Google's WeatherNext Cyclones lands Nature cover, fixing AI weather models' intensity blind spot

jiqizhixin · x · 2026-09-25

Google unveiled WeatherNext Cyclones (WN-C), featured on the cover of Nature, achieving state-of-the-art tropical cyclone track forecasting.

The problem: existing AI weather models run at 28 km resolution and inherit a low-intensity bias from 0.25° global analysis data — they can predict where a cyclone goes but not how strong it gets, long considered a major limitation.
The method: WN-C trains end-to-end on global analysis data plus the historical IBTrACS cyclone database, using a deterministic mapping to convert sparse tabular cyclone track data into gridded tensors at 0.25°, letting the model learn intensity directly from real cyclone records.
Capability: it generates 15-day ensemble forecasts of global weather and cyclone scenarios, delivering the most advanced ensemble predictions for both track and intensity.

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