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Academic Lectures
AMS Colloquium, Friday 9/12/25 at 3pm Chauvenet Hall 143
Department / Organization: AMS
Speaker: Dr. Adrienne Marshall, Colorado School of Mines
Title: From Descriptive Statistics to Machine Learning: Applications of Applied Math and Statistics in Snow Hydrology and Climate
Abstract: Mountainous snowpacks are essential to providing water resources, sustaining aquatic and terrestrial ecosystem function, and moderating climate feedbacks. Yet snow is also sensitive to climate change. Understanding the impacts of climate change on snow over the historic record through future projections is therefore key to identifying climate impacts and potential adaptation strategies. We have a suite of observational and modeled snow data products that facilitate scientific inquiry in this area, but heterogeneous spatial and temporal scales of these data products necessitate creative quantitative approaches to their application. Here, I will discuss past and ongoing research that uses applied math and statistics to investigate the impacts of climate change on snow. Mathematical approaches range in complexity from the creative use of descriptive statistics to new applications of machine learning. Applications span questions about climate impacts on snow drought frequency, impacts of changing snowfall intensity, and changes in snow accumulation and melt dynamics in burned forests. I aim to illustrate the ways that math can be applied in snow and climate studies, and point towards future opportunities for collaboration and synergy among these disciplines.
