Abstract
Abstract. Increasing melt over the Greenland Ice Sheet (GrIS) recorded over the past several years has resulted in significant changes of the percolation regime of the ice sheet. It remains unclear whether Greenland's percolation zone will act as a meltwater buffer in the near future through gradually filling all pore space or if near-surface refreezing causes the formation of impermeable layers, which provoke lateral runoff. Homogeneous ice layers within perennial firn, as well as near-surface ice layers of several meter thickness have been observed in firn cores. Because firn coring is a destructive method, deriving stratigraphic changes in firn and allocation of summer melt events is challenging. To overcome this deficit and provide continuous data for model evaluations on snow and firn density, temporal changes in liquid water content and depths of water infiltration, we installed an upward-looking radar system (upGPR) 3.4 m below the snow surface in May 2016 close to Camp Raven (66.4779∘ N, 46.2856∘ W) at 2120 m a.s.l. The radar is capable of quasi-continuously monitoring changes in snow and firn stratigraphy, which occur above the antennas. For summer 2016, we observed four major melt events, which routed liquid water into various depths beneath the surface. The last event in mid-August resulted in the deepest percolation down to about 2.3 m beneath the surface. Comparisons with simulations from the regional climate model MAR are in very good agreement in terms of seasonal changes in accumulation and timing of onset of melt. However, neither bulk density of near-surface layers nor the amounts of liquid water and percolation depths predicted by MAR correspond with upGPR data. Radar data and records of a nearby thermistor string, in contrast, matched very well for both timing and depth of temperature changes and observed water percolations. All four melt events transferred a cumulative mass of 56 kg m−2 into firn beneath the summer surface of 2015. We find that continuous observations of liquid water content, percolation depths and rates for the seasonal mass fluxes are sufficiently accurate to provide valuable information for validation of model approaches and help to develop a better understanding of liquid water retention and percolation in perennial firn.
Highlights
The Greenland Ice Sheet (GrIS) has been affected by changes in environmental conditions over recent decades, which resulted in persistent negative mass balances all over the ice sheet (e.g., Sasgen et al, 2012)
All MAR outputs for depths beneath the surface and recorded temperature data are converted to match the radar data. This was performed by subtracting simulated depths beneath the surface from bulk layer thickness of Ls measured by the FirnCover ultrasonic transducer (MacFerrin et al, 2015)
Concerning the mass balance of the snow layer above the summer horizon 2015 (b15) at Dye-2, we found an increase in accumulation of 84.4 kg m−2 for the time period of May until 30 September 2016
Summary
The Greenland Ice Sheet (GrIS) has been affected by changes in environmental conditions over recent decades, which resulted in persistent negative mass balances all over the ice sheet (e.g., Sasgen et al, 2012). Since melt conditions are expected to continue to increase (Vizcaíno et al, 2010; Huybrechts et al, 2011) and being amplified especially in northern latitudes (e.g., Meehl et al, 2012), the determination of melt and refreezing, and mass redistribution through liquid water are of utmost importance for density and firn temperature estimations in accumulation areas of polar regions (e.g., Gascon et al, 2014). Single snow and firn parameters such as density and temperature have a major effect on the storage capacity of melt water with the consequence that understanding and monitoring of these parameters is necessary for correct predictions of SMB and, on sea-level rise through melt of polar ice sheets (e.g., Hanna et al, 2008; Gardner et al, 2013). Liquid water infiltration into snow and firn and retention therein are major components of uncertainties in current SMB measurements and projections (Vernon et al, 2013) because observations are lacking (Harper et al, 2012)
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