Circum-Arctic Glaciers, Past, Present, and Future: Current Trends in Mass Balance and Simulation of Mass Balance Sensitivity to Temperature and Precipitation Increase

The circum-Arctic is a major contributor to sea level rise. Between 1991 and 2010, 70 % of eustatic sea level rise was attributable to glacier mass loss, 62 % of which was from glaciers in the circum-Arctic (Alaska, Arctic Canada North, Iceland, Svalbard, Scandinavia, and the Russian Arctic). In addition, Arctic temperatures are expected to increase at 2.4 times the magnitude of projected global average warming over the next 100 years. An understanding of how circum-Arctic glaciers are responding to temperature increase, and how they will respond under future climate conditions, is crucial to helping island nations and low-lying coastal communities predict and mitigate the impacts of sea level rise. This thesis has two objectives. The first objective is to a) identify the most effective methodology to calculate regional mass balance trends in the circum-Arctic using spatially and temporally sparse datasets and b) use these data to determine past and present (1961-2016) circum-Arctic mass balance trends. To accomplish this, I explore spatially interpolated mass balance from prior studies and compare these results to specific mass balance calculated using only observational data. I then compare two different time periods from the specific mass balance dataset (1961-2016 and 2000-2016) to determine regional mass balance trends. I find that mass balance calculated through spatial interpolation and specific mass balance are statistically likely to derive from the same population in regions that contain observational mass balance data. However, qualitatively, the variability between the datasets appears to be different for regions in which ≥50 % of observational data are geodetic. In addition, the mean magnitude of mass loss appears different in glacier regions with only high-variability glaciological mass balance data. A comparison of 1961-2016 and 2000-2016 mean specific mass balance in each region determines that glacier mass balance in Arctic Canada North has decreased at the largest rate, followed by Alaska and Svalbard (-0.20, -0.14, and -0.12 m w.e. a-1, respectively). The second objective of this thesis is to: a) determine the circum-Arctic glacier mass balance sensitivity temperature and precipitation increase and then b) investigate the factors driving the sensitivity. To achieve this objective, I use a degree-day model (the Python Glacier Evolution Model, PyGEM) to simulate circum-Arctic mass balance sensitivity to 1-3 °C temperature and 4%°C-1precipitation increase between 2000 and 2100. The model simulations suggest that Iceland glaciers are the most sensitive to temperature and precipitation increase (-0.70 m w.e. a-1 °C -1) of all regions studied, and Arctic Canada North is the least sensitive (-0.39 m w.e. a-1 °C -1). These results suggest that the degree of continentality (how warm/wet a region is) and the proximity of accumulation season temperatures (the rain/snow threshold) is the primary driver of mass balance sensitivity; warm, wet, ‘maritime’ regions (Iceland, Scandinavia) are more sensitive to the same temperature increase than cold, dry, ‘continental’ regions (Arctic Canada North, the Russian Arctic). Secondary factors such as glacier size, altitude, slope, and surface albedo may also impact regional glacier mass balance sensitivity. Small glacier size, low glacier altitude, large surface albedo, and steep glacier slope may increase mass balance sensitivity, while large glacier size, high glacier altitude, small surface albedo, and slight glacier slope may decrease mass balance sensitivity. Overall, the results of this thesis provide incentive for future data collection in rapidly changing regions like Arctic Canada North, and provides a better understanding of how the circum-Arctic may change in response to future climate change.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.