This dissertation investigates winter accumulation and snow cover change in the Columbia Mountains of British Columbia. In chapter 1, I start with an introduction that describes the study area, and then outlines the objectives and structure of this dissertation. In chapter 2, I examine the performance of two snow evolution models with different complexities (SnowModel and Alpine3D) at simulating winter glacier mass balance on four individual glaciers using two different forcing datasets, the Weather Research and Forecasting model (WRF) outputs and the North American Land Data Assimilation System (NLDAS). My results show that both models can simulate winter accumulation with less than 20% bias for each glacier, with SnowModel forced by WRF yielding the least overall bias. In chapter 3, I study the effect of wind on snow patterns to determine the impact of snow redistribution by wind in terms of erosion, deposition, and sublimation on winter mass balance estimation. The results demonstrate that modelled redistribution of snow by wind produces a visually realistic pattern of snow accumulation when compared to observed snow depth, but its impact on the glacier-averaged winter mass balance estimation is negligible (< 4%). The results also suggest that drifting snow sublimation is highly time and space dependent. Considering the model performance from previous chapters, in chapter 4, I analyzed the future snow cover change over the upper Columbia Basin under the Representative Concentration Pathway (RCP8.5) climate scenario by the end of the 21st century. I used downscaled climate projections of the Community Earth System Model (CESM1) by WRF, along with statistically downscaled data provided from the Pacific Climate Impacts Consortium (PCIC) to force SnowModel. The simulated snow maps represent a higher dynamically downscaled mean snow water equivalent (SWE) reduction – reaching up to 30% by the end of the century - than the statistically downscaled SWE reduction. While SWE reduction of more than 60% happens at lower and mid-elevations, altitudes higher than 2000 m are less vulnerable to climate change. I conclude this dissertation (Chapter 5) with a summary of the progress gained, study limitations, suggestions for future research, and research implications.
