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Cryoconite holes (CHs) are water-filled cylindrical holes with cryoconite (dark-coloured sediment) deposited at their bottoms, forming on ablating ice surfaces of glaciers and ice sheets worldwide. Because the collapse of CHs may disperse cryoconite on the ice surface, thereby decreasing the ice surface albedo, accurate simulation of the temporal changes in CH depth is essential for understanding ice surface melt. We established a novel model that simulates the temporal changes in CH depth using heat budgets calculated independently at the ice surface and CH bottom based on hole-shaped geometry. We evaluated the model with in situ observations of the CH depths on the Qaanaaq ice cap in northwestern Greenland during the 2012, 2014, and 2017 melt seasons. The model reproduced the observed depth changes and timing of CH collapse well. Although earlier models have shown that CH depth tends to be deeper when downward shortwave radiation is intense, our sensitivity tests suggest that deeper CH tends to form when the diffuse component of downward shortwave radiation is dominant, whereas CHs tend to be shallower when the direct component is dominant. In addition, the total heat flux to the CH bottom is dominated by shortwave radiation transmitted through ice rather than that directly from the CH mouths when the CH is deeper than 0.01 m. Because the shortwave radiation transmitted through ice can reach the CH bottom regardless of CH diameter, CH depth is unlikely to be correlated with CH diameter. The relationship is consistent with previous observational studies. Furthermore, the simulations highlighted that the difference in albedo between ice surface and CH bottom was a key factor for reproducing the timing of CH collapse. It implies that lower ice surface albedo could induce CH collapse and thus cause further lowering of the albedo. Heat component analysis suggests that CH depth is governed by the balance between the intensity of the diffuse component of downward shortwave radiation and the turbulent heat transfer. Therefore, these meteorological conditions may be important factors contributing to the recent surface darkening of the Greenland ice sheet and other glaciers via the redistribution of CHs. [ABSTRACT FROM AUTHOR]

Surface albedo of snow and ice is substantially reduced by inorganic impurities, such as aeolian mineral dust (MD) and black carbon (BC), and also by organic impurities, such as microbes that live in the snow. In this paper, we present the temporal changes of surface albedo, snow grain size, MD, BC and snow algal cell concentration observed on a snowpack in northwest Greenland during the ablation season of 2014 and our attempt to reproduce the changes in albedo with a physically based snow albedo model. We also attempt to reproduce the effects of inorganic impurities and the red snow algae (Sanguina nivaloides) on albedo. Concentrations of MD and red snow algae in the surface snow were found to increase in early August, while snow grain size and BC were found to not significantly change throughout the ablation season. Surface albedo was found to have decreased by 0.08 from late July to early August. The albedo simulated by the model agreed with the albedo observed during the study period. However, red snow algae exerted little effect on surface albedo in early August. This is probably owing to the abundance of smaller cells (4.9×104 cells L -1) when compared with the cell abundance of red snow reported by previous studies in the Arctic region (∼108 cells L -1). The simulation of snow albedo until the end of the melting season, with a snow algae model, revealed that the reduction in albedo attributed to red snow algae could equal 0.004, out of a total reduction of 0.102 arising from the three impurities on a snowpack in northwest Greenland. Finally, we conducted scenario simulations using the snow albedo model, coupled with the snow algae model, in order to simulate the possible effects of red snow blooming on snow albedo under warm conditions in northwest Greenland. The result suggests that albedo reduction by red snow algal growth under warm conditions (surface snow temperature of + 1.5 ∘ C) reached 0.04, equivalent to a radiative forcing of 7.5 W m -2 during the ablation season of 2014. This coupled albedo model has the potential to dynamically simulate snow albedo, including the effect of organic and inorganic impurities, leading to proper estimates of the surface albedo of snow cover in Greenland. [ABSTRACT FROM AUTHOR]

One of the primary controls upon the melting of the Greenland Ice Sheet (GrIS) is albedo, a measure of how much solar radiation that hits a surface is reflected without being absorbed. Lower-albedo snow and ice surfaces therefore warm more quickly. There is a major difference in the albedo of snow-covered versus bare-ice surfaces, but observations also show that there is substantial spatio-temporal variability of up to ∼0.4 in bare-ice albedo. Variability in bare-ice albedo has been attributed to a number of processes including the accumulation of light-absorbing impurities (LAIs) and the changing physical properties of the near-surface ice. However, the combined impact of these processes upon albedo remains poorly constrained. Here we use field observations to show that pigmented glacier algae are ubiquitous and cause surface darkening both within and outside the south-west GrIS "dark zone" but that other factors including modification of the ice surface by algal bloom presence, surface topography and weathering crust state are also important in determining patterns of daily albedo variability. We further use observations from an unmanned aerial system (UAS) to examine the scale gap in albedo between ground versus remotely sensed measurements made by Sentinel-2 (S-2) and MODIS. S-2 observations provide a highly conservative estimate of algal bloom presence because algal blooms occur in patches much smaller than the ground resolution of S-2 data. Nevertheless, the bare-ice albedo distribution at the scale of 20 m ×20 m S-2 pixels is generally unimodal and unskewed. Conversely, bare-ice surfaces have a left-skewed albedo distribution at MODIS MOD10A1 scales. Thus, when MOD10A1 observations are used as input to energy balance modelling, meltwater production can be underestimated by ∼2 %. Our study highlights that (1) the impact of the weathering crust state is of similar importance to the direct darkening role of light-absorbing impurities upon ice albedo and (2) there is a spatial-scale dependency in albedo measurement which reduces detection of real changes at coarser resolutions. [ABSTRACT FROM AUTHOR]

Snow algal bloom is a common phenomenon on melting snowpacks in polar and alpine regions and can substantially increase snow melt rates due to the effect of albedo reduction on the snow surface. In order to reproduce algal growth on the snow surface using a numerical model, temporal changes in snow algal abundance were investigated on the Qaanaaq Glacier in north-western Greenland from June to August 2014. Snow algae first appeared at the study sites in late June, which was approximately 94 h after air temperatures exceeded the melting point. Algal abundance increased exponentially after this appearance, but the increasing rate became slow after late July, and finally reached 3.5 × 10 7 cells m -2 in early August. We applied a logistic model to the algal growth curve and found that the algae could be reproduced with an initial cell concentration of 6.9 × 10 2 cells m -2 , a growth rate of 0.42 d -1 , and a carrying capacity of 3.5 × 10 7 cells m -2 on this glacier. This model has the potential to simulate algal blooms from meteorological data sets and to evaluate their impact on the melting of seasonal snowpacks and glaciers. [ABSTRACT FROM AUTHOR]

The darkening effects of biological impurities on ice and snow have been recognised as a control on the surface energy balance of terrestrial snow, sea ice, glaciers and ice sheets. With a heightened interest in understanding the impacts of a changing climate on snow and ice processes, quantifying the impact of biological impurities on ice and snow albedo ("bioalbedo") and its evolution through time is a rapidly growing field of research. However, rigorous quantification of bioalbedo has remained elusive because of difficulties in isolating the biological contribution to ice albedo from that of inorganic impurities and the variable optical properties of the ice itself. For this reason, isolation of the biological signature in reflectance data obtained from aerial/orbital platforms has not been achieved, even when ground-based biological measurements have been available. This paper provides the cell-specific optical properties that are required to model the spectral signatures and broadband darkening of ice. Applying radiative transfer theory, these properties provide the physical basis needed to link biological and glaciological ground measurements with remotely sensed reflectance data. Using these new capabilities we confirm that biological impurities can influence ice albedo, then we identify 10 challenges to the measurement of bioalbedo in the field with the aim of improving future experimental designs to better quantify bioalbedo feedbacks. These challenges are (1) ambiguity in terminology, (2) characterising snow or ice optical properties, (3) characterising solar irradiance, (4) determining optical properties of cells, (5) measuring biomass, (6) characterising vertical distribution of cells, (7) characterising abiotic impurities, (8) surface anisotropy, (9) measuring indirect albedo feedbacks, and (10) measurement and instrument configurations. This paper aims to provide a broad audience of glaciologists and biologists with an overview of radiative transfer and albedo that could support future experimental design. [ABSTRACT FROM AUTHOR]