Room: Ballroom
Date: 4/20/2023
Session Time: 8:00 AM to 5:45 PM (local time)
Earthquake Early Warning Optimization and Efficacy
Several elements contribute to the optimization of an Earthquake Early Warning (EEW) system’s performance, including: the design of the network, choice of sensors, algorithm refinement and means of communications. The processing of data and the accuracies and latencies this introduces also require analysis to ensure warnings are timely and meaningful. For example, the inclusion of site amplification in estimating intensities and the extent of the potentially impacted region should improve the accuracy of the EEW system; it may, however, slow the distribution of alerts. Additionally, EEW systems can only be effective if people and systems respond appropriately. Technical recipients must have automated systems in place to initiate protective measures, and people need to take safe response actions, such as to Drop, Cover and Hold on. To establish the necessary culture of awareness and preparedness, EEW organizations must work with others, including emergency measures organizations, to ensure a broad, consistent and authoritative EEW education and outreach effort. Such initiatives should include engagement with critical infrastructure operators and take special care to address particularly vulnerable populations, such as low income, new immigrants, Indigenous and elderly.
This session invites abstracts on all aspects of optimizing EEW systems, including sensor and communication developments, optimizing methodologies and system assessment and abstracts related to Education, Outreach and Engagement for EEW.
Conveners
Alison L. Bird, Natural Resources Canada, Sidney (alison.bird@nrcan-rncan.gc.ca)
Claire Perry, Natural Resources Canada (claire.perry@nrcan-rncan.gc.ca)
Sara K. McBride, U.S. Geological Survey (skmcbride@usgs.gov)
Danielle Sumy, Incorporated Research Institutions for Seismology (danielle.sumy@iris.edu)
Poster Presentations
| Participant Role | Details | Action |
|---|---|---|
| Submission | Evaluating the Performance of Long Short-Term Memory Neural Network in Predicting Peak Ground Acceleration of Earthquakes Using Shrinking P-Wave Data | View |
| Submission | Alaska Earthquake Early Warning Scenarios and Warning Time Estimates | View |
| Submission | Earthquake Science Communication of the 6.4 M Event Through Various Dissemination Products Used at the Puerto Rico Seismic Network | View |
| Submission | Evaluating the Impact of Location Errors on Magnitude Estimates Through Epic | View |
| Submission | Expected Contribution Metrics for Earthquake Early Warning Network Telemetry | View |
| Submission | Redundant Telemetry, System Monitoring, and Planning Tools for a Highly Resilient and Secure Regional Seismic Network (RSN) | View |
| Submission | Toward Implementing Earthquake Early Warning in Resource-Limited Regions: Comparing Magnitudes Predicted by Traditional Regressions and by Convolutional Neural Networks | View |
| Submission | Earthquake Early Warning Instrumentation and Efficient Workflows | View |
| Submission | National Public Earthquake Early Warning Systems Emerging Across Central America. | View |
| Submission | Update on the Progress of California Strong Motion Instrumentation Program (CSMIP) Toward Real Time Data Acquisition | View |
| Submission | Engagement and Outreach to Ensure the Success of Canada’s Earthquake Early Warning System | View |
| Submission | Geocoding Applications for Social Science to Improve Earthquake Early Warning Systems | View |
| Submission | WITHDRAWN Performance of a Real-Time Machine Learning Classifier in the Epic Earthquake Early Warning Algorithm | View |
| Submission | Empirical Calibration of Site Amplification From Residual Analysis of Earthquake Ground Motion Spectra and Station Magnitudes in Eastern Canada | View |
Earthquake Early Warning Optimization and Efficacy [Poster]
Description