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Event Detection Performance of the PLUM Earthquake Early Warning Algorithm in Southern California

Cochran, Elizabeth S. and Bunn, Julian and Minson, Sarah E. and Baltay, Annemarie S. and Kilb, Deborah L. and Kodera, Yuki and Hoshiba, Mitsuyuki (2019) Event Detection Performance of the PLUM Earthquake Early Warning Algorithm in Southern California. Bulletin of the Seismological Society of America, 109 (4). pp. 1524-1541. ISSN 0037-1106. https://resolver.caltech.edu/CaltechAUTHORS:20190621-152419604

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Abstract

We test the Japanese ground‐motion‐based earthquake early warning (EEW) algorithm, propagation of local undamped motion (PLUM), in southern California with application to the U.S. ShakeAlert system. In late 2018, ShakeAlert began limited public alerting in Los Angeles to areas of expected modified Mercalli intensity (⁠I_(MMI⁠)) 4.0+ for magnitude 5.0+ earthquakes. Most EEW systems, including ShakeAlert, use source‐based methods: they estimate the location, magnitude, and origin time of an earthquake from P waves and use a ground‐motion prediction equation to identify regions of expected strong shaking. The PLUM algorithm uses observed ground motions directly to define alert areas and was developed to address deficiencies in the Japan Meteorological Agency source‐based EEW system during the 2011 Mw 9.0 Tohoku earthquake sequence. We assess PLUM using (a) a dataset of 193 magnitude 3.5+ earthquakes that occurred in southern California between 2012 and 2017 and (b) the ShakeAlert testing and certification suite of 49 earthquakes and other seismic signals. The latter suite includes events that challenge the current ShakeAlert algorithms. We provide a first‐order performance assessment using event‐based metrics similar to those used by ShakeAlert. We find that PLUM can be configured to successfully issue alerts using I_(MMI) trigger thresholds that are lower than those implemented in Japan. Using two stations, a trigger threshold of I_(MMI) 4.0 for the first station and a threshold of I_(MMI) 2.5 for the second station PLUM successfully detect 12 of 13 magnitude 5.0+ earthquakes and issue no false alerts. PLUM alert latencies were similar to and in some cases faster than source‐based algorithms, reducing area that receives no warning near the source that generally have the highest ground motions. PLUM is a simple, independent seismic method that may complement existing source‐based algorithms in EEW systems, including the ShakeAlert system, even when alerting to light (⁠I_(MMI) 4.0) or higher ground‐motion levels.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1785/0120180326DOIArticle
ORCID:
AuthorORCID
Cochran, Elizabeth S.0000-0003-2485-4484
Bunn, Julian0000-0002-3798-298X
Minson, Sarah E.0000-0001-5869-3477
Additional Information:© 2019 Seismological Society of America. Manuscript received 7 December 2018; Published Online 18 June 2019. Data and Resources: All catalogs and seismic time‐series data used in this study are archived and available at the Southern California Earthquake Data Center (last accessed November 2018). A full list of the ShakeAlert testing and certification (T&C) test suite events and their associated time series in miniSEED format is available at http://scedc.caltech.edu/research-tools/eewtesting.html (last accessed November 2018). The authors thank U.S. Geological Survey (USGS) internal reviewers Jeff McGuire and Colin O'Rourke, two anonymous reviewers, and Associate Editor Stefano Parolai, who provided constructive comments to improve this article.
Issue or Number:4
Record Number:CaltechAUTHORS:20190621-152419604
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20190621-152419604
Official Citation:Elizabeth S. Cochran, Julian Bunn, Sarah E. Minson, Annemarie S. Baltay, Deborah L. Kilb, Yuki Kodera, Mitsuyuki Hoshiba; Event Detection Performance of the PLUM Earthquake Early Warning Algorithm in Southern California. Bulletin of the Seismological Society of America ; 109 (4): 1524–1541. doi: https://doi.org/10.1785/0120180326
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:96639
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:22 Jun 2019 12:41
Last Modified:03 Mar 2020 13:01

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