DeepMind Says Its AI Can Predict Hurricanes Earlier Than Everyone Else

Victoria TurkScienceAug 6, 2026 12:23 PMDeepMind Says Its AI Can Predict Hurricanes Earlier Than Everyone ElseIts WeatherNext model, which will be open-sourced, can accurately predict a storm’s track and intensity using lower-resolution weather data. Researchers don’t yet fully understand how it does this.Photo-Illustration: Wired Staff; Images; Google DeepMindCommentLoaderSave StorySave this storyCommentLoaderSave StorySave this storyIn October 2025, a storm brewed over the Caribbean Sea. Weather models differed on its trajectory.

Would it remain weak and end up in Haiti, or would it intensify and head to Jamaica? Artificial intelligence model WeatherNext, developed by Google’s DeepMind and Google Research, went with the latter. Five days before landfall, it predicted with 80 percent confidence that the storm system would hit Jamaica as a Category 5 hurricane.Hurricane Melissa was catastrophic, causing flooding and landslides across Jamaica.

But the AI model helped forecasters give an earlier warning to communities in its path, so they could better prepare.In a paper published on Thursday in Nature, researchers show that the WeatherNext AI model can predict cyclones with unprecedented accuracy. On average, it gives forecasters a day more lead time than existing models; this means its predictions three days out are as accurate as previous models’ predictions two days out. On the ground, that extra day can mean a lot.“Even a few hours can make a difference,” says Mike Brennan, director of the US National Hurricane Center.

Organizing evacuations, staging supplies, and moving resources to respond to a hurricane risk are all time-sensitive tasks—and making the wrong decision can have big consequences. Machine learning requires ample training data in order to make future predictions, but extreme events are by nature rare occurrences. Predicting a storm’s track—which direction it’s traveling—requires data about weather on a global scale, taking in information such as the location of cold fronts and prevailing winds.

Predicting a storm’s intensity, however, requires much smaller-scale data focused specifically on the local atmospheric and ocean conditions.“That’s something we just don’t get from these global models,” Musgrave says. While earlier AI models have done well at predicting a storm’s track, “intensity they could not do well at all.”It’s critical to predict both: A change in intensity can mean the difference between a relatively weak storm and a major hurricane. Sometimes—as in the case of Hurricane Melissa—a storm system can intensify rapidly, developing into an emergency situation overnight.

Melissa marked the first time the National Hurricane Centre was able to predict a Category 5 hurricane when the storm was only at a Category 1 stage.Before the WeatherNext model was used in live forecasts, researchers tested it on retrospective data. But when forecasters started adopting the model into their operations, this performance held true. This helps to capture any potential “butterfly effect,” says Alet, where a small deviation from a trend could lead to much bigger changes down the line.