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Real-Time Tsunami Data Assimilation of S-Net Pressure Gauge Records During the 2016 Fukushima Earthquake

Session: Advances in the Science and Observation of Tsunamis

Type: Oral

Date: 4/22/2021

Presentation Time: 10:30 AM Pacific

Description: 

The 2016 Fukushima earthquake (M7.4) generated a moderate tsunami, which was recorded by the offshore pressure gauges of the Seafloor Observation Network for Earthquakes and Tsunamis (S-net). We used 28 S-net pressure gauge records for tsunami data assimilation and forecasted the tsunami waveforms at four tide gauges on the Sanriku coast. The S-net raw records were processed using two different methods; in the first method, we removed the tidal components by polynomial fitting and applied a low-pass filter. In the second method, we used a real-time tsunami detection algorithm based on Ensemble Empirical Mode Decomposition to extract the tsunami signals, imitating real-time operations for tsunami early warning. The scores of forecast accuracy of the two detection methods are 60% and 74%, respectively, for a time window of 35 min, but they improve to 89 % and 94 % if we neglect the stations with imperfect modeling or insufficient offshore observations. Hence, the tsunami data assimilation approach can be put into practice with the help of the real-time tsunami detection algorithm.

Presenting Author: Yuchen Wang

Student Presenter: Yes

Authors