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

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 datasets: 558 M3.5+ earthquakes (California, Oregon, Washington;-2017 and the ShakeAlert test suite of historic and problematic signals (1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015). PLUM computes Modified Mercalli Intensity (IMMI) using velocity and acceleration data, leveraging co-located sensors to avoid problematic signals. An event detection is issued when the observed IMMI exceeds a given threshold(s). We find a two-station detection method using IMMI 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 dataset, reporting (not including telemetry or alert dissemination) detection times on par, and sometimes faster than current EEW methods (mean 8s; median 6s). As expected, detection times were slower for the older 1999-2015 earthquakes (N=21; mean 11s; median 6s) 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 IMMI 4+ shaking from local earthquakes and could complement and enhance EEW in the U.S.

“Saving Precious Seconds”—A Novel Approach to Implementing a Low-Cost Earthquake Early Warning System with Node-Level Detection and Alert Generation

“…Otherwise, the system will terminate the alert. As reconfirmed in a more recent EEW study in the US [82], this modified PLUM approach with a two-station trigger concept is expected to reduce the number of false alerts and increase the accuracy of the alert generation.…”

“…As shown in Figure 4, the prediction process for a given location (red star) takes place in a circle with a 30 km radius around an observation data point (blue dot). While the PLUM algorithm operates with a single operating point, this approach was subsequently criticised for the possibility of false or missed alerts and to terminate the propagation of the alert [82]. This is particularly relevant for the proposed type of EEW network, consisting of low-cost sensors installed in the homes of the general public, which are often in noisy environments compared to the high-end EEW networks consisting of sensors installed in much more noise-controlled environments.…”

“…This is particularly relevant for the proposed type of EEW network, consisting of low-cost sensors installed in the homes of the general public, which are often in noisy environments compared to the high-end EEW networks consisting of sensors installed in much more noise-controlled environments. Therefore, it is crucial to include extra observation points in the system to avoid false or missed alerts and terminate the propagation of a false alert [82]. Accordingly, to minimise the anticipated false alarms by having only a single observation station, we made a few modifications to Kodera's original PLUM algorithm.…”

“…For different earthquakes, the S-wave travel time will differ according to the sensor geolocations and the number of sensors used to trigger the alert (e.g., two sensors for our approach). As mentioned in the PLUM algorithm section, using the low-cost EEW sensor network proposed in this study, the use of two observation stations to trigger an alert is essential to reduce the number of false alerts [82]. Due to the two-station trigger concept, even though the first sensor in the network detects the earthquake in a fraction of time, it needs to wait for confirmation from the 2nd observation sensor.…”

Developments of the Nationwide Earthquake Early Warning System in Japan After the 2011 Mw9.0 Tohoku-Oki Earthquake

“…To mitigate earthquake damage, EEW systems have been developed and/or operated in many earthquake-prone regions around the world such as Japan (e.g., Nakamura, 1988;Hoshiba et al, 2008), Mexico (Espinosa-Aranda et al, 2009), the west coast of the United States (Böse et al, 2013;Kilb et al, 2021), Taiwan (Chen et al, 2015), Europe (Clinton et al, 2016), China (Zhang et al, 2016), Korea (Sheen et al, 2017), and Israel (Nof and Kurzon, 2021). In Japan, the Japan Meteorological Agency (JMA) has been operating the nationwide EEW system since 2007 to disseminate information on imminent strong ground motion to the general public and advanced technical users (Hoshiba et al, 2008).…”