Aurora, a foundation model for the Earth system

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Summary

Weather forecasters rely on models to help them make decisions that can have life-or-death consequences, so any advantage is welcome. Artificial intelligence holds promise to deliver more accurate forecasts quickly, and tech companies including Google, Nvidia and Huawei have produced A.I.-based forecasting models.The latest entrant is Aurora, an A.I. weather model from Microsoft, and it stands out for several reasons, according to a report published Wednesday in the journal Nature. It’s already in use at one of Europe’s largest weather centers, where it’s running alongside other traditional and A.I.-based models.The Aurora model can make accurate 10-day forecasts at smaller scales than many other models, the paper reports.And it was built to handle not only weather, but also any Earth system with data available. That means it can be trained, relatively easily, to forecast things like air pollution and wave height in addition to weather events like tropical cyclones. Users could add almost any system they like down the road; for instance, one start-up has already honed the model to predict renewable energy markets.“I’m most excited to see the adoption of this model as a blueprint that can add more Earth systems to the prediction pipeline,” said Paris Perdikaris, a professor at the University of Pennsylvania who led the development of Aurora while working at Microsoft.It’s also fast, able to return results in seconds as opposed to the hours that non-A.I. models can take.Traditional models, the basis of weather forecasting over the last 70 years, use layers of complex mathematical equations to represent the physical world: the sun heating the planet, winds and ocean currents swirling around the globe, clouds forming, and so on.Researchers then add real weather data and ask the computer models to predict what will happen next. Human forecasters look at results from many of these models and combine those with their own experience to tell the public what scenario is most ...

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