Drs. Ashley Payne (Climate and Space Sciences and Engineering), Yulin Pan (Naval Architecture and Marine Engineering) and the team use data science methods to improve the forecast of hydrological extremes (such as unprecedented floods). They use predictive modeling to select informative satellite remote sensing data, then use new data to improve model predictions. They will demonstrate these methods through the forecast of a class of phenomena known as atmospheric rivers that are related to hydrologic and wind extremes, and the replenishment of water resources.
Student will be presenting two case studies of the downstream effect of atmospheric rivers over the central US on numerical weather prediction forecasts downstream in the UK at the American Geophysical Union Annual Meeting in December
The team plans to submit a proposal based on this project to NASA’s CYGNSS Competed Science Team solicitation in the fall