Microsoft says its latest AI system, Aurora, can predict typhoons, hurricanes, sandstorms, and air quality events more accurately and significantly faster than traditional forecasting methods, according to a new research paper and blog post released this week.
The company published details of the Aurora model in Nature, citing major improvements in forecast accuracy and efficiency.
Trained on more than a million hours of satellite, radar, and ground station data, Aurora is designed to anticipate atmospheric events across the globe and can be fine-tuned for specific weather scenarios.
A new paper published in Nature explains how Microsoft’s Aurora AI foundation model goes beyond weather forecasting to more accurately predict a range of environmental events, from hurricanes and typhoons to air quality and ocean waves. https://t.co/zTEg0Lw9Qs
— Microsoft Research (@MSFTResearch) May 21, 2025
In tests, Microsoft says Aurora predicted the landfall of Typhoon Doksuri in the Philippines four days in advance — outperforming several expert forecasts.
The model also outpaced the US National Hurricane Center in tracking tropical cyclones over the 2022–2023 season and correctly anticipated a major sandstorm in Iraq in 2022.
While AI-based weather forecasting is not new — Google DeepMind’s WeatherNext is another example — Microsoft positions Aurora as among the most advanced models publicly available.
The company has also released Aurora’s source code and model weights, opening it to researchers and developers.
Microsoft reports that, despite its large training set and the infrastructure required to build it, Aurora runs highly efficiently.
Forecasts are generated in seconds, compared to hours required by legacy supercomputer-based systems.
A specialised version of the model will be integrated into Microsoft’s MSN Weather app, providing hourly updates and cloud forecasts.
The development is seen as a potential game-changer for meteorologists and climate scientists, offering faster and possibly more accurate tools for understanding extreme weather patterns and air quality.
