scholarly journals Preliminary Results of an Earthquake Early Warning System in Costa Rica

2021 ◽  
Vol 9 ◽  
Author(s):  
Juan Porras ◽  
Frédérick Massin ◽  
Mario Arroyo-Solórzano ◽  
Ivonne Arroyo ◽  
Lepolt Linkimer ◽  
...  

We analyze the performance of a prototype earthquake early warning system deployed at the National Seismological Network of Costa Rica in collaboration with the Swiss Seismological Service by presenting the real-time performance during six earthquakes (Mw 5.1-6.4) that took place during 2018 and 2019. We observe that, despite only limited efforts to optimize the existing network of 158 stations, for EEW purposes, the network density allows fast determination of source parameters using both the Virtual Seismologist and the Finite Fault Rupture Detector algorithms. Shallow earthquakes on or near-shore are routinely identified within 11–20 s of their occurrence. The warning times for the capital city of San Jose are of 43 s for epicenters located at 220 km, like for the Mw 6.4 Armuelles earthquake. On the other hand, during the time analyzed, the EEW system did not provide positive warning times for earthquakes at distances less than 40 km from San Jose. Even though large (Mw > 7) distant historical earthquakes have not caused heavy damage in San Jose, there is potential for developing an EEW system for Costa Rica, especially for the purposes of rapid earthquake notifications, disaster response management, and seismic risk mitigation.

2020 ◽  
Vol 110 (4) ◽  
pp. 1904-1923 ◽  
Author(s):  
Angela I. Chung ◽  
Men-Andrin Meier ◽  
Jennifer Andrews ◽  
Maren Böse ◽  
Brendan W. Crowell ◽  
...  

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.


Author(s):  
S. Enferadi ◽  
Z. H. Shomali ◽  
A. Niksejel

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.


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

2021 ◽  
Author(s):  
Bita Najdahmadi ◽  
Marco Pilz ◽  
Dino Bindi ◽  
Hoby Njara Tendrisoa Razafindrakoto ◽  
Adrien Oth ◽  
...  

<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>


2018 ◽  
Vol 89 (6) ◽  
pp. 2322-2336 ◽  
Author(s):  
J. R. Murray ◽  
B. W. Crowell ◽  
R. Grapenthin ◽  
K. Hodgkinson ◽  
J. O. Langbein ◽  
...  

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