Combined effect of algae and dust on snow spectral and broadband albedo

Abstract

The optical properties of snow can be strongly modified by the presence of a variety of impurities including mineral dust and snow algae. We made use of measured concentration of snow algae and mineral dust to parameterize the BioSNICAR radiative transfer model. Surficial snow samples were gathered during a field campaign on 7th July 2020 at the Presena glacier (Rhaetian Alps). We collected 18 samples of surface snow containing different amount of snow algae and mineral dust. Through radiative transfer simulations we estimated an average broadband albedo reduction of 7.4 ± 6.1 % and 35.3 ± 7.4 % compared to clean snow, caused by snow algae and mineral dust presence, respectively. When we considered the combined effect of snow algae and dust, we estimated a broadband albedo reduction equal to 40.8 ± 8.4 %. We estimated an average instantaneous radiative forcing induced by snow algae, mineral dust and both impurities equals to 42.3 (± 36.1) W/m2, 203.7 (±45.5) W/m2, and 211.8 (±45.9) W/m2, respectively.Using BioSNICAR simulations, we also tested a series of narrowband spectral indices to determine the concentration of mineral dust and snow algae from multi- and hyper-spectral data. Results showed that most spectral indices used for snow algae mapping are correlated also with mineral dust concentration. We found that only an index correlates uniquely with snow algae: the scaled band integral at 680 nm. A new spectral index, namely the Green Blue Normalized Index, is therefore proposed to discriminate mineral dust from snow algae when both impurities are present. The high spectral resolution of current (e.g. PRISMA, EnMAP) and future (e.g. CHIME, SBG) hyperspectral satellite missions will be fundamental to decouple the effect of mineral dust and snow algae on the optical properties of snow. In fact, from those data it is possible to calculate all narrowband indices presented in this study.