Methods for Snowpack Data Acquisition and Characterization

Abstract

This research focuses on improving and creating technologies that aid in making decisions about snowpack stability. First, different methods for extracting the temperature of the snow as a function of depth are explored. The temperature of the snow at different depths is important in predicting how layers of snow change overtime. Second, an existing snowpack data-accquisition probe is used to build two predictive models. The first model predicts the dominate grain type of the snow in each layer of the snowpack, and the second model predicts the result of a common snowpack stability test. Advancements in technologies like these are essential in improving avalanche forecasting ability and in making real-time judgements about the avalanche probability on a given slope.