Affiliation:
1. Earthquake Research Institute the University of Tokyo Bunkyo‐ku Japan
2. Artificial Intelligence Laboratory Fujitsu Limited Kawasaki Japan
Abstract
AbstractLong‐period (LP; approximately 2–10 s) ground motions generated by large earthquakes are amplified in large basins and threaten high‐rise buildings in modern cities. In this study, we accomplished an early forecast of LP ground motions in distant basins based on deep learning technology using waveforms observed near the epicenter. A Temporal Convolutional Network was first trained using waveform data from past large earthquakes in the Japan Trench. LP ground motions of recent large earthquakes, including the 2011 Off the Pacific coast of Tohoku earthquake (Mw 9.0), were forecasted in the Kanto (Tokyo) and Osaka basins. This study effectively forecasted LP ground motions of large earthquakes regarding amplitude, waveform envelope shape, spectral characteristics, and duration. Faster forecasts (in 0.05 s or less) allow for updating forecasts as data is acquired, improving forecast accuracies and ensuring 1–2 min of lead time before large and prolonged shakes occur.
Funder
Japan Society for the Promotion of Science London
JST-Mirai Program
Earthquake Research Institute, University of Tokyo
Publisher
American Geophysical Union (AGU)
Subject
General Earth and Planetary Sciences,Geophysics