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

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.

scholarly journals Feasibility study of earthquake early warning in Tehran, Iran

2021 ◽  
Author(s):  
S. Enferadi ◽  
Z. H. Shomali ◽  
A. Niksejel
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Earthquake Early Warning ◽  
Disaster Mitigation ◽  
Lead Times ◽  
Worst Case ◽  
Earthquake Parameters ◽  
Earthquake Early Warning System ◽  
Earthquake Scenarios

AbstractIn this study, we examine the scientific feasibility of an Earthquake Early Warning System in Tehran, Iran, by the integration of the Tehran Disaster Mitigation and Management Organization (TDMMO) accelerometric network and the PRobabilistic and Evolutionary early warning SysTem (PRESTo). To evaluate the performance of the TDMMO-PRESTo system in providing the reliable estimations of earthquake parameters and the available lead-times for The Metropolis of Tehran, two different approaches were analyzed in this work. The first approach was assessed by applying the PRESTo algorithms on waveforms from 11 moderate instrumental earthquakes that occurred in the vicinity of Tehran during the period 2009–2020. Moreover, we conducted a simulation analysis using synthetic waveforms of 10 large historical earthquakes that occurred in the vicinity of Tehran. We demonstrated that the six worst-case earthquake scenarios can be considered for The Metropolis of Tehran, which are mostly related to the historical and instrumental events that occurred in the southern, eastern, and western parts of Tehran. Our results indicate that the TDMMO-PRESTo system could provide reliable and sufficient lead-times of about 1 to 15s and maximum lead-times of about 20s for civil protection purposes in The Metropolis of Tehran.

The First Stage of an Earthquake Early Warning System in South Korea

2017 ◽  
Vol 88 (6) ◽  
pp. 1491-1498 ◽  
Author(s):  
Dong‐Hoon Sheen ◽  
Jung‐Ho Park ◽  
Heon‐Cheol Chi ◽  
Eui‐Hong Hwang ◽  
In‐Seub Lim ◽  
...  
Keyword(s):  
South Korea ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Earthquake Early Warning ◽  
Earthquake Early Warning System

Robust, an Earthquake Early Warning System in the Lower Rhine Embayment, Germany

2021 ◽  
Author(s):  
Bita Najdahmadi ◽  
Marco Pilz ◽  
Dino Bindi ◽  
Hoby Njara Tendrisoa Razafindrakoto ◽  
Adrien Oth ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Earthquake Early Warning ◽  
Optimization Approach ◽  
Ground Acceleration ◽  
Earthquake Early Warning System ◽  
Scenario Earthquakes ◽  
Lower Rhine Embayment ◽  
Lower Rhine

<p>The Lower Rhine Embayment in western Germany is one of the most important areas of earthquake recurrence north of the Alps, facing a moderate level of seismic hazard in the European context but a significant level of risk due to a large number of important industrial infrastructures. In this context, the project ROBUST aims at designing a user-oriented hybrid earthquake early warning and rapid response system where regional seismic monitoring is combined with smart, on-site sensors, resulting in the implementation of decentralized early warning procedures.<br><br>One of the research areas of this project deals with finding an optimal regional seismic network arrangement. With the optimally compacted network, strong ground movements can be detected quickly and reliably. In this work simulated scenario earthquakes in the area are used with an optimization approach in order to densify the existing sparse network through the installation of additional decentralized measuring stations. Genetic algorithms are used to design efficient EEW networks, computing optimal station locations and trigger thresholds in recorded ground acceleration. By minimizing the cost function, a comparison of the best earthquake early warning system designs is performed and the potential usefulness of existing stations in the region is considered as will be presented in the meeting.</p>

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