Alert Optimization of the PLUM Earthquake Early Warning Algorithm for the Western United States

2022 ◽  
Author(s):  
Elizabeth S. Cochran ◽  
Jessie K. Saunders ◽  
Sarah E. Minson ◽  
Julian Bunn ◽  
Annemarie Baltay ◽  
...  
Keyword(s):  
Early Warning ◽  
Cost Reduction ◽  
Ground Motions ◽  
Optimal Performance ◽  
Earthquake Early Warning ◽  
Western United States ◽  
High Tolerance ◽  
Alert Threshold ◽  
The Cost ◽  
The U.S

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.

Optimizing Earthquake Early Warning Alert Distance Strategies Using the July 2019 Mw 6.4 and Mw 7.1 Ridgecrest, California, Earthquakes

2020 ◽  
Vol 110 (4) ◽  
pp. 1872-1886 ◽  
Author(s):  
Jessie K. Saunders ◽  
Brad T. Aagaard ◽  
Annemarie S. Baltay ◽  
Sarah E. Minson
Keyword(s):  
Ground Motion ◽  
Early Warning ◽  
Ground Motions ◽  
Protective Action ◽  
Warning System ◽  
Prediction Equation ◽  
Earthquake Early Warning ◽  
Source Characterization ◽  
Earthquake Early Warning System ◽  
Alert Distance

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.

scholarly journals Development of a Geodetic Component for the U.S. West Coast Earthquake Early Warning System

2018 ◽  
Vol 89 (6) ◽  
pp. 2322-2336 ◽  
Author(s):  
J. R. Murray ◽  
B. W. Crowell ◽  
R. Grapenthin ◽  
K. Hodgkinson ◽  
J. O. Langbein ◽  
...  
Keyword(s):  
Early Warning ◽  
West Coast ◽  
Early Warning System ◽  
Warning System ◽  
Earthquake Early Warning ◽  
Earthquake Early Warning System ◽  
The U.S

Event Detection Performance of the PLUM Earthquake Early Warning Algorithm in Southern California

2019 ◽  
Vol 109 (4) ◽  
pp. 1524-1541 ◽  
Author(s):  
Elizabeth S. Cochran ◽  
Julian Bunn ◽  
Sarah E. Minson ◽  
Annemarie S. Baltay ◽  
Deborah L. Kilb ◽  
...  
Keyword(s):  
Los Angeles ◽  
Ground Motion ◽  
Early Warning ◽  
Southern California ◽  
Ground Motions ◽  
Tohoku Earthquake ◽  
Prediction Equation ◽  
Earthquake Early Warning ◽  
Japan Meteorological Agency ◽  
Origin Time

Abstract We test the Japanese ground‐motion‐based earthquake early warning (EEW) algorithm, propagation of local undamped motion (PLUM), in southern California with application to the U.S. ShakeAlert system. In late 2018, ShakeAlert began limited public alerting in Los Angeles to areas of expected modified Mercalli intensity (IMMI) 4.0+ for magnitude 5.0+ earthquakes. Most EEW systems, including ShakeAlert, use source‐based methods: they estimate the location, magnitude, and origin time of an earthquake from P waves and use a ground‐motion prediction equation to identify regions of expected strong shaking. The PLUM algorithm uses observed ground motions directly to define alert areas and was developed to address deficiencies in the Japan Meteorological Agency source‐based EEW system during the 2011 Mw 9.0 Tohoku earthquake sequence. We assess PLUM using (a) a dataset of 193 magnitude 3.5+ earthquakes that occurred in southern California between 2012 and 2017 and (b) the ShakeAlert testing and certification suite of 49 earthquakes and other seismic signals. The latter suite includes events that challenge the current ShakeAlert algorithms. We provide a first‐order performance assessment using event‐based metrics similar to those used by ShakeAlert. We find that PLUM can be configured to successfully issue alerts using IMMI trigger thresholds that are lower than those implemented in Japan. Using two stations, a trigger threshold of IMMI 4.0 for the first station and a threshold of IMMI 2.5 for the second station PLUM successfully detect 12 of 13 magnitude 5.0+ earthquakes and issue no false alerts. PLUM alert latencies were similar to and in some cases faster than source‐based algorithms, reducing area that receives no warning near the source that generally have the highest ground motions. PLUM is a simple, independent seismic method that may complement existing source‐based algorithms in EEW systems, including the ShakeAlert system, even when alerting to light (IMMI 4.0) or higher ground‐motion levels.

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

2021 ◽  
Vol 9 ◽  
Author(s):  
Yuki Kodera ◽  
Naoki Hayashimoto ◽  
Koji Tamaribuchi ◽  
Keishi Noguchi ◽  
Ken Moriwaki ◽  
...  
Keyword(s):  
Point Source ◽  
Ground Motion ◽  
Early Warning ◽  
Prediction Accuracy ◽  
Ground Motions ◽  
Earthquake Early Warning ◽  
Japan Meteorological Agency ◽  
Motion Prediction ◽  
Ground Motion Prediction ◽  
Strong Ground

In Japan, the nationwide earthquake early warning (EEW) system has been being operated by the Japan Meteorological Agency (JMA) since 2007, disseminating information on imminent strong ground motion to the general public and advanced technical users. In the beginning of the operation, the system ran based mainly on standard source-based algorithms with a point-source location estimate and ground motion prediction equation. The point-source algorithms successfully provided ground motion predictions with high accuracy during the initial operation; however, the 2011 Mw9.0 Tohoku-Oki earthquake and the subsequent intense aftershock and triggered earthquake activities underscored the weaknesses of the source-based approach. In this paper, we summarize major system developments after the Tohoku-Oki event to overcome the limits of the standard point-source algorithms and to enhance the EEW performance further. In addition, we evaluate how the system performance was influenced by the updates. One of significant improvements in the JMA EEW system was the implementation of two new ground motion prediction methods: the integrated particle filter (IPF) and propagation of local undamped motion (PLUM) algorithms. IPF is a robust point-source algorithm based on the Bayesian inference, and PLUM is a wavefield-based algorithm that predicts ground motions directly from observed shakings. Another notable update was the incorporation of new observation facilities including S-net, a large-scale ocean bottom seismometer network deployed along the Japan and Kuril trenches. The prediction accuracy and warning issuance performance analysis for the updated JMA EEW system showed that IPF improved the source-based ground motion prediction accuracy and reduced the risk of issuing overpredicted warnings. PLUM made the system less likely to underpredict strong ground motions and improved the warning issuance timeliness. The detection time analysis for the S-net incorporation suggested that S-net enabled the system to issue the first EEW report earlier than before the S-net incorporation for earthquakes around the Japan and Kuril trenches. Those findings indicate that the JMA EEW system has made substantial progress both on software and hardware aspects over the 10 years after the Tohoku-Oki earthquake.

scholarly journals Resolving dynamic ground motions with high-rate GNSS and implications for data fusion in broadband seismology and Earthquake Early Warning

2020 ◽  
Author(s):  
Roland Hohensinn ◽  
Nikolaj Dahmen ◽  
John Clinton ◽  
Alain Geiger ◽  
Markus Rothacher
Keyword(s):  
Data Fusion ◽  
Real Time ◽  
Early Warning ◽  
Ground Motions ◽  
Real Data ◽  
Satellite System ◽  
Earthquake Early Warning ◽  
High Rate ◽  
Velocity Waveform ◽  
Global Navigation Satellite

<p>In this paper we highlight the potential of geodetic high-precision and high-rate GNSS <em>(Global Navigation Satellite System)</em> sampling (1 to 100 Hz) for resolving seismic ground motions, of both the near and the far field of an earthquake. The analysis of the budget and characteristics of the error of high-rate GNSS displacement time series yields results, discussion, and conclusions on the sensitivity and waveform resolvability as well as on the derivation of a minimum detectable displacement (in the statistical sense).</p><p>Based on these analyses, we show how GNSS can contribute to optimal broadband displacement and velocity waveform products by means of data fusion by combining measurements taken from co-located sensors – e.g. accelerometers or gyroscopes – in real-time, near real-time and postprocessing mode. Concerning the inclusion of GNSS for such an analysis, we also briefly explore the ability of GNSS to record signals from different earthquake magnitudes and epicentral distances. We show that high-rate GNSS is sensitive to displacements down to the level of a few millimeters, and even below – an example also comes from the detection of very small vibrations from 100 Hz GNSS data.</p><p>We analyze measurements of synthetized signals obtained from experiments with a shake table, as well as from real data from strong earthquakes, namely the 6.5 M<sub>w</sub> event of 2016 near the city of Norcia (Italy) and the 7.0 M<sub>w</sub> Kumamoto earthquake of 2016 (Japan). Based on these data and our main findings, we finally discuss the role of GNSS in Earthquake Early Warning in terms of a fast hypocenter localization and reliable magnitude estimation.</p>

scholarly journals Robust Earthquake Early Warning at a Fraction of the Cost: ASTUTI Costa Rica

AGU Advances ◽  
2021 ◽  
Vol 2 (3) ◽  
Author(s):  
Benjamin A. Brooks ◽  
Marino Protti ◽  
Todd Ericksen ◽  
Julian Bunn ◽  
Floribeth Vega ◽  
...  
Keyword(s):  
Costa Rica ◽  
Early Warning ◽  
Earthquake Early Warning ◽  
The Cost

First-Year Performance of a Nationwide Earthquake Early Warning System Using a Wavefield-Based Ground-Motion Prediction Algorithm in Japan

2020 ◽  
Vol 91 (2A) ◽  
pp. 826-834
Author(s):  
Yuki Kodera ◽  
Naoki Hayashimoto ◽  
Ken Moriwaki ◽  
Keishi Noguchi ◽  
Jun Saito ◽  
...  
Keyword(s):  
Ground Motion ◽  
Early Warning ◽  
Ground Motions ◽  
Earthquake Early Warning ◽  
Japan Meteorological Agency ◽  
Prediction Algorithm ◽  
False Alarms ◽  
First Year ◽  
Earthquake Early Warning System ◽  
Earthquake Scenarios

Abstract The propagation of local undamped motion (PLUM) algorithm is a wavefield-based method that predicts ground motions using direct observations. In March 2018, the Japan Meteorological Agency (JMA) implemented PLUM into its nationwide earthquake early warning (EEW) system, in order to enhance system robustness for complex earthquake scenarios in which traditional source-based algorithms fail to provide accurate and timely ground-motion predictions. This was the first nationwide EEW system to implement a wavefield-based methodology. Here, we evaluate the performance of PLUM during its first year of implementation in the JMA EEW system, using earthquakes that occurred between March 2018 and March 2019; these include 13 earthquakes that satisfied the public warning issuance criteria. Our analysis shows that PLUM predicted ground motions without significant errors and reduced the number of missed warnings. These findings indicate that introducing the wavefield-based methodology benefits EEW users with high tolerance of false alarms, including the general public.

scholarly journals Real-Time Prediction of Impending Ground Shaking: Review of Wavefield-Based (Ground-Motion-Based) Method for Earthquake Early Warning

2021 ◽  
Vol 9 ◽  
Author(s):  
Mitsuyuki Hoshiba
Keyword(s):  
Real Time ◽  
Ground Motion ◽  
Early Warning ◽  
Ground Motions ◽  
Source Parameters ◽  
Earthquake Early Warning ◽  
Peak Ground Velocity ◽  
Ground Shaking ◽  
Time Prediction ◽  
Seismic Waveform

Earthquake early warning (EEW) systems aim to provide advance warning of impending ground shaking, and the technique used for real-time prediction of shaking is a crucial element of EEW systems. Many EEW systems are designed to predict the strength of seismic ground motions (peak ground acceleration, peak ground velocity, or seismic intensity) based on rapidly estimated source parameters (the source-based method), such as hypocentral location, origin time, magnitude, and extent of fault rupture. Recently, however, the wavefield-based (or ground-motion-based) method has been developed to predict future ground motions based directly on the current wavefield, i.e., ground motions monitored in real-time at neighboring sites, skipping the process of estimation of the source parameters. The wavefield-based method works well even for large earthquakes with long duration and huge rupture extents, highly energetic earthquakes that deviate from standard empirical relations, and multiple simultaneous earthquakes, for which the conventional source-based method sometimes performs inadequately. The wavefield-based method also enables prediction of the ongoing seismic waveform itself using the physics of wave propagation, thus providing information on the duration, in addition to the strength of strong ground motion for various frequency bands. In this paper, I review recent developments of the wavefield-based method, from simple applications using relatively sparse observation networks to sophisticated data assimilation techniques exploiting dense networks.

The Impact of 3D Finite-Fault Information on Ground-Motion Forecasting for Earthquake Early Warning

2021 ◽  
Author(s):  
Jessica R. Murray ◽  
Eric M. Thompson ◽  
Annemarie S. Baltay ◽  
Sarah E. Minson
Keyword(s):  
Ground Motion ◽  
Early Warning ◽  
Line Source ◽  
Earthquake Early Warning ◽  
Source Characterization ◽  
Origin Time ◽  
Finite Fault ◽  
Alert Threshold ◽  
The Impact ◽  
Fault Information

ABSTRACT We identify aspects of finite-source parameterization that strongly affect the accuracy of estimated ground motion for earthquake early warning (EEW). EEW systems aim to alert users to impending shaking before it reaches them. The U.S. West Coast EEW system, ShakeAlert, currently uses two algorithms based on seismic data to characterize the earthquake’s location, magnitude, and origin time, treating it as a point or line source. From this information, ShakeAlert calculates shaking intensity and alerts locations where shaking estimates exceed a threshold. Several geodetic EEW algorithms under development would provide 3D finite-fault information. We investigate conditions under which this information produces sufficiently better intensity estimates to potentially improve alerting. Using scenario crustal and subduction interface sources, we (1) identify the most influential source geometry parameters for an EEW algorithm’s shaking forecast, and (2) assess the intensity alert thresholds and magnitude ranges for which more detailed source characterization affects alert accuracy. We find that alert regions determined using 3D-source representations of correct magnitude and faulting mechanism are generally more accurate than those obtained using line sources. If a line-source representation is used and magnitude is calculated from the estimated length, then incorrect length estimates significantly degrade alert region accuracy. In detail, the value of 3D-source characterization depends on the user’s chosen alert threshold, tectonic regime, and faulting style. For the suite of source models we tested, the error in shaking intensity introduced by incorrect geometry could reach levels comparable to the intrinsic uncertainty in ground-motion calculations (e.g., 0.5–1.3 modified Mercalli intensity [MMI] units for MMI 4.5) but, especially for crustal sources, was often less. For subduction interface sources, 3D representations substantially improved alert area accuracy compared to line sources, and incorrect geometry parameters were more likely to cause error in calculated shaking intensity that exceeded uncertainties.

ShakeAlert Earthquake Early Warning System Performance during the 2019 Ridgecrest Earthquake Sequence

2020 ◽  
Vol 110 (4) ◽  
pp. 1904-1923 ◽  
Author(s):  
Angela I. Chung ◽  
Men-Andrin Meier ◽  
Jennifer Andrews ◽  
Maren Böse ◽  
Brendan W. Crowell ◽  
...  
Keyword(s):  
Los Angeles ◽  
Early Warning ◽  
Early Warning System ◽  
Los Angeles County ◽  
Warning System ◽  
Earthquake Early Warning ◽  
Earthquake Early Warning System ◽  
Sequence Of Events ◽  
Finite Fault ◽  
The U.S

ABSTRACT During July 2019, a sequence of earthquakes, including an Mw 6.4 foreshock and an Mw 7.1 mainshock, occurred near Ridgecrest, California. ShakeAlert, the U.S. Geological Survey (USGS) earthquake early warning system being developed for the U.S. West Coast, was operational during this time, although public alerting was only available within Los Angeles County. ShakeAlert created alert messages for the two largest events and for many of the larger aftershocks. In this study, we dissect log files and replay data through the system to reconstruct the sequence of events and analyze the performance of the system during that period. Although the system performed reasonably well overall, the sequence also revealed various issues and short comings that will be addressed in impending and future system upgrades. ShakeAlert detected and characterized both the Mw 6.4 and Mw 7.1 earthquakes within 6.9 s of their origin times and created alert messages that were available to ShakeAlert’s pilot users. No public alerts were sent out by the ShakeAlertLA cell phone app (the only publicly available alerting method at the time), because the predicted shaking for Los Angeles County was below the app’s alerting threshold of modified Mercalli intensity 4.0. For the Mw 6.4 event, this was accurate. For the Mw 7.1 event, public alerts for Los Angeles County were warranted, but ShakeAlert underpredicted the shaking levels, because both the point-source and finite-fault algorithms underestimated the magnitude of the earthquake by 0.8 units. A number of software and hardware issues that were responsible for the magnitude underestimation of the mainshock have been identified and will be addressed in future ShakeAlert releases. We also analyze the hypothetical alerting performance of ShakeAlert had public alerting been available throughout southern California.

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