TL;DR: The Virtual Seismologist (VS) method is a Bayesian approach to early warning that provides a unified framework for the real-time earthquake source estimation, as well as the subscriber’s decision-making problem.
Abstract: The goal of earthquake early warning is to provide timely information to guide damage-mitigating actions that can be taken in the few seconds between the detection of an earthquake and the onset of large ground motions at a given site From a subscriber’s perspective, effective early warning consists of both real-time information about the expected ground motions, as well as a methodology of how to use this information, and the inherent uncertainties, to guide decision-making The Virtual Seismologist (VS) method is a Bayesian approach to early warning that provides a unified framework for the real-time earthquake source estimation, as well as the subscriber’s decision-making problem The introduction of prior information into the source estimation problem via Bayes’ Theorem distinguishes the VS method from other paradigms for earthquake early warning Station locations, previously observed seismicity, and known fault traces are among the type of information that can be used to resolve trade-offs in magnitude and location that are unresolved by the ground motion observations alone at the initial stages of earthquake rupture The benefits of prior information are most evident in regions of low station density, where large inter-station distances result in source estimates based on a relatively sparse set of observations The drawback of prior information is the increased complexity of information that must be communicated to the user, as the resultant earthquake source estimates can no longer be adequately described by Gaussian distributions We illustrate the performance of the VS method in regions of high and low stations density, and discuss how subscriber requirements ultimately dictate how the real-time source estimation problem must be addressed
TL;DR: ShakeAlert 2.0 was tested using historic waveform data consisting of 60 M 3.5+ and 25 M 5.0+ earthquakes, in addition to other anomalous waveforms such as calibration signals to assess how the system behaves in regions that are well‐instrumented, sparsely instrumented, and for offshore earthquakes.
Abstract: The ShakeAlert earthquake early warning system is designed to automatically identify and characterize the initiation and rupture evolution of large earthquakes, estimate the intensity of ground shaking that will result, and deliver alerts to people and systems that may experience shaking, prior to the occurrence of shaking at their location. It is configured to issue alerts to locations within the West Coast of the United States. In 2018, ShakeAlert 2.0 went live in a regional public test in the first phase of a general public rollout. The ShakeAlert system is now providing alerts to more than 60 institutional partners in the three states of the western United States where most of the nation’s earthquake risk is concentrated: California, Oregon, and Washington. The ShakeAlert 2.0 product for public alerting is a message containing a polygon enclosing a region predicted to experience modified Mercalli intensity (MMI) threshold levels that depend on the delivery method. Wireless Emergency Alerts are delivered for M 5+ earthquakes with expected shaking of MMI≥IV. For cell phone apps, the thresholds are M 4.5+ and MMI≥III. A polygon format alert is the easiest description for selective rebroadcasting mechanisms (e.g., cell towers) and is a requirement for some mass notification systems such as the Federal Emergency Management Agency’s Integrated Public Alert and Warning System. ShakeAlert 2.0 was tested using historic waveform data consisting of 60 M 3.5+ and 25 M 5.0+ earthquakes, in addition to other anomalous waveforms such as calibration signals. For the historic event test, the average M 5+ false alert and missed event rates for ShakeAlert 2.0 are 8% and 16%. The M 3.5+ false alert and missed event rates are 10% and 36.7%. Real‐time performance metrics are also presented to assess how the system behaves in regions that are well‐instrumented, sparsely instrumented, and for offshore earthquakes.
TL;DR: In this article, the authors demonstrate the performance of the Geodetic First Approximation of Size and Time (G•FAST) geodetic early warning system, using simulated displacements for the 2001 M w  6.8 Nisqually earthquake.
Abstract: A prototype earthquake early warning (EEW) system is currently in development in the Pacific Northwest. We have taken a two‐stage approach to EEW: (1) detection and initial characterization using strong‐motion data with the Earthquake Alarm Systems (ElarmS) seismic early warning package and (2) the triggering of geodetic modeling modules using Global Navigation Satellite Systems data that help provide robust estimates of large‐magnitude earthquakes. In this article we demonstrate the performance of the latter, the Geodetic First Approximation of Size and Time (G‐FAST) geodetic early warning system, using simulated displacements for the 2001 M w 6.8 Nisqually earthquake. We test the timing and performance of the two G‐FAST source characterization modules, peak ground displacement scaling, and Centroid Moment Tensor‐driven finite‐fault‐slip modeling under ideal, latent, noisy, and incomplete data conditions. We show good agreement between source parameters computed by G‐FAST with previously published and postprocessed seismic and geodetic results for all test cases and modeling modules, and we discuss the challenges with integration into the U.S. Geological Survey’s ShakeAlert EEW system.
TL;DR: The ShakeAlert earthquake early warning system was developed by the United States Geological Survey (USGS) for the West Coast of United States as discussed by the authors, which leverages existing stations and infrastructure of the Advanced National Seismic System (ANSS) regional networks to achieve this new capability.
Abstract: COVER IMAGE: Map generated from the ShakeAlert earthquake early warning system showing the initial 10 seconds of an M7.8 scenario earthquake on the southern San Andreas Fault. Expected warning times for the scenario earthquake are shown by red dashed lines with warning time labeled. Faults (solid dark-gray lines), length of the scenario rupture (dotted black line), and major cities (black dot with city name labeled) are shown. Purple, red, and yellow colors show instantaneous surface velocity of the earthquake, and this data is modified from the TeraShake simulation (www.scec.org/terashake). For more information on the USGS—the Federal source for science about the Earth, its natural and living resources, natural hazards, and the environment—visit http://www.usgs.gov or call 1–888–ASK–USGS For an overview of USGS information products, including maps, imagery, and publications, visit To order this and other USGS information products, visit http://store.usgs.gov Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Although this report is in the public domain, permission must be secured from the individual copyright owners to reproduce any copyrighted material contained within this report. Executive Summary Earthquake Early Warning (EEW) systems can provide as much as tens of seconds of warning to people and automated systems before strong shaking arrives. The United States Geological Survey (USGS) and its partners are developing such an EEW system, called ShakeAlert, for the West Coast of the United States. This document describes the technical implementation of that system, which leverages existing stations and infrastructure of the Advanced National Seismic System (ANSS) regional networks to achieve this new capability. While significant progress has been made in developing the ShakeAlert early warning system, improved robustness of each component of the system and additional testing and certification are needed for the system to be reliable enough to issue public alerts. Major components of the system include dense networks of ground motion sensors, telecommunications from those sensors to central processing systems, algorithms for event detection and alert creation, and distribution systems to alert users. Capital investment costs for a West Coast EEW system are projected to be $38.3M, with additional annual maintenance and operations totaling $16.1M—in addition to current ANSS expenditures for earthquake monitoring. An EEW system is complementary to, but does not replace, other strategies to mitigate earthquake losses. The system has limitations: false and missed alerts are possible, and the area very near …