Tsunami Data Assimilation With Sparse Observations: Improvement Towards Tsunami Warning System

稀疏观测的海啸数据同化：海啸预警系统的改进

• 批准号: 19J20293
• 负责人: WANG YUCHEN
• 金额: $ 1.79万
• 依托单位: The University of Tokyo
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for JSPS Fellows
• 财政年份: 2019
• 资助国家: 日本
• 起止时间: 2019-04-25 至 2022-03-31
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-19J20293/
• 关键词: Tsunami; Tsunami Early Warning; Data Assimilation; Bottom Pressure Gauge; Real-Time Detection; Resonance Analysis; Tsunami Forecasting; Tsunami Resonance

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.

在过去的一年里，我一直致力于海啸数据同化的早期预警。我成功地对2016年的福岛地震进行了追溯研究。我使用28个S-net压力计记录进行海啸数据同化，并预测了三陆海岸四个验潮站的海啸波形。在35分钟的时间窗口内，预测准确率得分为74%。此外，我还研究了海上底部压力计（OBPG）的最佳部署。提出了一种基于数据同化方法的南海海底地震预警系统的优化部署方案。结果表明，要成功地预报南海海啸，至少需要三个台站覆盖沿着华南沿海。下一步是将海啸数据同化应用于2022年汤加火山爆发产生的海啸。将采用S-net和DONET观测。

项目成果

Tsunami Data Assimilation of the 2015 Torishima Earthquake

2015 年鸟岛地震海啸数据同化

• 发表时间: 2019
• 作者: Sandanbata;O.;Wang;Y.;Satake;K.;Maeda;T.;and Su;H.
• 通讯作者: H.

A method of real-time tsunami detection

一种实时海啸检测方法

• 发表时间: 2019
• 作者: Wang;Y.;& Satake;K.
• 通讯作者: K.

The Third Peking University Geophysics Symposium for Young Scientists

第三届北京大学地球物理青年科学家研讨会

• 发表时间: 2019

Tsunami resonance and standing waves in Hangzhou Bay

• DOI: 10.1063/5.0059383
• 发表时间: 2021-08
• 期刊: Physics of Fluids
• 影响因子: 4.6
• 作者: Zhiyuan Ren;J. Hou;Peitao Wang;Yuchen Wang

Tsunami data assimilation of S-net pressure gauge records

S-net压力表记录的海啸数据同化

• 发表时间: 2020
• 作者: Wang;Y. and Satake;K.
• 通讯作者: K.