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The Greenland Ice Sheet is now the single largest cryospheric contributor to global sea-level rise yet uncertainty remains about its future contribution due to complex interactions between increasing snowfall and surface melt. Reducing uncertainty in future snowfall predictions requires sophisticated, physically based climate models evaluated with present-day observations. The accuracy of modeled snowfall rates, however, has yet to be systematically assessed because observations are sparse. Here, we produce high spatial resolution (15 km) snowfall climatologies (2006–2016) derived from CloudSat's 2C-SNOW-PROFILE product to evaluate climate model simulations of snowfall across the Greenland Ice Sheet. In comparison to accumulation datasets acquired from ice cores and airborne accumulation radar, we find that our CloudSat climatologies capture broad spatial patterns of snowfall in both the accumulation and ablation zones. By comparing our CloudSat snowfall climatologies with the Regional Atmospheric Climate Model Version 2.3p2 (RACMO2.3p2), Modèle Atmosphérique Régional 3.9 (MAR3.9), ERA5, and Community Earth System Model version 1 (CESM1), we demonstrate that climate models likely overestimate snowfall rates at the margins of the ice sheet, particularly in South, Southeast, and Northwest Greenland during autumn and winter. Despite this overestimation, there are few areas of the ice sheet where the models and CloudSat substantially disagree about the spatial pattern and seasonality of snowfall rates. We conclude that a combination of CloudSat snowfall observations and the latest generation of climate models has the potential to improve understanding of how snowfall rates respond to increasing air temperatures, thereby constraining one of the largest sources of uncertainty in Greenland's future contribution to global sea levels.

Supraglacial lakes forming and draining on the Greenland are particularly important for understanding the hydrologic control on flow due to their ability to rapidly transport water to the base of the ice sheet and induce basal sliding (Das et al., 2008). In the past decade, numerous studies have mapped supraglacial lakes using remotely sensed imagery and noted a steady inland progression of lakes coincident with increasing melt (Fitzpatrick et al., 2014; Howat et al., 2013). However, there remains significant uncertainty in this progression, particularly in regards to the impact of observational bias on lake detection (Leeson et al., 2013) and possible physical altitudinal limits to inland expansion of lakes and rapid drainage events (Poinar et al., 2015). The aim of this dissertation is to examine patterns in inland expansion and rapid drainage frequency through an analysis of supraglacial lake processes in central West Greenland from 2000-2015. Using a fully automated lake detection approach adapted from Liang et al. (2012), ~515 supraglacial lakes per year are mapped over a 63,000 km2 study area. In high melt years, lakes form and disappear earlier and a greater number of lakes appear on the ice sheet as lakes extend to higher elevations. Strong positive trends in the number of lakes, cumulative surface water loss and maximum lake elevation are also identified over the 16-year record. Comparison of different methods of rapid drainage detection from previous studies reveals the percent of lakes detected as rapidly draining varies from 3% to 38% depending on how rapid drainage is defined and indicates that the number of rapid drainage events is strongly dependent on the frequency of cloud-free lake observations. Statistical analysis of this observation bias in rapid drainage detection suggests a true rapid drainage probability between 0.36 and 0.45, which is considerably higher than previous studies have reported. Finally, no evidence is found to support a physical altitudinal limit on inland expansion of rapid drainage events, suggesting rapid drainage events will continue to move inland as the climate warms and thus may propagate basal sliding-induced mass loss to higher elevations.

Rapid drainage of supraglacial lakes on the Greenland Ice Sheet enables the establishment of surface-to-bed hydrologic connections and subsequent basal water delivery. Estimates of the number and spatial distribution of rapidly draining lakes vary widely, and no study has quantified the impact of observation bias due to cloud cover in satellite imagery on reported frequency of rapid lake drainage. To better understand the rapid drainage mechanism, we map and track an average of 515 supraglacial lakes per year in central West Greenland from 2000-2015. We test four previously published definitions of rapid lake drainage and find the proportion of rapidly draining lakes to vary from 3% to 38% and to be strongly dependent on observation frequency. We then apply an observation bias correction and test three new drainage criteria, which reveal a bias corrected rapid drainage probability of 36-45%. When observation bias is addressed, we can also show that lakes above 1600m are as likely to drain rapidly as lakes located at lower elevations. We conclude that inconsistent detection methodologies and observation bias have obscured the true frequency of rapidly draining lakes, and that the rapid lake drainage mechanism will establish surface-to-bed hydrologic connections at increasing distance from the margin as supraglacial lakes expand inland under climate warming.