Submitted:
22 August 2025
Posted:
22 August 2025
You are already at the latest version
Abstract
Keywords:
1. Introduction
2. Synoptic and Mesoscale Situations
3. Storm-Scale Features
4. Performance of Numerical Models
4.1. Global NWP and AI Models
4.2. Mesoscale NWP Models
5. Nowcasting Aspect
6. Conclusions
References
- Bi, K.; Xie, L.; Zhang, H.; Chen, X.; Gu, X.; Tian, Q. Accurate medium-range global weather forecasting with 3D neural networks. Nature 2023, 619, 533–538. [Google Scholar] [CrossRef]
- Chan, Y.W.; Chan, P.W.; Cheung, P. Observation of downburst associated with intense thunderstorms encountered by an aircraft at Hong Kong International Airport. Applied Sciences 2025, 15, 2223. [Google Scholar] [CrossRef]
- Chen, D.H.; Xue, J.S.; Yang, X.S.; Zhang, H.L.; Shen, X.S.; Hu, J.L.; Wang, Y.; Ji, L.R.; Chen, J.B. New generation of multi-scale NWP system (GRAPES): general scientific design. Chinese Science Bulletin 2008, 53, 3433–3445. [Google Scholar] [CrossRef]
- Chen, L.; Zhong, X.; Zhang, F.; Cheng, Y.; Xu, Y.; Qi, Y.; Li, H. FuXi: a cascade machine learning forecasting system for 15-day global weather forecast. npj Climate and Atmospheric Science 2023, 6, 190. [Google Scholar] [CrossRef]
- Doswell, C.A.I.I.I.; Brooks, H.E.; Maddox, R.A. Flash flood forecasting: An ingredients-based methodology. Weather and Forecasting 1996, 11, 560–581. [Google Scholar] [CrossRef]
- Han, T.; Guo, S.; Ling, F.; Chen, K.; Gong, J.; Luo, J.; Gu, J.; Dai, K.; Ouyang, W.; Bai, L. FengWu-GHR: Learning the Kilometer-scale Medium-range Global Weather Forecasting. arXiv 2024, arXiv:2402.00059. [Google Scholar] [CrossRef]
- He, Y.H.; Chan, P.W. A study of the extended-range weather forecasts by artificial intelligence models Pangu-Weather and FengWu. Weather 2025, 80, 134–138. [Google Scholar] [CrossRef]
- HKO. (2025) Rainstorm Warning System. Hong Kong Observatory. https://www.hko.gov.hk/en/wservice/warning/rainstor.htm (Accessed August 2025).
- Houze, R.A., Jr. Mesoscale convective systems. Reviews of Geophysics 2004, 42, RG4003. [Google Scholar] [CrossRef]
- Lai, S.K.; Chan, P.W.; He, Y.; Chen, S.S.; Kerns, B.W.; Su, H.; Mo, H. Real-time operational trial of atmosphere–ocean–wave coupled model for selected tropical cyclones in 2024. Atmosphere 2024, 15, 1509. [Google Scholar] [CrossRef]
- Lam, R.; Sanchez-Gonzalez, A.; Willson, M.; Wirnsberger, P.; Fortunato, M.; Alet, F.; Ravuri, S.; Ewalds, T.; Eaton-Rosen, Z.; Hu, W.; Merose, A.; Hoyer, S.; Holland, G.; Vinyals, O.; Stott, J.; Pritzel, A.; Mohamed, S.; Battaglia, P. Learning skillful medium-range global weather forecasting. Science 2023, 382, eadi2336. [Google Scholar] [CrossRef] [PubMed]
- Wong, W.K. (2024) AI Technology in Nowcasting. WMO WMC Beijing Workshop on New Technology and Products, Guangzhou, 12–14 November 2024 (presentation available at https://rsmc.hko.gov.hk/nowcast/papers/AI-Nowcasting-Technology.pdf).














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