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NHC uses Google DeepMind AI after it beat track models on Isaias
NPR reports National Hurricane Center forecasters now blend Google DeepMind's AI with physics models after it outperformed traditional track forecasts on Hurricane Isaias in October.
- New headline Was: “How AI is transforming hurricane forecasts”
- Our desk filed its story
Based on reporting by NPR
National Hurricane Center forecasters are using artificial intelligence alongside traditional computer models, according to a WUSF report carried by NPR on Monday1.
The report said Hurricane Isaias made landfall near Destin, Florida, as a Category 2 storm in early October, after conventional models had initially pointed farther west toward southeastern Louisiana1.
Google DeepMind's weather model indicated a western Florida Panhandle landfall from the start, the report said, citing Miami meteorologist Michael Lowry, a former adviser to FEMA and the NHC1.
NPR said the NHC began using the DeepMind model in official forecasts last year and that University of Miami researcher Brian McNoldy called it among the best path-and-intensity tools by the end of the 2025 Atlantic season1.
Unlike physics-based models that solve atmospheric equations from satellite and aircraft data, AI systems match patterns in past storms, Lowry told NPR, which can leave forecasters unsure why a run is right or wrong1.
NHC Director Michael Brennan told NPR the center uses a consensus of proven AI and traditional models, with humans issuing updates every six hours so the public sees continuity rather than jumpy raw output1.
Brennan said DeepMind led on Isaias's track but lagged the NHC blend on intensity, and that his staff sends regular feedback; NPR said Google did not answer questions for the story1.
Lowry told NPR that AI skill can jump in months where older models took years, and that he does not see the tools replacing human forecasters1.
