Quantum Computing Approach for Predicting Extreme Atmospheric Events

This project will explore the feasibility of using quantum computing to help predict extreme atmospheric events including floods, tsunamis, storms and turbulent atmospheric bursts. This project combines quantum information science and geophysical fluid dynamics, two communities that rarely interact. The project will also train an essential quantum-researcher workforce at the intersection of quantum computing, fluid dynamics, and machine learning. Providing better forecasting would have a direct benefit for public-safety value. Prediction of extreme atmospheric events—heat waves, flash floods, blocking-driven precipitation extremes remains challenging: classical numerical weather prediction faces prohibitive ensemble costs when the goal is to capture rare, high-amplitude events, and data- driven models trained on mean-squared-error losses systematically underpredict them. This project would explore whether Quantum Reservoir Computing (QRC) can provide a genuine computational advantage for extreme-event prediction when the target system is described by shallow water equations on the rotating sphere. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.