GenCast, an AI weather program from Google DeepMind, performed up to 20% better than the ENS forecast from the European Centre for Medium-Range Weather Forecasts (ECMWF), widely regarded as the world leader.
In the near term, GenCast is expected to support traditional forecasts rather than replace them, but even in an assistive capacity it could provide clarity around future cold blasts, heatwaves and high winds, and help energy companies predict how much power they will generate from windfarms.
In a head-to-head comparison, the program churned out more accurate forecasts than ENS on day-to-day weather and extreme events up to 15 days in advance, and was better at predicting the paths of destructive hurricanes and other tropical cyclones, including where they would make landfall.
"Outperforming ENS marks something of an inflection point in the advance of AI for weather prediction," said Ilan Price, a research scientist at Google DeepMind. "At least in the short term, these models are going to accompany and be alongside existing, traditional approaches."
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