2021 Fiscal Year Annual Research Report
Tsunami Data Assimilation With Sparse Observations: Improvement Towards Tsunami Warning System
| Project/Area Number |
19J20293
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| Research Institution | The University of Tokyo |
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Principal Investigator |
WANG YUCHEN 東京大学, 理学系研究科, 特別研究員(DC1) (80943290)
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| Project Period (FY) |
2019-04-25 – 2022-03-31
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| Keywords | Tsunami / Tsunami Early Warning / Data Assimilation / Bottom Pressure Gauge |
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| Outline of Annual Research Achievements |
In the past year, I have been working on tsunami data assimilation for early warning. I successfully conducted a retroactive study of the 2016 Fukushima earthquake. I 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 forecast accuracy score is 74% for a time window of 35 min. In addition, I also worked on the optimal deployment of offshore bottom pressure gauges (OBPGs). I proposed an optimal deployment scheme of OBPGs in the South China Sea, aiming at early warning of potential tsunami hazards based on the data assimilation approach. The results indicated that at least three stations are required to cover the coast along southern China to forecast the tsunami in the South China Sea successfully. The next step is to apply tsunami data assimilation to the tsunami generated by the 2022 Tonga volcanic eruption. The S-net and DONET observation will be adopted.
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| Research Progress Status |
令和3年度が最終年度であるため、記入しない。
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| Strategy for Future Research Activity |
令和3年度が最終年度であるため、記入しない。
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