So-called “100-year weather events” now seem almost commonplace as floods, storms and fires continue to set new standards for largest, strongest and most destructive.
So-called “100-year weather events” now seem almost commonplace as floods, storms and fires continue to set new standards for largest, strongest and most destructive. But to categorize weather as a true 100-year event, there must be just a 1% chance of it occurring in any given year. The trouble is that researchers don’t always know whether the weather aligns with the current climate or defies the odds.
Traditional weather forecasting models run on energy-hogging supercomputers that are typically housed at large research institutions. In the past five years, artificial intelligence has emerged as a powerful tool for cheaper, faster forecasting, but most AI-powered models can only accurately forecast 10 days into the future. Still, longer-range forecasts are critical for climate science — and helping people prepare for seasons to come.
In a new study published on Aug. 25 in AGU Advances, University of Washington researchers used AI to simulate the Earth’s current climate and interannual variability for up to 1,000 years. The model runs on a single processor and takes just 12 hours to generate a forecast. On a state-of-the-art supercomputer, the same simulation would take approximately 90 days.
Read more at: University of Washington
The new AI model from Dale Durran, University of Washington professor of atmospheric and climate science, and graduate student Nathaniel Cresswell-Clay, simulates up to 1000 years of the current climate using less computing power than conventional methods. It captures atmospheric conditions like the low pressure system over the central US pictured above. (Photo Credit: NASA Earth Observing System/Interdisciplinary Science (IDS) program under the Earth Science Enterprise)
