A group of students led by professors of climate sciences and stochastic analysis will use climate models to improve the projected rainfall over the southeastern United States. Students will learn about the climate processes that influence precipitation, flooding, and droughts, as well as how to improve model capability to predict water cycles. Students will develop Bayesian statistical models to reduce the uncertainty in future rainfall projections. This economical and effective method of optimizing future climate projections could provide practical approaches to addressing damages and losses caused by climate change.
Project Lead: Yan Pan