Next Generation Earthquake Early Warning Systems: Advances, Innovations and Applications [Poster]
Date: 4/25/2019
Time: 6:00 PM to 11:00 PM
Room: Grand Ballroom
Recent scientific advances in real-time data processing, source characterization and ground motion prediction shape the future of earthquake early warning (EEW) systems. Machine-learning based techniques take conventional event detection algorithms to the next level by successfully identifying concurrent seismic radiations from multiple sources and reducing the number of false triggers. Integration of real-time seismic and GPS data reduce uncertainties on source characterization by providing additional insights on event magnitude, fault slip and rupture geometry. Ground-motion algorithms that make use of real-time observed amplitudes, regional wave propagation attributes and frequency-dependent site amplification allow for the reliable prediction of shaking intensities. Incorporation of building/facility inventory and associated vulnerabilities allows prediction of where damage potential is high for rapid aftermath response.
This session seeks contributions from the latest advances in the field of earthquake early warning, including (but not limited to):
• real-time earthquake location, rupture and ground motion characterization techniques/algorithms;
• insights gleaned from multi-disciplinary real-time data sets;
• challenges related to complex ruptures and concurrent events;
• characterization of prediction uncertainties and risk-oriented probabilistic early warnings;
• tsunami potential and early warning at local and global scales;
• case studies, testing and performance evaluation of existing systems;
• near real-time of damage predictions for post-disaster management.
This session is jointly organized by the Seismological Society of Japan and SSA.
Conveners
Angela I. Chung, Berkeley Seismology Lab (aichung@berkeley.edu)
Emrah Yenier, Nanometrics Incorporated (emrahyenier@nanometrics.ca)
Men-Andrin Meier, Caltech (mmeier@caltech.edu)
Mark Novakovic, Nanometrics Incorporated (marknovakovic@nanometrics.ca)
Mitsuyuki Hoshiba, Japan Meteorological Agency (mhoshiba@mri-jma.go.jp)
Yuki Kodera, Japan Meteorological Agency (y_kodera@mri-jma.go.jp)
Poster Presentations
Participant Role | Details | Action |
---|---|---|
Submission | A Case Study of the Plum Earthquake Early Warning Algorithm Using Southern California Data | View |
Submission | Envelope-Based, Real-Time Nested Grid Search: Estimates for Earthquake Early Warning | View |
Submission | A New Multi-Sensor Network Developed for the China Earthquake Early Warning System (EEWs) | View |
Submission | Investigating the Effect of Finite Source Processes in Single Station Based On-Site Earthquake Early Warning System | View |
Submission | Rapid Magnitude Assessment of Large Earthquakes From Recurrent Neural Networks | View |
Submission | Reducing False Positives in the On-Site and Regional Earthquake Early Warning Systems | View |
Submission | California Regional Adjustments to Ground Motion Models Used in Earthquake Early Warning Algorithms | View |
Submission | Investigating the Performance of Earthquake Early Warning Algorithms on the Cascadia Subduction Zone | View |
Submission | Too-Late Warnings by Estimating Mw: Earthquake Early Warning in the Near-Fault Region | View |
Submission | Evaluating and Improving Earthquake Early Warning in Central America | View |
Submission | ElarmS/EPIC Earthquake Early Warning System: 2018-2019 Development and Performance | View |
Submission | Social Science and ShakeAlert | View |
Submission | Finite-Fault Rupture Detector (Finder): Rapid Line-Source Models for Large Crustal Earthquakes in Sichuan, China | View |
Submission | An Automatic S-Phase Arrival Time Picker | View |
Submission | An Amphibious Subduction Zone Earthquake Early Warning System for British Columbians — Introduction, Design and First Results | View |
Submission | Shakealert Testing and Certification: Future Developments | View |
Next Generation Earthquake Early Warning Systems: Advances, Innovations and Applications [Poster]
Description