews, Jennifer0000-0002-5679-5565
Heaton, Thomas0000-0003-3363-2197
Additional Information:© 2018 Seismological Society of America. Manuscript received 3 May 2017; Published Online 12 June 2018. Data and Resources: The strong‐motion records used in this study are downloaded from the Southern California Earthquake Data Center (http://scedc.caltech.edu, last accessed June 2016). The catalog database is downloaded from Advanced National Seismic System (ANSS) Composite Catalog (http://www.ncedc.org/anss/, last accessed June 2016). This research was supported by the Gordon and Betty Moore Foundation Grant Numbers 3023 and 5229, and U.S. Geological Survey/National Earthquake Hazards Reduction Program (USGS/NEHRP) Cooperative Agreement G16AC00355. This research was also supported by the Natural Sciences and Engineering Research Council of Canada’s (NSERC) Postgraduate Scholarships‐Doctoral Program.
Group:Seismological Laboratory
Funders:
Funding AgencyGrant Number
Gordon and Betty Moore Foundation3023
Gordon and Betty Moore Foundation5229
USGSG16AC00355
Natural Sciences and Engineering Research Council of Canada (NSERC)UNSPECIFIED
Issue or Number:4
Record Number:CaltechAUTHORS:20180815-160549100
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20180815-160549100
Official Citation:Lucy Yin, Jennifer Andrews, Thomas Heaton; Rapid Earthquake Discrimination for Earthquake Early Warning: A Bayesian Probabilistic Approach Using Three‐Component Single‐Station Waveforms and Seismicity Forecast. Bulletin of the Seismological Society of America ; 108 (4): 2054–2067. doi: https://doi.org/10.1785/0120170138
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:88836
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:16 Aug 2018 00:14
Last Modified:03 Oct 2019 20:10

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