The Sentinel Application Platform (SNAP) architecture facilitates Earth Observation data processing. In this work, we present results from a new Snow Processor for SNAP. We also describe physical principles behind the developed snow property retrieval technique based on the analysis of Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3A/B measurements over clean and polluted snow fields. Using OLCI spectral reflectance measurements in the range 400–1020 nm, we derived important snow properties such as spectral and broadband albedo, snow specific surface area, snow extent and grain size on a spatial grid of 300 m. The algorithm also incorporated cloud screening and atmospheric correction procedures over snow surfaces. We present validation results using ground measurements from Antarctica, the Greenland ice sheet and the French Alps. We find the spectral albedo retrieved with accuracy of better than 3% on average, making our retrievals sufficient for a variety of applications. Broadband albedo is retrieved with the average accuracy of about 5% over snow. Therefore, the uncertainties of satellite retrievals are close to experimental errors of ground measurements. The retrieved surface grain size shows good agreement with ground observations. Snow specific surface area observations are also consistent with our OLCI retrievals. We present snow albedo and grain size mapping over the inland ice sheet of Greenland for areas including dry snow, melted/melting snow and impurity rich bare ice. The algorithm can be applied to OLCI Sentinel-3 measurements providing an opportunity for creation of long-term snow property records essential for climate monitoring and data assimilation studies—especially in the Arctic region, where we face rapid environmental changes including reduction of snow/ice extent and, therefore, planetary albedo.

Microalgae colonizing the underside of sea ice in spring are a key component of the Arctic foodweb as they drive early primary production and transport of carbon from the atmosphere to the ocean interior. Onset of the spring bloom of ice algae is typically limited by the availability of light, and the current consensus is that a few tens‐of‐centimeters of snow is enough to prevent sufficient solar radiation to reach underneath the sea ice. We challenge this consensus, and investigated the onset and the light requirement of an ice algae spring bloom, and the importance of snow optical properties for light penetration. Colonization by ice algae began in May under >1 m of first‐year sea ice with ∼1 m thick snow cover on top, in NE Greenland. The initial growth of ice algae began at extremely low irradiance (<0.17 μmol photons m−2 s−1) and was documented as an increase in Chlorophyll a concentration, an increase in algal cell number, and a viable photosynthetic activity. Snow thickness changed little during May (from 110 to 91 cm), however the snow temperature increased steadily, as observed from automated high‐frequency temperature profiles. We propose that changes in snow optical properties, caused by temperature‐driven snow metamorphosis, was the primary driver for allowing sufficient light to penetrate through the thick snow and initiate algae growth below the sea ice. This was supported by radiative‐transfer modeling of light attenuation. Implications are an earlier productivity by ice algae in Arctic sea ice than recognized previously.

Abstract. Snow accumulation is the main positive component of the mass balance in Antarctica. In contrast to the major efforts deployed to estimate its overall value on a continental scale – to assess the contribution of the ice sheet to sea level rise – knowledge about the accumulation process itself is relatively poor, although many complex phenomena occur between snowfall and the definitive settling of the snow particles on the snowpack. Here we exploit a dataset of near-daily surface elevation maps recorded over 3 years at Dome C using an automatic laser scanner sampling 40–100 m2 in area. We find that the averaged accumulation is relatively regular over the 3 years at a rate of +8.7 cm yr−1. Despite this overall regularity, the surface changes very frequently (every 3 d on average) due to snow erosion and heterogeneous snow deposition that we call accumulation by “patches”. Most of these patches (60 %–85 %) are ephemeral but can survive a few weeks before being eroded. As a result, the surface is continuously rough (6–8 cm root-mean-square height) featuring meter-scale dunes aligned along the wind and larger, decameter-scale undulations. Additionally, we deduce the age of the snow present at a given time on the surface from elevation time series and find that snow age spans over more than a year. Some of the patches ultimately settle, leading to a heterogeneous internal structure which reflects the surface heterogeneity, with many snowfall events missing at a given point, whilst many others are overrepresented. These findings have important consequences for several research topics including surface mass balance, surface energy budget, photochemistry, snowpack evolution, and the interpretation of the signals archived in ice cores.

Abstract. Knowledge of the albedo of polar regions is crucial for understanding a range of climatic processes that have an impact on a global scale. Light-absorbing impurities in atmospheric aerosols deposited on snow and sea ice by aeolian transport absorb solar radiation, reducing albedo. Here, the effects of five mineral aerosol deposits reducing the albedo of polar snow and sea ice are considered. Calculations employing a coupled atmospheric and snow/sea ice radiativetransfer model (TUV-snow) show that the effects of mineral aerosol deposits are strongly dependent on the snow or sea ice type rather than the differences between the aerosol optical characteristics. The change in albedo between five different mineral aerosol deposits with refractive indices varying by a factor of 2 reaches a maximum of 0.0788, whereas the difference between cold polar snow and melting sea ice is 0.8893 for the same mineral loading. Surprisingly, the thickness of a surface layer of snow or sea ice loaded with the same mass ratio of mineral dust has little effect on albedo. On the contrary, the surface albedo of two snowpacks of equal depth, containing the same mineral aerosol mass ratio, is similar, whether the loading is uniformly distributed or concentrated in multiple layers, regardless of their position or spacing. The impact of mineral aerosol deposits is much larger on melting sea ice than on other types of snow and sea ice. Therefore, the higher input of shortwave radiation during the summer melt cycle associated with melting sea ice accelerates the melt process.

We propose a system of analytical equations to retrieve snow grain size and absorption coefficient of pollutants from snow reflectance or snow albedo measurements in the visible and near-infrared regions of the electromagnetic spectrum, where snow single-scattering albedo is close to 1.0. It is assumed that ice grains and impurities (e.g., dust, black and brown carbon) are externally mixed, and that the snow layer is semi-infinite and vertically and horizontally homogeneous. The influence of close-packing effects on reflected light intensity are assumed to be small and ignored. The system of nonlinear equations is solved analytically under the assumption that impurities have the spectral absorption coefficient, which obey the Ångström power law, and the impurities influence the registered spectra only in the visible and not in the near infrared (and vice versa for ice grains). The theory is validated using spectral reflectance measurements and albedo of clean and polluted snow at various locations (Antarctica Dome C, European Alps). A technique to derive the snow albedo (plane and spherical) from reflectance measurements at a fixed observation geometry is proposed. The technique also enables the simulation of hyperspectral snow reflectance measurements in the broad spectral range from ultraviolet to the near infrared for a given snow surface if the actual measurements are performed at a restricted number of wavelengths (two to four, depending on the type of snow and the measurement system).

Abstract. Light-absorbing particles (LAPs) such as black carbon or mineral dust are some of the main drivers of snow radiative transfer. Small amounts of LAPs significantly increase snowpack absorption in the visible wavelengths where ice absorption is particularly weak, impacting the surface energy budget of snow-covered areas. However, linking measurements of LAP concentration in snow to their actual radiative impact is a challenging issue which is not fully resolved. In the present paper, we point out a new method based on spectral irradiance profile (SIP) measurements which makes it possible to identify the radiative impact of LAPs on visible light extinction in homogeneous layers of the snowpack. From this impact on light extinction it is possible to infer LAP concentrations present in each layer using radiative transfer theory. This study relies on a unique dataset composed of 26 spectral irradiance profile measurements in the wavelength range 350–950 nm with concomitant profile measurements of snow physical properties and LAP concentrations, collected in the Alps over two snow seasons in winter and spring conditions. For 55 homogeneous snow layers identified in our dataset, the concentrations retrieved from SIP measurements are compared to chemical measurements of LAP concentrations. A good correlation is observed for measured concentrations higher than 5 ng g−1 (r2=0.81) despite a clear positive bias. The potential causes of this bias are discussed, underlining a strong sensitivity of our method to LAP optical properties and to the relationship between snow microstructure and snow optical properties used in the theory. Additional uncertainties such as artefacts in the measurement technique for SIP and chemical contents along with LAP absorption efficiency may explain part of this bias. In addition, spectral information on LAP absorption can be retrieved from SIP measurements. We show that for layers containing a unique absorber, this absorber can be identified in some cases (e.g. mineral dust vs. black carbon). We also observe an enhancement of light absorption between 350 and 650 nm in the presence of liquid water in the snowpack, which is discussed but not fully elucidated. A single SIP acquisition lasts approximately 1 min and is hence much faster than collecting a profile of chemical measurements. With the recent advances in modelling LAP–snow interactions, our method could become an attractive alternative to estimate vertical profiles of LAP concentrations in snow.

Abstract. Knowledge of water-surface velocities in rivers is useful for understanding a range of river processes. In cold regions, river-ice break up and the related downstream transport of ice debris is often the most important hydrological event of the year, leading to flood levels that typically exceed those for the open-water period and to strong consequences for river infrastructure and ecology. Accurate and complete surface-velocity fields on rivers have rarely been produced. Here, we track river ice debris over a time period of about one minute, which is the typical time lag between the two or more images that form a stereo data set in spaceborne, along-track optical stereo mapping. Using a series of nine stereo scenes from the US/Japanese Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) onboard the NASA Terra spacecraft with 15 m image resolution, we measure the ice and water velocity field over a 620 km-long reach of the lower Lena River, Siberia, just above its entry into the Lena delta. Careful analysis and correction of higher-order image and sensor errors enables an accuracy of ice-debris velocities of up to 0.04 m s−1 from the ASTER data. Maximum ice or water speeds, respectively, reach up to 2.5 m s−1 at the time of data acquisition, 27 May 2011 (03:30 UTC). Speeds show clear along-stream undulations with a wavelength of about 21 km that agree well with variations in channel width and with the location of sand bars along the river reach studied. The methodology and results of this study could be valuable to a number of disciplines requiring detailed information about river flow, such as hydraulics, hydrology, river ecology and natural-hazard management.

Abstract. Surface albedo is an essential variable to determine the Earth's surface energy budget, in particular for snow-covered areas where it is involved in one of the most powerful positive feedback loops of the climate system. In situ measurements of broadband and spectral albedo are therefore common. However they are subject to several artefacts. Here we investigate the sensitivity of spectral albedo measurements to surface slope, and we propose simple correction algorithms to retrieve the intrinsic albedo of a slope from measurements, as if it were flat. For this, we first derive the analytical equations relating albedo measured on a slope to intrinsic direct and diffuse albedo, the apportionment between diffuse and direct incoming radiation, and slope inclination and aspect. The theory accounts for two main slope effects. First, the slope affects the proportion of solar radiation intercepted by the surface relative to that intercepted by the upward-looking, horizontal, sensor. Second, the upward- and downward-looking sensors receive reduced radiation from the sky and the surface respectively and increased radiation from neighbouring terrain. Using this theory, we show that (i) slope has a significant effect on albedo (over 0.01) from as little as a ≈1∘ inclination, causing distortions of the albedo spectral shape; (ii) the first-order slope effect is sufficient to fully explain measured albedo up to ≈15∘, which we designate “small-slope approximation”; and (iii) for larger slopes, the theory depends on the neighbouring slope geometry and land cover, leading to much more complex equations. Next, we derive four correction methods from the small-slope approximation, to be used depending on whether (1) the slope inclination and orientation are known or not, (2) the snow surface is free of impurities or dirty, and (3) a single or a time series of albedo measurements is available. The methods applied to observations taken in the Alps on terrain with up to nearly 20∘ slopes prove the ability to recover intrinsic albedo with a typical accuracy of 0.03 or better. From this study, we derive two main recommendations for future field campaigns: first, sloping terrain requires more attention because it reduces the measurement accuracy of albedo even for almost invisible slopes (1–2∘). Second, while the correction of the slope effect is possible, it requires additional information such as the spectral diffuse and direction partitioning and if possible the actual slope inclination and aspect, especially when the absence of impurities can not be assumed.