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Operational Tropical Cyclone Forecasting with AI
Nature
(2026) Cite this article
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Tropical cyclones are among the most dangerous and costly weather phenomena, yet forecasting them remains a profound scientific challenge. Here, we introduce WeatherNext Cyclones (WN-C), an AI operational weather model producing state-of-the-art ensemble forecasts for track, intensity, and size of tropical cyclones worldwide. Trained on a combination of global analysis data1 and a global database of historical tropical cyclones2,3, WN-C generates large ensembles of possible global weather and cyclone scenarios extending 15 days into the future. Evaluated on tropical cyclones from 2023–2025, the track, intensity and wind radii predictions from WN-C offer an average of a day or more of lead time advantage over leading operational models, an improvement in accuracy comparable to the progress seen over the last decade of operational development. We achieved these results using inputs orders of magnitude coarser than regional models, suggesting that high resolution is not a strict prerequisite for state-of-the-art intensity forecasting and that this coarser atmospheric data contains more intensity signal than previously recognised. Including predictions from WN-C in a weighted-average consensus ensemble substantially improves its skill. The scalability of WN-C enables up to 1,000-member ensembles which better capture rare events over conventional 50-member ensembles. By providing state-of-the-art operational ensemble guidance to human forecasters, this work represents a step-change towards more reliable and timely forecasts and warnings that can help protect lives and mitigate the devastating impacts of tropical cyclones.
These authors contributed equally: Ferran Alet, Tom R. Andersson, Ilan Price, Stratis Markou, Andrew El-Kadi, Dominic Masters
Ferran Alet, Tom R. Andersson, Ilan Price, Stratis Markou, Andrew El-Kadi, Dominic Masters, Gregory Thornton, Ken MacKay, Ben Gaiarin, Devaja Shah, Elinor Kruse, Jacklynn Stott, Remi Lam, Paul Komarek, Matthew Willson, Alvaro Sanchez-Gonzalez & Peter Battaglia
Samier Merchant, Natalie Williams, Olivia Graham, Akib Uddin & Aaron Bell
NOAA/NWS/NCEP National Hurricane Center, Miami, FL, USA
Wallace Hogsett, David Zelinsky, John Cangialosi & Jonathan Martinez
Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, USA
Jonathan Martinez, James Franklin, Mark DeMaria & Kate Musgrave