Abstract
Liquid water plays a major role in warming the snowpack, providing both advective heat transport as it percolates and latent heat release when it refreezes. As liquid water percolates through the snow, snow grains and snowpack structures are modified, creating complex liquid water pathways that are difficult to model and capture without dye trace experiments and snow pits. Previous studies have used thermistor installation to study the warming and infiltration of liquid water in firn and snowpacks of less than 2 m. Here, I present a two-year Spring season (2021 and 2022) snow temperature data collected by multiple installations of thermistors within a 6 m-thick maritime snowpack on Wolverine Glacier in the Kenai Peninsula, Alaska. This thesis aims to capture the spatial and temporal variability of snowpack warming and the infiltration of snow meltwater into the Spring snowpack. In addition, presenting a one-dimensional diffusion model that can infer the radius of the water pipes and the spacing between pipes using direct snow temperature measurements.In both years, two distinct warming and infiltration patterns were captured between the installation date (May 13, 2021, and April 28, 2022) and the snowpack becoming isothermal (3 weeks 4 days after installation). The first pattern was progressive warming from the top-down. The second pattern was a ‘skipping’ pattern, where deeper depths warmed up quicker. This suggests preferential flow bypassing part of the snowpack, then pooling and refreezing at greater depths with the associated release of latent heat. Through the one-dimensional diffusion, the radius of the pipe and spacing between pipes were inferred, providing estimates of a pipe radius of around 3 cm and spacing of 1 m, similar to observations found in previous field observations.