Washington, D.C. — Federal researchers are turning to artificial intelligence in hopes of improving how quickly and accurately weather forecasts are made across the United States.
The National Oceanic and Atmospheric Administration (NOAA), in partnership with the National Weather Service and the Earth Prediction Innovation Center, recently unveiled Project EAGLE, a new experimental platform designed to integrate AI into weather prediction models.
According to NOAA, Project EAGLE will allow scientists and researchers both inside and outside the agency to test and demonstrate new AI-powered forecasting tools against NOAA’s existing systems. The initiative aims to reduce the time it takes to develop models, cut computing costs, and ultimately provide the public with more reliable forecasts.
“Traditional weather models can take years to develop and require expensive supercomputers,” said Sergey Frolov, Chief Scientist for Project EAGLE. “AI models can significantly shorten development timelines and open the door to innovative ways of predicting the weather.”
Project EAGLE is expected to provide what NOAA calls a research-to-operations pipeline, allowing experimental models to move into real-world use more quickly. It will also give scientists, universities, and private companies a platform to train and test forecasting systems in an open environment.
The first version of EAGLE will include two test settings: one for single deterministic forecasts and another for ensemble models, which provide multiple possible outcomes. Future plans include integrating NOAA’s high-resolution Rapid Refresh forecast model, expanding training data, and collaborating with European weather agencies.
NOAA officials say the long-term goal is for Project EAGLE to become a cornerstone of the nation’s forecasting operations, ensuring faster warnings and more precise predictions for communities across the country.
This article was produced by a journalist and may include AI-assisted input. All content is reviewed for accuracy and fairness.
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