Why the National Hurricane Center bet big on AI to forecast Isaias

From the time Hurricane Isaias first formed, meteorologists at the National Hurricane Center made a big bet. They shaped their predictions to closely match an AI hurricane model developed by Google DeepMind, rather than leaning on the classic physics-based models many Americans are more familiar with, such as the European and GFS. So far, the bet has paid off. Forecasts for this storm reflect the improving reliability of AI weather models overall, and signal an astonishingly rapid shift to routine use of such products by human forecasters. Relying heavily on DeepMind meant NHC forecast Isaias would become a Category 2 from the first advisory on Tuesday, when it didn’t even have a name yet. At that point, many of the physics-based computer models, which rely on mathematical equations describing how the atmosphere works to simulate future weather conditions, were vacillating between different projections but generally forecasting a weaker storm that would take a different track than the DeepMind and other AI models were showing. If the forecast is accurate, it will mark a huge victory for Google and help the people in the path of the storm, who will have had more time to prepare for a significantly stronger blow. Hurricane Isaias is the first hurricane in the tropical Atlantic season, due largely to the effects of a super El Niño in the Pacific, setting a record for the ocean basin’s latest first hurricane of the season. The confidence of NHC forecasters in Google DeepMind model in particular — the newest iteration of which is WeatherNext 3 — stems largely from experience. Last season the Hurricane Center correctly anticipated the rapid intensification of Hurricane Melissa almost three days before its devastating arrival in Jamaica based largely on the projections from DeepMind. It also stems from the fact that the Hurricane Center partnered with Google to help train the model and learn more about its capabilities. As is occurring in many fields right now, the world of meteorology is undergoing rapid advancements due to AI, although these models are used in conjunction with the traditional physics models, which still have their advantages. AI models are trained on past weather events and, in the case of DeepMind’s, are also given current weather data. DeepMind performed extremely well last season, according to NHC director Michael Brennan, and has been accurate in anticipating the intensity of many Pacific Ocean storms this season. “The AI models have shown more consistency” from one model run to the next, Brennan said regarding the reliance on DeepMind for Hurricane Isaias. “It’s a combination of probably what we were seeing from looking at these physics-based models and some of the inconsistency there, and then just the performance of the AI guidance so far, and the fact that it has proven to be pretty reliable,” Brennan said. Part of that proof came from a gutsy call that the Hurricane Center forecasters made last year during Hurricane Melissa. Last season, in a first, Hurricane Center forecasters explicitly forecast that Hurricane Melissa would reach Category 5 intensity when it was just an 80-mph Category 1 hurricane, largely by relying on the clear projections from DeepMind. In fact, by some measures, DeepMind even outperformed human forecasters during the 2025 Atlantic hurricane season overall. With global climate change enabling more tropical cyclones to rapidly intensify, the Hurricane Center has been making more bullish first forecasts for certain storms, including Isaias. Before AI stepped onto the forecasting stage, the NHC had employed more of a stair-step approach, gradually raising the intensity ceiling of a storm as it revved up, which often put the official forecasts behind the curve. That practice seems to have ended. Rapidly intensifying storms are now more common, and the latest models are better able to anticipate it. “We’ve definitely been making more aggressive intensity forecasts overall for the last several years, and we certainly do have more confidence to try to make some of these more aggressive intensity forecasts early on, like we did for Melissa last year, but we’ve also done for Helene and Milton,” Brennan said. He cited physical computer model support for rapid intensification plus weather forecasters’ understanding of the environment in which a storm is forming as additional factors allowing early predictions of rapid intensification. “It’s not just one thing, but certainly the AI models have done pretty well in some of those cases,” Brennan said. “So it’s another tool in the toolbox, so to speak, or another piece of evidence that can help support those more aggressive intensity forecasts,” he said of the AI models. Brennan said forecasters are not skittish about relying on DeepMind in part because they know the training data that went into it. “I think the most important thing is to make sure that the models are trained on the most accurate data we have,” he said, “and we’ve worked with Google to help them train on our best track analysis, and that’s one reason why I think their performance has improved in terms of intensity forecasting relative to some of the earlier AI models that did well for track, but did not do well for intensity.” Those models had been trained on large-scale data sets that weren’t hurricane-specific, he said. Meanwhile, Hurricane Isaias is churning its way toward the northeastern Gulf Coast and is likely to make landfall as a hurricane, according to a consensus of most computer models — not just DeepMind.