AI can make storm warnings faster and more accurate, researchers say
In a paper published by the journal Nature, Microsoft researchers claimed that the company's Aurora AI model "outperforms operational forecasts in predicting air quality, ocean waves, tropical cyclone tracks and high-resolution weather, all at orders of magnitude lower computational cost."
Microsoft stated that the system was "trained on more than one million hours of diverse geophysical data" - enough information to enable it "more accurately predict not just the weather, but a wide range of environmental events in a series of retrospective analyses," including, hurricanes, typhoons and ocean waves
Meanwhile, a team from the US government's National Oceanic and Atmospheric Administration (NOAA) and the University of Oklahoma said that a prediction model they created using Google DeepMind's Graphcast tool could be 10 times faster at predicting storms than previous computer-based platforms.
The researchers "trained" the Google platform on data from NOAA's Warn-on-Forecast-System (WOFS), creating an AI variant called WOFSCast that shortens forecast times from minutes to seconds.
"The model yielded largely accurate predictions of how storms would evolve for up to 2 hours; these predictions matched 70% to 80% of those generated by the Warn-on-Forecast system," according to the American Geophysical Union, which published the NOAA/Oklahoma findings its Geophysical Researh Letters journal.
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