Interseasonal Prediction of Western United States Snowpack with Deep Learning

Gemma Anderson | 19-ERD-032

Executive Summary

During this project, we will train a deep neural network on 40 years of observational data supplemented with high-resolution model data to better understand the underlying physical processes of the snowpack in the Western United States. The resulting state-of-the-art deep-learning computational tools will improve snowpack predictions that look six to ten months in advance, enabling water resource managers to plan for the year ahead.