Hiu Ching Tam, Yu-Heng He, Pak Wai Chan, Shiwei Yu, Huisi Mo, Hui Su, Ling-Feng Hsiao, Yangzhao Gong
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引用次数: 0
Abstract
On 7–8 September 2023, Hong Kong was hit by a historical and record-breaking rainstorm associated with the remnant of Tropical Cyclone Haikui (2311). The hourly rainfall recorded at the Hong Kong Observatory Headquarters once reached 158.1 mm, the highest since record began in 1884. The 24-h rainfall even exceeded 600 mm in some parts of the territory. The historical rainstorm resulted in heavy flooding and landslides, bringing significant societal impact to Hong Kong. This paper aims to review this unprecedented heavy rain event from the aspects of diagnosis, forecasting and nowcasting. Early indicators of such events over Hong Kong with substantial lead time are limited from the dynamics and thermodynamics consideration, the numerical weather prediction models, given the present technology. The only indication may come from the climatologically extreme total precipitable water. While recent research of developing a regional risk-based alerting system on the higher impact event of flooding associated with heavy rain might have potential to enhance the weather service, and emerging AI model showed some promising post-simulations, predicting historical and record-breaking rainstorms remains a challenge for operational weather forecasting and warning services.
期刊介绍:
Atmospheric Science Letters (ASL) is a wholly Open Access electronic journal. Its aim is to provide a fully peer reviewed publication route for new shorter contributions in the field of atmospheric and closely related sciences. Through its ability to publish shorter contributions more rapidly than conventional journals, ASL offers a framework that promotes new understanding and creates scientific debate - providing a platform for discussing scientific issues and techniques.
We encourage the presentation of multi-disciplinary work and contributions that utilise ideas and techniques from parallel areas. We particularly welcome contributions that maximise the visualisation capabilities offered by a purely on-line journal. ASL welcomes papers in the fields of: Dynamical meteorology; Ocean-atmosphere systems; Climate change, variability and impacts; New or improved observations from instrumentation; Hydrometeorology; Numerical weather prediction; Data assimilation and ensemble forecasting; Physical processes of the atmosphere; Land surface-atmosphere systems.