EGU25-9751, updated on 14 Mar 2025
https://doi.org/10.5194/egusphere-egu25-9751
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Oral | Tuesday, 29 Apr, 15:15–15:25 (CEST)
 
Room 3.29/30
Thunderstorm in Taiwan and Its Impact on Railway
Chi-June Jung1, Ben Jong-Dao Jou1,2, Ko Pak Tin Boaz2, Yi-Hsi Lee1, and Kai-Shiang Yang1
Chi-June Jung et al.
  • 1Center for Weather Climate and Disaster Research, National Taiwan University, Taiwan (d03229001@ntu.edu.tw)
  • 2Department of Atmospheric Sciences, National Taiwan University, Taiwan (jouben@ntu.edu.tw)

Severe convective storms frequently occur in Taiwan, bringing heavy rainfall, strong winds, and lightning. These events significantly disrupt critical infrastructure, including railways, by causing operational delays and damage to facilities. The proximity of the railway network to high-frequency thunderstorm zones highlights the need for tailored meteorological applications to mitigate these risks. 

Heavy rainfall and wind gust are key characteristics of severe convective storms. Analysis of a thunderstorm event in Taipei Basin demonstrates that merged convective cells can produce extreme rain rates exceeding 60 mm in 20 minutes, which is closely tied to urban flash flood occurrences. Microbursts, identified through radar signatures like descending precipitation cores and strong near-ground divergent outflows, further exacerbate railway hazards, generating wind gusts exceeding 10 m/s. 

To address these challenges, the Central Weather Administration issues real-time severe thunderstorm warnings based on radar observations, such as radar echoes > 55 dBZ and 60-minute rainfall > 40 mm. Since 2024, National Taiwan University has collaborated with Taiwan Railway Company to implement targeted warnings. These alerts, distributed via the LINE app, provide real-time updates on affected railway sections, improving disaster preparedness and operational resilience. 

Between April and October 2024, alerts were issued for various disasters, including flooding, fallen trees, and landslides. However, the actual occurrence rate was only 2%. To reduce false alarms and enhance the accuracy of warnings, radar-based quantitative precipitation forecast (QPF) thresholds are being introduced. These efforts aim to strengthen railway safety and minimize disruptions caused by severe weather events.

How to cite: Jung, C.-J., Jou, B. J.-D., Boaz, K. P. T., Lee, Y.-H., and Yang, K.-S.: Thunderstorm in Taiwan and Its Impact on Railway, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9751, https://doi.org/10.5194/egusphere-egu25-9751, 2025.