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Tropical cyclones could be predicted with an extra day’s warning, thanks to an AI model

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Why This Matters

The development of the WeatherNext Cyclones AI model marks a significant advancement in tropical cyclone forecasting, providing up to two weeks' notice. This improved prediction capability can help save lives, reduce property damage, and enhance preparedness efforts worldwide, making it a crucial tool for the tech industry and disaster management agencies.

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Tropical cyclones — also called typhoons or hurricanes, depending on where they occur — are a major cause of deaths worldwide, and inflict considerable damage on property and infrastructure. The formation and evolution of these rapidly rotating weather systems are driven by effects on a range of scales, which makes it incredibly challenging to forecast them accurately using conventional models. Now, writing in Nature, Alet et al.1 introduce WeatherNext Cyclones (WN-C), an artificial-intelligence model that can produce two-week forecasts of unfolding tropical cyclones.

doi: https://doi.org/10.1038/d41586-026-02643-w

References Alet, F. et al. Nature https://doi.org/10.1038/s41586-026-10953-2 (2026). Mooney, K. R. et al. Earth Space Sci. 13, e2025EA004869 (2026). Zhang, Z. et al. Trop. Cyclone Res. Rev. 12, 30–49 (2023). Knapp, K. R., Kruk, M. C., Levinson, D. H., Diamond, H. J. & Neumann, C. J. Bull. Am. Meteorol. Soc. 91, 363–376 (2010). Gomez, M., Poulain-Auzéau, L., Berne, A. & Beucler, T. Artif. Intell. Earth Syst. 5, e250073 (2026). Alet, F. et al. Preprint at arXiv https://doi.org/10.48550/arXiv.2506.10772 (2025). Selz, T. & Craig, G. C. J. Geophys. Res. Mach. Learn. Comput. 3, e2025JH001180 (2026). Sun, Y. Q. et al. Proc. Natl Acad. Sci. USA 122, e2420914122 (2025). Knutson, T. et al. Bull. Am. Meteorol. Soc. 101, E303–E322 (2020). McGovern, A. et al. Bull. Am. Meteorol. Soc. 105, E567–E583 (2024). Download references

Competing Interests The authors declare no competing interests.

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