Seasonal changes of ice surface characteristics and productivity in the ablation zone of the Greenland Ice Sheet

Field and remote sensing observations in the ablation zone of the Greenland Ice Sheet have revealed a diverse range of ice surface characteristics, primarily reflecting the variable distribution of fine debris (cryoconite). This debris reduces the surface albedo and is therefore an important control on melt rates and ice sheet mass balance. Meanwhile, studies of ice sheet surface biological processes have found active microbial communities associated with the cryoconite debris, which may themselves modify the cryoconite distribution. Due to the considerable difficulties involved with collecting ground-based observations of the ice surface, our knowledge of the physical and biological surface processes, and their links, remains very limited. Here we present data collected at a field camp established in the ice sheet ablation zone at 67 N, occupied for almost the entire melt season (26 May–10 August 2012), with the aim of gaining a much more detailed understanding of the physical and biological processes occurring on the ice surface. These data sets include quadrat surveys of surface type, measurements of ice surface ablation, and in situ biological oxygen demand incubations to quantify microbial activity. In addition, albedo at the site was retrieved from AVHRR (Advanced Very High Resolution Radiometer) remote sensing data. Observations of the areal coverage of different surface types revealed a rapid change from complete snow cover to the “summer” (summer study period) ice surface of patchy debris (“dirty ice”) and cryoconite holes. There was significant correlation between surface albedo, cryoconite hole coverage and surface productivity during the melt season, but microbial activity in “dirty ice” was not correlated with albedo and varied widely throughout the season. While this link suggests the potential for a remote-sensing approach to monitoring cryoconite hole biological processes, very wide seasonal and spatial variability in net surface productivity demonstrates the need for caution when extrapolating point measurements of biological processes to larger temporal or spatial scales.