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Julian J Bunn

Publications and source records attributed to Julian J Bunn.

2 recordsLinked to original sources

Real-time earthquake detection and alerting behavior of PLUM ground-motion-based early warning in the United States

We examine the real‐time earthquake detection and alerting behavior of the Propagation of Local Undamped Motion (PLUM) earthquake early warning (EEW) algorithm and compare PLUM’s performance with the real‐time performance of the current source‐characterization‐based ShakeAlert System. In the United States (U.S.), PLUM uses a two‐station approach to detect earthquakes. Once a detection is confirmed, observed modified Mercalli intensity (MMI) distributions are forecast onto a regular grid, in which the preferred alert regions are grid cells with MMI 4.0+ forecasts. Although locations of dense station coverage allow PLUM to detect small ( M < 4.5) earthquakes typically not considered for EEW in the U.S., a PLUM detection on a small earthquake does not always generate an alert. This is because PLUM alerts are determined by current shaking distributions. If the MMI 4.0+ shaking subsides prior to detection confirmation by shaking at a second neighboring station, the prior MMI 4.0+ information will not be in the alert forecasts. Of the 432 M 3.0+ U.S. West Coast earthquakes in 2021, 33 produced ground motions large enough to be detected by PLUM. Twenty‐four generated MMI 4.0+ PLUM alerts, whereas ShakeAlert issued public EEW alerts for 13 of these earthquakes. We compare PLUM and ShakeAlert alert regions with ShakeMap and “Did You Feel It?” intensity distributions. Because PLUM alert regions surround stations observed to have strong ground motions (regardless of earthquake magnitude), PLUM alerts reliably include locations that experience significant shaking. This is not necessarily the case for ShakeAlert alert regions when there are large errors in magnitude or epicenter estimates. For two of the largest earthquakes in our real‐time dataset, the M 6.0 Antelope Valley and M 5.1 Petrolia earthquakes, the inclusion of PLUM would have improved real‐time ShakeAlert performance. Our results indicate that incorporation of PLUM into ShakeAlert will improve the robustness of the EEW system.

California, Oregon, Washington

The PLUM earthquake early warning algorithm: A retrospective case study of West Coast, USA, data

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.

British Columbia, California, Oregon, Washington