Cross-Comparison of Albedo Products for Glacier Surfaces Derived from Airborne and Satellite (Sentinel-2 and Landsat 8) Optical Data

Abstract

Surface albedo partitions the amount of energy received by glacier surfaces from shortwave fluxes and modulates the energy available for melt processes. The ice-albedo feedback, influenced by the contamination of bare-ice surfaces with light-absorbing impurities, plays a major role in the melting of mountain glaciers in a warming climate. However, little is known about the spatial and temporal distribution and variability of bare-ice glacier surface albedo under changing conditions. In this study, we focus on two mountain glaciers located in the western Swiss Alps and perform a cross-comparison of different albedo products. We take advantage of high spectral and spatial resolution (284 bands, 2 m) imaging spectrometer data from the Airborne Prism Experiment (APEX) and investigate the applicability and potential of Sentinel-2 and Landsat 8 data to derive broadband albedo products. The performance of shortwave broadband albedo retrievals is tested and we assess the reliability of published narrow-to-broadband conversion algorithms. The resulting albedo products from the three sensors and different algorithms are further cross-compared. Moreover, the impact of the anisotropy correction is analysed depending on different surface types. While degradation of the spectral resolution impacted glacier-wide mean albedo by about 5%, reducing the spatial resolution resulted in changes of less than 1%. However, in any case, coarser spatial resolution was no longer able to represent small-scale variability of albedo on glacier surfaces. We discuss the implications when using Sentinel-2 and Landsat 8 to map dynamic glaciological processes and to monitor glacier surface albedo on larger spatial and more frequent temporal scales.

Impact of impurities and cryoconite on the optical properties of the Morteratsch Glacier (Swiss Alps)

“…In agreement with previous satellite investigations on Alpine glaciers, low α VIS values are estimated in the Morteratsch ablation zone (Brun et al, 2015;Dumont et al, 2011;Fugazza et al, 2016;Klok et al, 2004;Naegeli et al, 2015Naegeli et al, , 2017. This decrease in albedo can be explained by both an increase in LAI content and/or variations of the snow and ice grain properties.…”

Fluctuation of Glacial Retreat Rates in the Eastern Part of Warszawa Icefield, King George Island, Antarctica, 1979–2018

“…In general, in the entire visible spectrum, the reflection is very high: about 90% for snow and 65% for ice of glaciers. In contrast, in the shortwave infrared spectral reflection can be even lower than 10% [32].…”

“…For such selected pixels, local statistics were calculated in a moving window with a size of 2 × 2 pixels. Based on the knowledge of the spectral reflection characteristics of ice [32], it was assumed that a difference of less than 0.1 between the panNDSI index values will not allow for a detailed distinction of the ice-ground boundary ( Figure 3F). As the local variation increases for pixels arranged along the ice border, the higher the possibility of automatic or semiautomatic classification.…”

Quantifying bioalbedo: a new physically based model and discussion of empirical methods for characterising biological influence on ice and snow albedo

“…Several studies have estimated BRDFs and HCRFs of snow and sea ice surfaces (e.g. Hudson et al, 2006;Marks et al, 2015;Arnold et al, 2002), but equivalent measurements are scarce for glacier ice in various states of melt and impurity loading, although Naegeli et al (2015) measured HCRF for various surface types on an alpine glacier, and Gruell and de Ruyter de Wildt (1999) measured anisotropic reflection from melting glaciers in two Landsat Thematic Mapper bands. Naegeli et al (2017) recently showed that ice surfaces with higher impurity loads scatter more anisotropically, possibly due to locally enhanced melt.…”

“…We have recently undertaken field work for this purpose and will publish the outcomes in a future paper. There is uncertainty in the biological literature concerning the impact of cell size on the optical properties of algae arising from the spatial distribution of pigments within cells (Haardt and Maske, 1987), variable intracellular architecture (Haardt and Maske, 1987), packaging effects (Morel and Bricaud, 1981) and non-linear relationships between cell growth and Figure 4. A constant biomass (0.5 mg algae /g ice , pigment mass fractions (% total cell dry mass) is 1.5 % chlorophyll a, 5 % primary and secondary carotenoids, 15 µm cell radius) distributed vertically in layers of ice (1500 µm grain radius) of varying thickness (1, 2, 3, 4, 5, 10 mm).…”