[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.

ABSTRACT We evaluate the timeliness and accuracy of ground-motion-based earthquake early warning (EEW) during the July 2019 M 6.4 and 7.1 Ridgecrest earthquakes. In 2018, we began retrospective and internal real-time testing of the propagation of local undamped motion (PLUM) method for earthquake warning in California, Oregon, and Washington, with the potential that PLUM might one day be included in the ShakeAlert EEW system. A real-time version of PLUM was running on one of the ShakeAlert EEW system’s development servers at the time of the 2019 Ridgecrest sequence, allowing us to evaluate the timeliness and accuracy of PLUM’s warnings for the M 6.4 and 7.1 mainshocks in real time with the actual data availability and latencies of the operational ShakeAlert EEW system. The latter is especially important because high-data latencies during the M 7.1 earthquake degraded ShakeAlert’s performance. PLUM proved to be largely immune to these latencies. In this article, we present a retrospective analysis of PLUM performance and explore three potential regional alerting strategies ranging from spatially large regions (counties), to moderate-size regions (National Weather Service public forecast zones), to high-spatial specificity (50 km regular geographic grid). PLUM generated initial shaking forecasts for the two mainshocks 5 and 6 s after their respective origin times, and faster than the ShakeAlert system’s first alerts. PLUM was also able to accurately forecast shaking across southern California for all three alerting strategies studied. As would be expected, a cost-benefit analysis of each approach illustrates trade-offs between increasing warning time and minimizing the area receiving unneeded alerts. Choosing an optimal alerting strategy requires knowledge of users’ false alarm tolerance and minimum required warning time for taking protective action, as well as the time required to distribute alerts to users.

No abstract

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.

ABSTRACT The ShakeAlert earthquake early warning system aims to alert people who experience modified Mercalli intensity (MMI) IV+ shaking during an earthquake using source estimates (magnitude and location) to estimate median-expected peak ground motions with distance, then using these ground motions to determine median-expected MMI and thus the extent of MMI IV shaking. Because median ground motions are used, even if magnitude and location are correct, there will be people outside the alert region who experience MMI IV shaking but do not receive an alert (missed alerts). We use 91,000 “Did You Feel It?” survey responses to the July 2019 Mw 6.4 and Mw 7.1 Ridgecrest, California, earthquakes to determine which ground-motion to intensity conversion equation (GMICE) best fits median MMI with distance. We then explore how incorporating uncertainty from the ground-motion prediction equation and the GMICE in the alert distance calculation can produce more accurate MMI IV alert regions for a desired alerting strategy (e.g., aiming to alert 95% of people who experience MMI IV+ shaking), assuming accurate source characterization. Without incorporating ground-motion uncertainties, we find MMI IV alert regions using median-expected ground motions alert fewer than 20% of the population that experiences MMI IV+ shaking. In contrast, we find >94% of the people who experience MMI IV+ shaking can be included in the MMI IV alert region when two standard deviations of ground-motion uncertainty are included in the alert distance computation. The optimal alerting strategy depends on the false alert tolerance of the community due to the trade-off between minimizing missed and false alerts. This is especially the case for situations like the Mw 6.4 earthquake when alerting 95% of the 5 million people who experience MMI IV+ also results in alerting 14 million people who experience shaking below this level and do not need to take protective action.

Alerting the public of potential dangers during rapid-onset natural hazard events always carries some uncertainty due to the limited real-time information available to develop accurate warnings as well as the natural randomness of the system. For extreme weather phenomena such as tornadoes during supercell thunderstorms, flash floods during atmospheric river events, and lahars during volcanic eruptions, warning centers do not know exactly where these events will occur nor the exact path they will take when they do. As such, public alerts for these phenomena are issued to wider areas than may ultimately be impacted to account for these uncertainties (e.g.,

As the seismological community embraces fiber optic distributed acoustic sensing (DAS), DAS arrays are becoming a logical, scalable option to obtain strain and ground-motion data for which the installation of seismometers is not easy or cheap, such as in dense offshore arrays. The potential of strain data in earthquake early warning (EEW) applications has been recently demonstrated using records from borehole strainmeters (BSMs). However, current BSM networks are sparse, installing more BSMs is expensive and often impractical, and BSMs have the same limitations in offshore environments as other traditional seismic instruments. Here, we aim to provide a road map about how DAS data could be used in existing EEW applications, using the ShakeAlert EEW System for the West Coast of the United States as an example. We review the data requirements for EEW systems, examine ways in which strain-derived ground-motion data can be incorporated into such systems without significant modifications, and determine what is still needed for full utilization of DAS data in these applications. Importantly, EEW algorithms require ground-motion amplitude information for rapid earthquake source characterization; thus, accurate strain amplitude observations, not only phase information, are necessary for deriving these ground-motion metrics from DAS data. To obtain high-quality ground-motion observations, EEW-compatible DAS arrays need to be multicomponent, well coupled, and low noise. We suggest ways to achieve such data requirements using existing DAS technology and discuss areas in which further research is needed to optimize DAS array performance for EEW.