Combining AI and Analog Forecasting to Predict Extreme Weather - Eos

The future of extreme weather prediction may lie in modernizing a piece of technology from the past. Researchers recently developed a new technique to augment an old-fashioned weather forecasting method with the power of deep learning, a subset of artificial intelligence (AI). Once the deep learning system is fully trained, it is able to predict extreme weather events like heat waves and cold spells with 80% accuracy up to 5 days beforehand. "This is a very inexpensive way of predicting extreme events at least a few days ahead of time," said Ashesh Chattopadhyay, a mechanical engineering graduate student at Rice University in Houston and lead author on the project. The project began when Pedram Hassanzadeh, an assistant professor of mechanical engineering at Rice, realized that extreme weather events like heat waves and cold spells usually arise from very unusual atmospheric circulation patterns that could potentially be taught to a pattern recognition computer program.