Small-scale spatial variability in bare-ice reflectance at Jamtalferner, Austria

• Published in: The cryosphere 2020-11, Vol.14 (11), p.4063-4081
• Main Authors: Hartl, Lea, Felbauer, Lucia, Schwaizer, Gabriele, Fischer, Andrea
• Format: Article
• Language: English
• Subjects: Ablation; Albedo; Albedo (solar); Analysis; Atmospheric models; Bare ice; Broadband; Data; Deglaciation; Dry ice; Dust; Glacial drift; Glaciers; Ice; Ice sheets; Landsat; Landsat satellites; Meltwater; Mountain glaciers; Mountains; Reflectance; Remote sensing; Satellite data; Satellites; Spacecraft recovery; Spatial variability; Spatial variations; Spectra; Spectral albedo; Spectral reflectance; Spectrum analysis; Synchronous satellites; Water
• ISSN: 1994-0424; 1994-0416; 1994-0424; 1994-0416
• DOI: 10.5194/tc-14-4063-2020

As Alpine glaciers become snow-free in summer, more dark, bare ice is exposed, decreasing local albedo and increasing surface melting. To include this feedback mechanism in models of future deglaciation, it is important to understand the processes governing broadband and spectral albedo at a local scale. However, few in situ reflectance data have been measured in the ablation zones of mountain glaciers. As a contribution to this knowledge gap, we present spectral reflectance data (hemispherical–conical–reflectance factor) from 325 to 1075 nm collected along several profile lines in the ablation zone of Jamtalferner, Austria. Measurements were timed to closely coincide with a Sentinel-2 and Landsat 8 overpass and are compared to the respective ground reflectance (bottom-of-atmosphere) products. The brightest spectra have a maximum reflectance of up to 0.7 and consist of clean, dry ice. In contrast, reflectance does not exceed 0.2 for dark spectra where liquid water and/or fine-grained debris are present. Spectra can roughly be grouped into dry ice, wet ice, and dirt or rocks, although gradations between these groups occur. Neither satellite captures the full range of in situ reflectance values. The difference between ground and satellite data is not uniform across satellite bands, between Landsat and Sentinel, and to some extent between ice surface types (underestimation of reflectance for bright surfaces, overestimation for dark surfaces). We highlight the need for further, systematic measurements of in situ spectral reflectance properties, their variability in time and space, and in-depth analysis of time-synchronous satellite data.