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Item Thermal contact resistance at the snow-ice interface: dependence on grain size(Montana State University - Bozeman, College of Engineering, 2022) Dvorsak, Michael Alan; Chairperson, Graduate Committee: Kevin HammondsSeasonal snow covers consist of many stratigraphic layers of varying density and, therefore, thermal conductivity. Weak layers can develop at the interface between these snow layers, reducing stability and increasing avalanche danger. While it is known that a bulk temperature gradient of -10?C m -1 across a snowpack enhances weak layer development via kinetic snow metamorphism, recent studies have identified an enhancement of this temperature gradient across snow interfaces. Previous work has determined that at a snow-ice interface, such as might exist around ice crusts in the snowpack, the driving factor for a temperature gradient enhancement could be a thermal contact resistance. This creates an interfacial phenomenon that induces a large temperature drop at the interface between two connected materials. The primary mechanism is a reduction of contact area for conduction to occur due to the porous nature of snow. Here, we further investigate the thermodynamics of a snow-ice interface by varying the grain size, which directly correlates to the total contact area. Within a controlled laboratory environment, a 4 mm ice lens was artificially made and placed between rounded grains that varied in size (1, 2, and 3 mm) between experiments. Temperature gradients of -10, -50, and -100 ?C m -1 were then applied across the sample. The temperature gradient was measured in-situ within 1 mm of the ice lens using micro-thermocouple measurements. The local temperature gradient at the snowice interface was found to be up to four times the imposed temperature gradient with 2-3 mm snow grains and near the bulk temperature gradient with the 1 mm grains. Following a thermal analysis, it was concluded that the enhancement in the temperature gradient was also due to a thermal contact resistance at the snow-ice interface. Utilizing timelapse x-ray computed microtomography, a microstructural characterization of the snow-ice interface was also performed, where it was observed that new ice crystal growth, kinetic snow metamorphism, and sublimation were all occurring simultaneously near the ice lens. These results indicate that the observed grain size near an ice lens or crust in a natural snowpack may be a pertinent parameter for better understanding kinetic snow metamorphism regimes that may exist at these interfaces.Item Remote sensing of wet snow processes in a controlled laboratory environment(Montana State University - Bozeman, College of Engineering, 2022) Donahue, Christopher Paul; Chairperson, Graduate Committee: Kevin Hammonds; This is a manuscript style paper that includes co-authored chapters.Water flow through snow, due to snowmelt or rain-on-snow events, is a heterogeneous process that has implications for snowmelt timing and magnitude, snow metamorphism, albedo evolution, and avalanche hazard. Remote sensing technologies, ranging from ground-based to satellite-borne scales, offer a non-destructive method for monitoring seasonal snowpacks, although there is no single technique that is ideal for monitoring snow. Wet snow, specifically, presents a challenge to both optical and radar remote sensing retrievals. The primary aim of this dissertation was to develop wet snow remote sensing methods from within a controlled laboratory environment, allowing for precise characterization of snow properties. Experiments were conducted by preparing laboratory snow samples of prescribed structures and monitoring them during and after melt using hyperspectral imaging and polarimetric radar. Snow properties were characterized using X-ray computed microtomography, a dielectric liquid water content sensor, and serial-section reconstructions. In addition to laboratory experiments, hyperspectral imaging snow property retrieval methods were developed and tested in the field during wet snow conditions at the ground-based scale. The primary outcomes from this work were three new remote sensing applications for monitoring wet snow processes. First, a new hyperspectral imaging method to map effective snow grain size was developed and used to quantify grain growth due to wet snow metamorphism. Second, the optimal radiative transfer mixing model to simulate wet snow reflectance was determined and used to map liquid water content in snow in 2- and 3- dimensions. Lastly, snow melt progression was monitored using continuous upward-looking polarimetric radar and it was found, by comparison to 3-dimensional liquid water content retrievals from hyperspectral imaging, that the cross-polarized radar signal was sensitive to the presence of preferential flow paths. The work presented here highlights the utility of using a multi-sensor fusion approach to snow remote sensing. Although these laboratory remote sensing experiments were at a small scale, the remote sensing instrument response to specific snow conditions directly translates to larger scales, which is valuable to support algorithm development for ground, airborne, and spaceborne remote sensing missions.