[1] During subduction, bending of downgoing oceanic lithosphere gives rise to normal faulting due to the extensional stress state generated in the upper plate. As deformation patterns inherently reflect a material's state of stress and rheology, extensive global observations of outer-rise faulting patterns and subduction dynamics provide a unique opportunity to examine the factors controlling outer-rise deformation. Despite a wide range of observed oceanic plate ages, convergence rates and slab pull magnitudes across modern subduction systems, however, measured outer-rise faulting patterns show effectively no correlation to variations in these parameters. This lack of correlation may reflect that outer-rise faulting patterns are strongly sensitive to all of these parameters, are dependent on additional parameters such as downgoingoverriding plate coupling or that existing faulting measurements require additional analysis. In order to provide a basis for future analysis of outer-rise faulting patterns, we build on previous thermo-mechanical numerical models of outer-rise deformation and explore the relationship between outer-rise faulting patterns, subduction dynamics and brittle rheology in an oceanic-continental subduction system. Analysis of timeaveraged outer-rise faulting patterns indicates that downgoing plate age and velocity, downgoing-overriding plate coupling and slab pull all significantly affect faulting patterns, while variations in brittle rheology have a significantly smaller impact. These relationships reflect that the sensitivity of outer-rise faulting patterns to the frictional properties of the oceanic crust and mantle is small compared to variations in the overall stress state and deformation rate of subduction systems. In order to gain additional insight into the origin outer-rise faulting patterns, future numerical studies should focus on specific regions in order to place constraints on the structure of the downgoing plate and dynamics of the subduction system.Components: 9,895 words, 9 figures, 2 tables.
We determine an optimal alerting configuration for the propagation of local undamped motion (PLUM) earthquake early warning (EEW) algorithm for use by the U.S. ShakeAlert system covering California, Oregon, and Washington. All EEW systems should balance the primary goal of providing timely alerts for impactful or potentially damaging shaking while limiting alerts for shaking that is too low to be of concern (precautionary alerts). The PLUM EEW algorithm forward predicts observed ground motions to nearby sites within a defined radius without accounting for attenuation, avoiding the earthquake source parameter estimation step of most EEW algorithms. PLUM was originally developed in Japan where the alert regions and ground motions for which alerts are issued differ from those implemented by ShakeAlert. We compare predicted ground motions from PLUM to ShakeMap-reported ground motions for a set of 22 U.S. West Coast earthquakes of magnitude 4.4–7.2 and evaluate available warning times. We examine a range of prediction radii (20–100 km), thresholds used to issue an alert (alert threshold), and levels of impactful or potentially damaging shaking (target threshold). We find optimal performance when the alert threshold is close to the target threshold, although higher target ground motions benefit from somewhat lower alert thresholds to ensure timely alerts. We also find that performance, measured as the cost reduction that a user can achieve, depends on the user’s tolerance for precautionary alerts. Users with a low target threshold and high tolerance for precautionary alerts achieve optimal performance when larger prediction radii (60–100 km) are used. In contrast, users with high target thresholds and low tolerance for precautionary alerts achieve better performance for smaller prediction radii (30–60 km). Therefore, setting the PLUM prediction radius to 60 km balances the needs of many users and provides warning times of up to ∼20 s.
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.
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