New AI systems could speed up our ability to create weather forecasts

The first, developed by Huawei, details how its new AI model, Pangu-Weather, can predict weekly weather patterns around the world much more quickly than traditional forecasting methods, but with comparable accuracy. The second demonstrates how a deep-learning algorithm was able to predict extreme rainfall more accurately and with more notice than other leading methods, ranking first around 70% of the time in tests against similar existing systems. If adopted, these models could be used alongside conventional weather predicting methods to improve authorities' ability to prepare for bad weather, says Lingxi Xie, a senior researcher at Huawei. To build Pangu-Weather, researchers at Huawei built a deep neural network trained on 39 years of reanalysis data, which combines historical weather observations with modern models. Unlike conventional methods that analyze weather variables one at a time, which could take hours, Pangu-Weather is able to analyze all of them at the same time in mere seconds.