Oceanic and Atmospheric Research (OAR) - or NOAA Research - provides the research foundation for understanding the complex systems that support our planet.
NOAA Research develops an AI-powered sibling to its flagship weather modelHRRR-Cast output showing simulated reflectivity and wind particles over the contiguous-U.S. domain for a line of strong thunderstorms that occurred May 6, 2024. This image was created using GSL’s DESI tool. Image credit: NOAA/GSLNOAA’s pioneering High Resolution Rapid Refresh short-term weather forecast model, known as the HRRR, will soon be joined by an experimental, AI-powered sibling.
This panel displays from left to right, the operational HRRR Composite Reflectivity forecast for a line of thunderstorms sweeping across the central United States, initialized at 2300 UTC on May 6, 2024, followed by experimental HRRR-Cast forecast and the HRRR analysis of radar observations from the event. Credit: NOAA Global Systems Laboratory
“By leveraging new, high-resolution observations that help us better understand fine-scale physical processes, physical models can be improved, thereby improving the data on which AI-driven models are trained,” Jankov said. She added that her fellow researchers believe that the future of forecasting lies with a hybrid approach using both physical and data-driven models to take advantage of the gains in computational efficiency that AI techniques provide.
One big difference: HRRR-Cast is 100 to 1000 times more computationally efficient than the operational HRRR, which allows HRRR-Cast to be run without the need for a supercomputer.
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