Data Assimilation Using High‐Frequency Radar for Tsunami Early Warning: A Case Study of the 2022 Tonga Volcanic Tsunami

Author:

Wang Yuchen1ORCID,Imai Kentaro1,Mulia Iyan E.2ORCID,Ariyoshi Keisuke1ORCID,Takahashi Narumi13,Sasaki Kenichi4,Kaneko Hitoshi4ORCID,Abe Hiroto45ORCID,Sato Yoshiaki4

Affiliation:

1. Yokohama Institute for Earth Sciences Japan Agency for Marine–Earth Science and Technology Yokohama Japan

2. Prediction Science Laboratory RIKEN Cluster for Pioneering Research Kobe Japan

3. Network Center for Earthquake, Tsunami and Volcano National Research Institute for Earth Science and Disaster Resilience Tsukuba Japan

4. Mutsu Institute for Oceanography Japan Agency for Marine–Earth Science and Technology Mutsu Japan

5. Faculty of Fisheries Sciences Hokkaido University Hakodate Japan

Abstract

AbstractHigh‐frequency (HF) radar monitors the sea surface current velocity and provides information for tsunami early warning. SeaSondeR, an HF ocean radar system in the eastern Tsugaru Strait, Japan, measured the tsunami‐induced current velocity during the 2022 Tonga volcanic tsunami. As an air‐coupled tsunami, the generating mechanism was complex, making it difficult to predict coastal tsunamis using traditional early warning methods. We adopted the tsunami data assimilation (DA) approach, which reconstructs the tsunami wavefield using offshore data and does not require source information, to forecast the coastal tsunami waveforms. Observations from the HF radar and offshore bottom pressure gauges (OBPGs) were used as the input for tsunami DA. The assimilation process started at 09:00 (UTC, hereafter) and forecasts were made at 14:00 and 15:00. The surface current velocity recorded by the HF radar reached the maximum (∼0.25 m/s) at 13:00, which corresponded to a negative phase of ∼2 cm sea level variation observed by OBPGs. We compared the forecasted waveforms with the observed waveforms at Hakodate and Shimokita tide gauges. The assimilation results obtained using HF radar showed a better performance in tsunami forecasting than those using OBPG in this case study. At 14:00, the forecasting accuracy indices were 91% and 67% for the next 2 and 6 hr, respectively. At 15:00, it was 63% and 70% for the next 2 and 6 hr, respectively. We suggest that HF radar could be a good supplement to OBPG for tsunami early warning purposes.

Funder

Japan Society for the Promotion of Science

Publisher

American Geophysical Union (AGU)

Subject

Space and Planetary Science,Earth and Planetary Sciences (miscellaneous),Geochemistry and Petrology,Geophysics

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3