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Pigmented microalgae inhabiting snow and ice environments lower the albedo of glacier and ice-sheet surfaces, significantly enhancing surface melt. Our ability to accurately predict their role in glacier and ice-sheet surface mass balance is limited by the current lack of empirical data to constrain their representation in predictive models. Here we present new empirical optical properties for snow and ice algae and incorporate them in a radiative transfer model to investigate their impact on snow and ice surface albedo. We found ice algal cells to be more efficient absorbers than snow algal cells, but their blooms had comparable impact on surface albedo due to the different photic conditions of their habitats. We then used the model to reconstruct the effect of ice algae on bare ice albedo spectra collected at our field site in southern Greenland, where blooms dropped the albedo locally by between 3 and 43%, equivalent to 1–10 L m$^{-2}$ d$^{-1}$ of melted ice. Using the newly parametrized model, future studies could investigate biological albedo reduction and algal quantification from remote hyperspectral and multispectral imagery.

The surface of the Greenland Ice Sheet is darkening, which accelerates its surface melt. The role of glacier ice algae in reducing surface albedo is widely recognised but not well quantified and the feedbacks between the algae and the weathering crust remain poorly understood. In this letter, we summarise recent advances in the study of the biological darkening of the Greenland Ice Sheet and highlight three key research priorities that are required to better understand and forecast algal-driven melt: (i) identifying the controls on glacier ice algal growth and mortality, (ii) quantifying the spatio-temporal variability in glacier ice algal biomass and processes involved in cell redistribution and (iii) determining the albedo feedbacks between algal biomass and weathering crust characteristics. Addressing these key research priorities will allow us to better understand the supraglacial ice-algal system and to develop an integrated model incorporating the algal and physical controls on ice surface albedo.

Several different types of light-absorbing particles (LAPs) darken snow surfaces, enhancing snowmelt on glaciers and snowfields. LAPs are often present as a mixture of biotic and abiotic components at the snow surface, yet methods to separate their respective abundance and albedo-reducing effects are lacking. Here, we present a new optimisation method enabling the retrievals of dust, black carbon, and red algal abundances and their respective darkening effects from spectral albedo. This method includes a deep-learning emulator of a radiative transfer model (RTM) and an inversion algorithm. The emulator alone can be used as a fast and lightweight alternative to the full RTM with the possibility to add new features, such as new light-absorbing particles. The inversion method was applied to 180 ground field spectra collected on snowfields in southern Norway, with a mean absolute error on spectral albedo of 0.0056, and surface parameters that closely matched expectations from qualitative assessments of the surface. The emulator predictions of surface parameters were used to quantify the albedo-reducing effect of algal blooms, mineral dust, and dark particles represented by black carbon. Among these 180 surfaces, the albedo reduction due to light-absorbing particles was highly variable and reached up to 0.13, 0.21, and 0.25 for red algal blooms, mineral dust, and dark particles respectively. In addition, the effect of a single LAP was attenuated by the presence of other LAPs by up to 2–3 times. These results demonstrate the importance of considering the individual types of light-absorbing particles and their concomitant interactions for forecasting snow albedo.

Blooms of pigmented algae darken the surface of glaciers and ice sheets, thereby enhancing solar energy absorption and amplifying ice and snow melt. The impacts of algal pigment and community composition on surface darkening are still poorly understood. Here, we characterise glacier ice and snow algal pigment signatures on snow and bare ice surfaces and study their role in photophysiology and energy absorption on three glaciers in Southeast Greenland. Purpurogallin and astaxanthin esters dominated the glacier ice and snow algal pigment pools (mass ratios to chlorophyll a of 32 and 56, respectively). Algal biomass and pigments impacted chromophoric dissolved organic matter concentrations. Despite the effective absorption of astaxanthin esters at wavelengths where incoming irradiance peaks, the cellular energy absorption of snow algae was 95% lower than anticipated from their pigmentation, due to pigment packaging. The energy absorption of glacier ice algae was consequently ~ 5 × higher. On bare ice, snow algae may have locally contributed up to 13% to total biological radiative forcing, despite contributing 44% to total biomass. Our results give new insights into the impact of algal community composition on bare ice energy absorption and biomass accumulation during snow melt.