Savanna Wolvin

Savanna Wolvin is a Ph.D. student in the Atmospheric Sciences Department of the University of Utah. Her dissertation aims to improve precipitation and temperature predictions through statistical downscaling with machine learning. Downscaling is essential to producing high-spatial-resolution data desired for forecasts and to support research in other earth science disciplines. Her research utilizes the relationship of precipitation and temperature with elevation in complex terrain, predicted using a convolutional neural network. Her research interests include mountain meteorology, statistical modeling, machine learning, and climate variability. Savanna previously completed a B.S. in Meteorology from St. Cloud State University. At the University of Utah, she completed an Interdisciplinary Graduate Certificate in Hydrology and Water Resources and an M.S. in Atmospheric Sciences.