Development of a real-time tsunami forecasting method based on the data assimilation technique for next-generation dense tsunametor network

2017 Fiscal Year Final Research Report

• Project/Area Number: 15K16306
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Natural disaster / Disaster prevention science
• Research Institution: The University of Tokyo
• Principal Investigator: Maeda Takuto 東京大学, 地震研究所, 助教 (90435579)
• Project Period (FY): 2015-04-01 – 2018-03-31
• Keywords: 津波 / 即時予測 / 海底圧力観測 / データ同化 / シミュレーション

Outline of Final Research Achievements

This study utilized the data assimilation technique for the real-time tsunami forecasting problem for the first time. The data assimilation directly estimates the tsunami wavefield, consists of tsunami height and flow velocity vector, at the present time rather than the initial tsunami height due to the earthquake fault motion. This was achieved by successive feedbacks from the observed data to the numerical simulation of tsunami wave propagation. Verification of this method has been done via numerical tests with the station layout of the S-net around Japan trench, and a real-world application with offline ocean-bottom stations. On the other hand, tsunami observation based on ocean-bottom pressure gauges may be biased due to the coseismic deformation near the earthquake source, which considerably affects the result of the data assimilation. Several countermeasures against this problem are investigated theoretically.

Free Research Field

地震学