Presented on March 13, 2024, by

Dr. Chieh-Ying Ke
Department of Atmospheric Sciences
National Central University
Taoyuan City, Taiwan


A Mei-Yu front with an accumulated rainfall of over 550 mm in 8 hours stagnated in northern Taiwan in the early morning of June 1-2, 2017. This study investigates the primary characteristics of this extreme rainfall event using both observational data and numerical model simulations. A modified k-means clustering method is applied to classify 128-member ensemble simulations into five groups by rainfall map. The dynamic features on both the meso-α and meso-β scales are discussed to diagnose the key factors responsible for the front stagnation and heavy rainfall in northern Taiwan while also understanding the forecast uncertainty. The low-level jet plays a significant role in the extreme rainfall process and highlights the importance of the connection between short-wave troughs and the rainband spatial distributions. Through analysis, two types can be further distinguished within five clusters, providing a comprehensive explanation of the interaction between the mid-to-low-level trough and the front in northern Taiwan. In summary, this clustering analysis not only aids in analyzing the dynamic structure of the Mei-Yu front but also assists in evaluating model simulations’ performance, offering an overview of Mei-Yu processes at different scales.


Dr. Ke is a Postdoctoral Research Fellow at the National Central University, Taiwan. Her current project is in weather radar meteorology, including observation, dynamic and thermodynamic analysis, retrieval of wind field, data assimilation, ensemble simulation, and machine learning.