Abstract
Albedo—a primary control on surface melt—varies considerably across the Greenland Ice Sheet yet the specific surface types that comprise its dark zone remain unquantified. Here we use UAV imagery to attribute seven distinct surface types to observed albedo along a 25 km transect dissecting the western, ablating sector of the ice sheet. Our results demonstrate that distributed surface impurities—an admixture of dust, black carbon and pigmented algae—explain 73% of the observed spatial variability in albedo and are responsible for the dark zone itself. Crevassing and supraglacial water also drive albedo reduction but due to their limited extent, explain just 12 and 15% of the observed variability respectively. Cryoconite, concentrated in large holes or fluvial deposits, is the darkest surface type but accounts for <1% of the area and has minimal impact. We propose that the ongoing emergence and dispersal of distributed impurities, amplified by enhanced ablation and biological activity, will drive future expansion of Greenland's dark zone.
Highlights
Albedo—a primary control on surface melt—varies considerably across the Greenland Ice Sheet yet the specific surface types that comprise its dark zone remain unquantified
On 8 August 2014, a fixed-wing unmanned aerial vehicle (UAV) equipped with a digital camera and upward and downward facing pyranometers was deployed from a field camp based in the vicinity of the Ktransect, S6 automated weather station (AWS) on a 25 km eastwest transect dissecting the dark zone (Fig. 1)
The analysis presented here demonstrates that the dark zone has low fractional areas of surface water (
Summary
Albedo—a primary control on surface melt—varies considerably across the Greenland Ice Sheet yet the specific surface types that comprise its dark zone remain unquantified. Previous field-based, in situ observations indicate that western Greenland’s ablation zone is characterized by highly variable nonice constituents and surface structures[8,13,14,15] These include features such as crevasses, fractures and foliations[16,17]; supraglacial hydrological features, including streams, rivers, ponds and lakes[18,19]; snow patches and fracture cornices; cryoconite, concentrated in holes or in supraglacial fluvial deposits[20,21]; microbes and their humic by-products[22,23,24]; mineral dust and aerosols from outcropping or contemporary aeolian deposition including black carbon from wildfires[10,25,26] and other aerosols. The mean albedo of each surface type was derived from the digital imagery and the relative contribution of different surface types to mesoscale albedo variability (defined by MOD10A1 pixels) was calculated using principal component regression (PCR)
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