日本地球惑星科学連合2023年大会

講演情報

[J] オンラインポスター発表

セッション記号 H (地球人間圏科学) » H-DS 防災地球科学

[H-DS06] 津波とその予測

2023年5月24日(水) 10:45 〜 12:15 オンラインポスターZoom会場 (9) (オンラインポスター)

コンビーナ:室谷 智子(国立科学博物館)、馬場 俊孝(徳島大学大学院産業理工学研究部)

現地ポスター発表開催日時 (2023/5/23 17:15-18:45)

10:45 〜 12:15

[HDS06-P02] Korea Meteorological Administration's Tsunami Prediction System Overview

*TAEHWAN JO1Seolhan You1Haseong Lee1、Jimin Lee1Sun-Cheon Park1 (1.Korea Meteorological Administration)

キーワード:Tsunami, Tsunami Prediction System, Korea Meteorological Administration, COMCOT, Numerical Modelling

A tsunami, one of the natural disasters that can cause great damage, is a long-period wave caused by the displacement of a large volume of water such as submarine earthquakes. Major tsunami disasters in Korea occurred on the western coast of Japan in 1983 and 1993. These tsunamis caused casualties and property damage on the East Coast of Korea. In particular, the East Sea has a possibility of tsunami occurrence.
Now Korea Meteorological Administration (KMA) has established a tsunami scenario database (DB) to issue tsunami warnings after a submarine earthquake occurs, immediately. The tsunami scenario DB has been constructed by setting virtual earthquake scenarios around the ocean of the Korean Peninsula and has been operating its tsunami warning system.
The DB was built with COMCOT version 1.7 by simulating for about 590,000 virtual earthquake cases. The cases have been considered for the depths (10-600km) and magnitudes (6.0-9.0) of 5,901 points around the Korean Peninsula. After the occurrence of a submarine earthquake with a magnitude of 6.0 or higher, the predicted maximum tsunami height is searched based on scenario DB. Then advisory (0.5 - 1m) or warning (over 1m) is first issued according to the predicted maximum tsunami height for each area. After the first warning, KMA provides more accurate tsunami information by executing a numerical simulation of the tsunami using additional analyzed earthquake fault information. At the same time, tsunami travel time map is automatically generated and provided.
In this study, we introduce the KMA tsunami prediction system such as scenario DB and numerical prediction model.