Deep Learning Accurately Forecasts Heat Waves, Cold Spells

Rice University engineers have created a deep learning computer system that taught itself to accurately predict extreme weather events, like heat waves, up to five days in advance using minimal information about current weather conditions. Ironically, Rice's self-learning "capsule neural network" uses an analog method of weather forecasting that computers made obsolete in the 1950s. During training, it examines hundreds of pairs of maps. Each map shows surface temperatures and air pressures at five-kilometers height, and each pair shows those conditions several days apart. The training includes scenarios that produced extreme weather -- extended hot and cold spells that can lead to deadly heat waves and winter storms.