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International audience; The transmission of ultraviolet (UVR) and photosynthetically available radiation (PAR) through sea ice is a key factor controlling under-ice phytoplankton growth in seasonally ice-covered waters. The increase toward sufficient light levels for positive net photosynthesis occurs concurrently with the sea ice melt progression in late spring when ice surface conditions shift from a relatively homogeneous high-albedo snow cover to a less reflective mosaic of bare ice and melt ponds. Here, we present a detailed dataset on the spatial and temporal progression of transmitted UVR and PAR in relation to changing quantities of snow, sea ice and melt ponds. Data were collected with a remotely operated vehicle (ROV) during the GreenEdge landfast sea ice campaign in June–July 2016 in southwestern Baffin Bay. Over the course of melt progression, there was a 10-fold increase in spatially averaged UVR and PAR transmission through the sea ice cover, reaching a maximum transmission of 31% for PAR, 7% for UVB, and 26% for UVA radiation. The depth under the sea ice experiencing spatial variability in light levels due to the influence of surface heterogeneity in snow, white ice and melt pond distributions increased from 7 ± 4 to 20 ± 6 m over our study. Phytoplankton drifting in under-ice surface waters were thus exposed to variations in PAR availability of up to 43%, highlighting the importance to account for spatial heterogeneity in light transmission through melting sea ice. Consequently, we demonstrate that spatial averages of PAR transmission provided more representative light availability estimates to explain under-ice bloom progression relative to single point irradiance measurements during the sea ice melt season. Encouragingly, the strong dichotomy between white ice and melt pond PAR transmittance and surface albedo permitted a very good estimate of spatially averaged light transmission from drone imagery of the surface and point transmittance measurements beneath different ice surface types.

The energy budget of Arctic sea ice is strongly affected by the snow cover. Intensive sampling of snow properties was conducted near Qikiqtarjuak in Baffin Bay on typical landfast sea ice during two melt seasons in 2015 and 2016. The sampling included stratigraphy, vertical profiles of snow specific surface area (SSA), density and surface spectral albedo. Both seasons feature four main phases: I) dry snow cover, II) surface melting, III) ripe snowpack and IV) melt pond formation. Each of them was characterized by distinctive physical and optical properties. Highest SSA of 49.3 m2 kg−1 was measured during phase I on surface windslab together with a high broadband albedo of 0.87. The next phase was marked by alternative episodes of surface melting which dramatically decreased the SSA below 3 m2 kg−1 and episodes of snowfall reestablishing the pre-melt conditions. Albedo was highly time variable especially in the near-infrared with minimum values around 0.45 at 1000 nm. At some point, the melt progressed leading to a fully ripe snowpack composed of clustered rounded grains in phase III. Albedo began to decrease in the visible as snow thickness decreased but remained steady at longer wavelengths. Moreover, its spatial variability clearly appeared for the first time following snow depth heterogeneity. The impacts on albedo of both snow SSA and thickness were quantitatively investigated using a radiative transfer model. Comparisons between albedo measurements and simulations show that our data on snow physical properties are relevant for radiative transfer modeling. They also point out to the importance of the properties of the very surface snow layer for albedo computation, especially during phase II when several distinctive layers of snow superimposed following snowfalls, melt or diurnal cycles.

Abstract. Spectral albedo of the snow surface in the visible/near-infrared range has been measured for 3 years by an automatic spectral radiometer installed at Dome C (75°S, 123°E) in Antarctica in order to retrieve specific surface area (SSA) of superficial snow. This study focuses on the uncertainties of the SSA retrieval due to the instrument deficiencies and issues related to data processing. We find that when the solar zenith angle is high, the main source of error is the imperfect angular response of the light collectors. This imperfection introduces a small spurious wavelength-dependent trend in the albedo spectra which greatly affects the SSA retrieval. By modeling this effect, we show that for typical snow and illumination conditions encountered at Dome C, retrieving SSA with an accuracy better than 15% (our target), requires the slope of this trend not to exceed 2% between 400 and 1100 nm. Such a small slope can be achieved only by i) careful design of the collectors, ii) an ad hoc correction of the spectra using the actual measured angular response of the collectors, and iii) for solar zenith angles less than 75°. The comparison of the retrieved SSA with independent measurements made with an optical device operating at 1310 nm confirms the presence of a sharp and recurrent vertical gradient of SSA in the uppermost centimeter at Dome C, which challenges the assessment of the absolute accuracy from independent measurements. Nevertheless, with three-fold variations of SSA during the summer seasons, we conclude that the retrieved SSA is accurate enough to provide a detailed picture of the October-March evolution of the surface snow at Dome C.