Microsoft has introduced Aurora, a new AI model designed to predict weather events like air quality, hurricanes, typhoons, and other atmospheric phenomena with high accuracy. According to a recent paper published in Nature and a company blog post, Aurora offers faster and more precise forecasts compared to traditional weather prediction methods.
Aurora has been trained on an extensive dataset comprising over a million hours of information from satellites, radar, weather stations, simulations, and prior forecasts. This vast training enables the model to be fine-tuned for specific weather conditions and events, improving its forecasting capabilities.
While AI weather prediction isn’t a novel idea—Google DeepMind has developed several models, including WeatherNext, which is known for outperforming many top forecasting systems—Microsoft positions Aurora as a leading contender in this space. The company highlights Aurora’s potential to advance weather science and assist research labs worldwide.
In practical tests, Aurora accurately predicted the landfall of Typhoon Doksuri in the Philippines four days before it happened, outperforming some expert forecasts. It also surpassed the National Hurricane Center’s five-day tropical cyclone track predictions during the 2022-2023 season and correctly forecasted a major sandstorm in Iraq in 2022.
Despite requiring significant computing resources for its initial training, Aurora is highly efficient during use. It generates forecasts in seconds, whereas traditional systems often need hours on supercomputers. This efficiency makes it practical for real-time weather prediction applications.
Microsoft has made Aurora’s source code and model weights publicly accessible, encouraging further development and adoption. Additionally, a tailored version of Aurora is already integrated into Microsoft’s MSN Weather app, providing hourly weather updates, including cloud coverage forecasts, to users.
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