日本地球惑星科学連合2021年大会

講演情報

[E] ポスター発表

セッション記号 A (大気水圏科学) » A-AS 大気科学・気象学・大気環境

[A-AS03] 台風研究の新展開~過去・現在・未来

2021年6月3日(木) 17:15 〜 18:30 Ch.02

コンビーナ:金田 幸恵(名古屋大学宇宙地球環境研究所)、和田 章義(気象研究所台風・災害気象研究部)、宮本 佳明(慶應義塾大学 環境情報学部)、伊藤 耕介(琉球大学)

17:15 〜 18:30

[AAS03-P08] Evaluation of the Sensitivity of Typhoon Pre-disaster Prevention Model According to the Application of the Type of Soil Data During Typhoon Season

*Woo-Sik JUNG1、HANA NA1 (1.Department of Atmospheric Environment Information Engineering, INJE University, Republic of Korea.)

キーワード:Typhoon Pre-Disaster Prevention Model, Soil Data, WRF

Recently, as global warming has become more serious, SST in the northwest Pacific Ocean has risen, and the frequency and intensity of typhoons affecting the Korean Peninsula have been increasing. Therefore, we are conducting research by developing a Korean typhoon pre-disaster prevention model optimized for the Korean Peninsula based on the Florida Public Hurricane Loss Model (FPHLM) model of the U.S. FDFS. This typhoon pre-disaster prevention model can predict and diagnose the maximum instantaneous wind speed (3-second GUST) and maximum damage that can occur due to strong winds accompanying the typhoon. Since natural disasters have the risk of destroying almost everything at the moment they exceed the intensity of the threshold, it is very important to accurately predict the 3-second GUST and provide reliable information on possible future damage from the perspective of prevention of strong winds accompanying typhoons. To improve the prediction accuracy of the Korean typhoon pre-disaster prevention model, it is very important to improve the reliability of the Weather Research and Forecasting (WRF) numerical model that produces the initial wind information input into the model. Therefore, to improve the accuracy of the WRF model, we perform a sensitivity analysis of the WRF model according to the type of soil data. As a result of comparative analysis of each modeling result by applying the Unified Model (UM) based Global Data Assimilation Prediction System (GDAPS) soil data and Global Forecasting System (GFS) soil data to each WRF model, the accuracy of the WRF modeling results using UM-based GDAPS soil data is better. In addition, the results of the 3-second GUST of the Korean typhoon pre-disaster prevention model, which used WRF modeling results using GDAPS soil data as input, were also found to be more accurate than those of GFS soil data. In terms of preventing damage caused by strong winds accompanied by typhoons in advance, it is thought that the use of a Korean typhoon pre-disaster prevention model with improved accuracy will play an effective role in minimizing damage from typhoons.

This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. 2020R1F1A1068738)