Abstract: The evolution of snow is an important area of research for a number of applications, such as altimetry-derived mass loss predictions from the ice sheets, calculations of the age difference between the ice and air for ice-core interpretations, glacier volume storage approximations for water resource assessments, vehicular tire-terrain interactions, and avalanche mechanics. The most common snow-compaction models used are empirical and show considerable spread in output. Models with different frameworks, such as from microstructural analysis, exist but often also involve some rigor of calibration. For universal application, large datasets over spatial and temporal ranges with assumptions of the climatic influence on snow and firn are necessary, as well as the dominant feedbacks that govern compaction. Therefore, broadly, there exists a need to:

1. explore building snow-compaction models using non-empirical frameworks, and
2. understand the relationships between compaction and microstructure.

The thesis here targets specific topics within these areas through numerical and experimental methods by investigating snow-compaction modeling through a two-phase modeling with a continuum framework (Chapter 1); analyzing microstructural evolution through uniaxial compression using micro-CT analysis (Chapter 2); exploring microstructure from extreme metamorphism and the influence of near-surface processes (Chapter 3); and using micro-CT data to estimate permeability through pore-network modeling (Chapter 4).

Thesis Committee: Zoe Courville (chair), Mary Albert, Helen Seroussi, and Kaitlin Keegan (UNR)