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

Kilb, D. and Bunn, J. J. and Saunders, J. K. and Cochran, E. S. and Minson, S. E. and Baltay, A. and O’Rourke, C. T. and Hoshiba, M. and Kodera, Y. (2021) The PLUM Earthquake Early Warning Algorithm: A Retrospective Case Study of West Coast, USA, Data. Journal of Geophysical Research. Solid Earth, 126 (7). Art. No. e2020JB021053. ISSN 2169-9313. doi:10.1029/2020jb021053. https://resolver.caltech.edu/CaltechAUTHORS:20210623-171817924

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Abstract

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.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1029/2020jb021053DOIArticle
https://scedc.caltech.edu/research-tools/eewtesting.htmlRelated ItemSouthern California Earthquake Data Center
https://doi.org/10.7914/SN/AZDOIData
https://doi.org/10.7914/SN/BCDOIData
https://doi.org/10.7914/SN/CCDOIData
https://doi.org/10.7914/SN/CIDOIData
https://doi.org/10.7914/SN/CNDOIData
https://doi.org/10.7914/SN/IUDOIData
https://doi.org/10.7914/SN/NCDOIData
https://doi.org/10.7914/SN/NPDOIData
https://doi.org/10.7914/SN/UODOIData
https://doi.org/10.7914/SN/OODOIData
https://doi.org/10.7914/SN/USDOIData
https://doi.org/10.7914/SN/UWDOIData
https://dx.doi.org/10.7909/C3WD3xH1DOISouthern California Earthquake Data Center
http://ds.iris.edu/ds/nodes/dmc/data/Related ItemIncorporated Research Institutions for Seismology
http://service.scedc.caltech.edu/ftp/TestingEventArchiveRelated ItemTesting Event Archive
https://doi.org/10.9732/BDSNDOIData
ORCID:
AuthorORCID
Kilb, D.0000-0002-7252-4167
Bunn, J. J.0000-0002-3798-298X
Saunders, J. K.0000-0001-5340-6715
Cochran, E. S.0000-0003-2485-4484
Minson, S. E.0000-0001-5869-3477
Baltay, A.0000-0002-6514-852X
O’Rourke, C. T.0000-0001-5403-4685
Hoshiba, M.0000-0001-9701-5986
Kodera, Y.0000-0002-8071-2360
Additional Information:© 2021. American Geophysical Union. All Rights Reserved. This article has been contributed to by US Government employees and their work is in the public domain in the USA. Issue Online: 19 July 2021; Version of Record online: 19 July 2021; Accepted manuscript online: 11 June 2021; Manuscript accepted: 04 June 2021; Manuscript revised: 26 May 2021; Manuscript received: 30 October 2020. This work benefited from helpful discussions with those from the extended ShakeAlert team and ShakeAlert working groups. The authors thank Jessica Murray and Andy Barbour for detailed feedback on an initial draft of this manuscript. The authors also thank Editor Rachel Abercrombie and an anonymous associate editor and two anonymous reviewers for their thoughtful suggestions that greatly improved the manuscript. Additional feedback from Jeff McGuire, Shane Detweiler and Mike Diggles also improved the manuscript. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Data Availability Statement: The WC data set (magnitude, location, and depth) were obtained from the ComCat catalog (data last accessed July 2019). The miniSEED waveform data used in the WC data set were obtained from https://scedc.caltech.edu/research-tools/eewtesting.html, which included associated metadata (data last accessed November 2019). Data from the following networks were used in this study: Anza regional network (AZ; https://doi.org/10.7914/SN/AZ), Red Sísmica del Noroeste de México (BC; https://doi.org/10.7914/SN/BC), Berkeley Digital Seismograph Network (BK; https://doi.org/10.9732/BDSN), Cascade Chain Volcano Monitoring (CC; https://doi.org/10.7914/SN/CC), California Strong Motion Instrumentation Program (CE: no doi available), Southern California Seismic Network (CI; https://doi.org/10.7914/SN/CI), Canadian National Seismograph Network (CN; https://doi.org/10.7914/SN/CN), Global Seismograph Network – IRIS/USGS (IU; https://doi.org/10.7914/SN/IU), USGS Northern California Network (NC; https://doi.org/10.7914/SN/NC), United States National Strong-Motion Network (NP; https://doi.org/10.7914/SN/NP), NEPTUNE Canada (NV; no doi available), University of Oregon and Pacific Northwest Seismic Network (UO; https://doi.org/10.7914/SN/UO), Ocean Observatories Initiative (OO; https://doi.org/10.7914/SN/OO), United States National Seismic Network (US; https://doi.org/10.7914/SN/US), Pacific Northwest Seismic Network (UW; https://doi.org/10.7914/SN/UW). Data were also obtained from the Southern California Earthquake Center (https://doi.org/10.7909/C3WD3xH1) and IRIS (http://ds.iris.edu/ds/nodes/dmc/data/). Maps (Figures 1 and 7) were created with Matlab. Waveform gain and instrument response information used to produce Figure 2 were obtained via the IRIS-WS Library Java API (IRIS-WS v. 2.0.18), which allows direct access to data and information at the IRIS Data Management Center (DMC; data last accessed April 2020). The WCTC data, metadata, and waveform data (miniseed) were downloaded from the ShakeAlert Testing Event Archive ftp site housed at the Southern California Earthquake Data Center (http://service.scedc.caltech.edu/ftp/TestingEventArchive; last accessed October 2019). Data with incorrect gains (NC.CSL, NC.CVP; NC.PCH, NC.PCHB, NC.PCHC, NC.PHOB, and NC.PMM) that were identified in early 2020 were removed (Deborah Smith, written communication 2020). ShakeAlert station network information for January 2020 was obtained from Valerie Thomas (written communication, 2020).
Subject Keywords:California; Cascadia; earthquake early warning (EEW); earthquake preparedness; earthquake; Oregon; PLUM; San Andreas Fault; seismic network; ShakeAlert System; Washington
Issue or Number:7
DOI:10.1029/2020jb021053
Record Number:CaltechAUTHORS:20210623-171817924
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210623-171817924
Official Citation:Kilb, D., Bunn, J. J., Saunders, J. K., Cochran, E. S., Minson, S. E., Baltay, A., et al. (2021). The PLUM earthquake early warning algorithm: A retrospective case study of West Coast, USA, data. Journal of Geophysical Research: Solid Earth, 126, e2020JB021053. https://doi.org/10.1029/2020JB021053
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:109556
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:23 Jun 2021 18:03
Last Modified:26 Jul 2021 22:21

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