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This paper presents a physics-based macroscale model for the densification of dry snow which provides for a smooth transition between densification by grain-boundary sliding (stage 1) and densification by power-law creep (stage 2). The model uses established values of the stage 1 and 2 densification rates away from the transition zone and two transition parameters with a simple physical basis: the transition density and the half-width of the transition zone. It has been calibrated using density profiles from the SUMup database and physically based expressions for the transition parameters have been derived. The transition model produces better predictions of the depth of the nominal bubble close-off horizon than the Herron and Langway model, both in its classical form and in a recent version with re-optimised densification rates.

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.

Since the year 2000, Greenland ice sheet mass loss has been dominated by a decrease in surface mass balance rather than an increase in solid ice discharge. Southeast Greenland is an important region to understand how high accumulation rates can offset increasing Greenland ice sheet meltwater runoff. To that end, we derive a new 9-year long dataset (2009–17) of accumulation rates in Southeast Greenland using NASA Operation IceBridge snow radar. Our accumulation dataset derived from internal layers focuses on high elevations (1500–3000 m) because at lower elevations meltwater percolation obscured internal layer structure. The uncertainty of the radar-derived accumulation rates is 11% [using Firn Densification Model (FDM) density profiles] and the average accumulation rate ranges from 0.5 to 1.2 m w.e. With our observations spanning almost a decade, we find large inter-annual variability, but no significant trend. Accumulation rates are compared with output from two regional climate models (RCMs), MAR and RACMO2. This comparison shows that the models are underestimating accumulation in Southeast Greenland and the models misrepresent spatial heterogeneity due to an orographically forced bias in snowfall near the coast. Our dataset is useful to fill in temporal and spatial data gaps, and to evaluate RCMs where few in situ measurements are available.

Within the lower percolation zone of the southeastern Greenland ice sheet, meltwater has accumulated within the firn pore space, forming extensive firn aquifers. Previously, it was unclear if these aquifers stored or facilitated meltwater runoff. Following mixing of a saline solution into boreholes within the aquifer, we observe that specific conductance measurements decreased over time as flowing freshwater diluted the saline mixture in the borehole. These tests indicate that water flows through the aquifer with an average specific discharge of 4.3 × 10−6 m/s (σ = 2.5 × 10−6 m/s). The specific discharge decreases dramatically to 0 m/s, defining the bottom of the aquifer between 30 to 50 m depth. The observed flow indicates that the firn pore space is a short-term (