journal article Open Access Mar 16, 2016

Estimating ice albedo from fine debris cover quantified by a semi-automatic method: the case study of Forni Glacier, Italian Alps

The Cryosphere Vol. 10 No. 2 pp. 665-679 · Copernicus GmbH
View at Publisher Save 10.5194/tc-10-665-2016
Abstract
Abstract. In spite of the quite abundant literature focusing on fine debris deposition over glacier accumulation areas, less attention has been paid to the glacier melting surface. Accordingly, we proposed a novel method based on semi-automatic image analysis to estimate ice albedo from fine debris coverage (d). Our procedure was tested on the surface of a wide Alpine valley glacier (the Forni Glacier, Italy), in summer 2011, 2012 and 2013, acquiring parallel data sets of in situ measurements of ice albedo and high-resolution surface images. Analysis of 51 images yielded d values ranging from 0.01 to 0.63 and albedo was found to vary from 0.06 to 0.32. The estimated d values are in a linear relation with the natural logarithm of measured ice albedo (R  =  −0.84). The robustness of our approach in evaluating d was analyzed through five sensitivity tests, and we found that it is largely replicable. On the Forni Glacier, we also quantified a mean debris coverage rate (Cr) equal to 6 g m−2 per day during the ablation season of 2013, thus supporting previous studies that describe ongoing darkening phenomena at Alpine debris-free glaciers surface. In addition to debris coverage, we also considered the impact of water (both from melt and rainfall) as a factor that tunes albedo: meltwater occurs during the central hours of the day, decreasing the albedo due to its lower reflectivity; instead, rainfall causes a subsequent mean daily albedo increase slightly higher than 20 %, although it is short-lasting (from 1 to 4 days).
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Published
Mar 16, 2016
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10(2)
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665-679
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Roberto Sergio Azzoni, Antonella Senese, Andrea Zerboni, et al. (2016). Estimating ice albedo from fine debris cover quantified by a semi-automatic method: the case study of Forni Glacier, Italian Alps. The Cryosphere, 10(2), 665-679. https://doi.org/10.5194/tc-10-665-2016