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Discussion papers | Copyright
https://doi.org/10.5194/tc-2016-204
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 12 Sep 2016

Research article | 12 Sep 2016

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This discussion paper is a preprint. It has been under review for the journal The Cryosphere (TC). A final paper in TC is not foreseen.

Attribution of Greenland's ablating ice surfaces on ice sheet albedo using unmanned aerial systems

Jonathan C. Ryan1, Alun Hubbard1,2, Marek Stibal3,4, Jason E. Box5, and the Dark Snow Project team* Jonathan C. Ryan et al.
  • 1Centre for Glaciology, Institute of Geography and Earth Sciences, Aberystwyth University, Aberystwyth, SY23 3DB, UK
  • 2Centre for Arctic Gas Hydrate, Environment and Climate, Department of Geology, University of Tromsø, Dramsveien 201, 9037, Norway
  • 3Department of Ecology, Faculty of Science, Charles University, Vinicna 7, 128 44 Prague, Czech Republic
  • 4Department of Geochemistry, Geological Survey of Denmark and Greenland, Copenhagen, Denmark
  • 5Department of Glaciology and Climate, Geological Survey of Denmark and Greenland, Copenhagen, Denmark
  • *A full list of authors and affiliations appears at the end of the paper

Abstract. Surface albedo, a primary control on the amount of energy available for melt, has considerable spatial heterogeneity across the Greenland ice sheet ablation area. However, the relative importance of distinct surface types on albedo remains unclear. In this study, the causes of mesoscale (102 to 103m) albedo variability are assessed using high resolution (decimetre-scale) digital imagery and broadband albedo data acquired by a fixed-wing unmanned aerial system. We characterize the reflectance properties and terrain roughness associated with six distinct surface types identified from a 25km longitudinal transect across the ablating dark region of the Kangerlussuaq sector. Principal component analysis of the fractional area of each surface type versus coincident Moderate Resolution Imaging Spectroradiometer (MODIS) albedo data reveals the relative importance of each surface type. The highest correlation with mesoscale albedo was the fractional area of distributed impurities. Although not the darkest surface type, their extensive coverage meant that they could explain 65% of the albedo variability across the survey transect including the presence of the dark region. In contrast, the 2% mean surface water coverage across our survey transect could only explain 12% of albedo variation and crevasses, only 17%. Localised cryoconite patches have the lowest albedo signature but comprise less than 1% of the survey area and do not appear to reduce mesoscale albedo. We anticipate further reduction in ablation area albedo under future warming as localized areas of distributed impurities, supraglacial water and crevassing increase in extent and conclude that current bare ice area albedo models may advance significantly by representing the evolution of the surface types identified in this study.

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Jonathan C. Ryan et al.
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Using digital imagery and broadband albedo acquired by a fixed-wing UAS we classified and measured the albedo of six surface types that dominate the Greenland ablation area and its dark region. We found that the primary control on ablation area albedo is the fractional area of distributed impurities. Although not the darkest surface type observed, the distributed impurities dominate the albedo signal because of their extensive coverage.
Using digital imagery and broadband albedo acquired by a fixed-wing UAS we classified and...
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