Japan Geoscience Union Meeting 2025

Presentation information

[E] Poster

A (Atmospheric and Hydrospheric Sciences ) » A-AS Atmospheric Sciences, Meteorology & Atmospheric Environment

[A-AS05] Weather, Climate, and Environmental Science Studies using High-Performance Computing

Wed. May 28, 2025 5:15 PM - 7:15 PM Poster Hall (Exhibition Hall 7&8, Makuhari Messe)

convener:Hisashi Yashiro(National Institute for Environmental Studies), Masuo Nakano(Japan Agency for Marine-Earth Science and Technology), Miyakawa Tomoki(Atmosphere and Ocean Research Institute, The University of Tokyo), Takuya Kawabata(Meteorological Research Institute)

5:15 PM - 7:15 PM

[AAS05-P07] Case Simulation Study and Adaptation Methods for the Spread of Dengue Fever in Taiwan

*JOU PING HOU1, Chia-Wei Chang1, Tzu-Ling Chen1 (1.Chung Cheng Institute of Technology, National Defense University)

Keywords:Global warming, Dengue fever, WRF, Solar-powered AI automatic mosquito-trapping vehicle

From 1880 to 1980, the century-long temperature rise trend in Taiwan was 0.08°C per decade. However, over the past 30 years (1993 to 2022), based on observations from 11 surface weather observed stations in Taiwan, the air temperature rise trend has accelerated to 0.25°C per decade. As global warming intensifies, this average temperature increase rate is likely to continue rising, making Taiwan a significantly warming region. During this warming process, various organisms have adapted by gradually shifting their habitats. Among them, dengue fever disease-carrying mosquitoes have been expanding from southern Taiwan to northern regions, leading to a broader dengue infection area. Using the atmospheric WRF model, we selected a case study (June 29–30, 2015) to analyze the environmental atmospheric factors contributing to the sudden increase in vector mosquitoes in the Shan-hua area. Our findings indicate that high air temperatures and heavy rainfall are key factors driving the surge in dengue fever disease-carrying mosquitoes. To efficiently eliminate disease-carrying mosquitoes and reduce labor costs, we have designed a solar-powered AI automatic mosquito-trapping vehicle. By incorporating our AI-driven obstacle avoidance function, we have significantly improved the mosquito-trapping efficiency, enabling the vehicle to autonomously capture mosquitoes in affected areas around the clock, effectively curbing the spread of dengue fever. Furthermore, to promote energy conservation and carbon reduction, we utilize solar charging panels to supplement the power supply of our solar-powered AI automatic mosquito-trapping vehicle, indirectly mitigating environmental warming.