Articles | Volume 25, issue 8
https://doi.org/10.5194/nhess-25-2803-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-25-2803-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Investigation of an extreme rainfall event during 8–12 December 2018 over central Vietnam – Part 2: An evaluation of predictability using a time-lagged cloud-resolving ensemble system
Chung-Chieh Wang
Department of Earth Sciences, National Taiwan Normal University, Taipei, Taiwan
Department of Earth Sciences, National Taiwan Normal University, Taipei, Taiwan
Viet Nam Institute of Meteorology, Hydrology and Climate Change, Hanoi, Vietnam
Thang Van Vu
Viet Nam Institute of Meteorology, Hydrology and Climate Change, Hanoi, Vietnam
Pham Thi Thanh Nga
Viet Nam Institute of Meteorology, Hydrology and Climate Change, Hanoi, Vietnam
Pi-Yu Chuang
Department of Earth Sciences, National Taiwan Normal University, Taipei, Taiwan
Viet Nam Institute of Meteorology, Hydrology and Climate Change, Hanoi, Vietnam
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The extreme rainfall event (645 mm in 24 h) at the northern coast of Taiwan on 2 June 2017 is studied using a cloud model. Two 1 km experiments with peak amounts of 541 and 400 mm are compared to isolate the reasons for such a difference. It is found that the frontal rainband remains fixed in location for a longer period in the former run due to a low disturbance that acts to focus the near-surface convergence. Therefore, the rainfall is more concentrated and there is a higher total amount.
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In this study, cloud-resolving simulations are performed under idealized and uniform southwesterly flow direction and speed to investigate the rainfall regimes in the Mei-yu season and the role of complex mesoscale topography on rainfall without the influence of unwanted disturbances, including a low-Froude number regime where the thermodynamic effects and island circulation dominate, a high-Froude number regime where topographic rainfall in a flow-over scenario prevails, and a mixed regime.
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This study indicated that the Cloud-Resolving Storm Simulator (CReSS) model significantly improved heavy-rainfall quantitative precipitation forecasts in the Taiwan Mei-yu season. At high resolution, the model has higher threat scores and is more skillful in predicting larger rainfall events compared to smaller ones. And the strength of the model mainly lies in the topographic rainfall rather than less predictable and migratory events due to nonlinearity.
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Short summary
The study assesses the practical predictability of an extreme rainfall event on 8 to 12 December 2018 over central Vietnam using quantitative precipitation forecasts (QPFs) from a time-lagged cloud-resolving ensemble system. To do this, 29 time-lagged (8 d in the forecast range) high-resolution (2.5 km) members were run every 6 h from 3 to 10 December 2018. Results reveal that the cloud-resolving model predicted the rainfall fields in the short range (less than 3 d) for 10 December (the rainiest day).
The study assesses the practical predictability of an extreme rainfall event on 8 to 12 December...
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