Abstract. The energy budget and the photochemistry of a snowpack depend greatly on the penetration of solar radiation in snow. Below the snow surface, spectral irradiance decreases exponentially with depth with a decay constant called the asymptotic flux extinction coefficient. As with the albedo of the snowpack, the asymptotic flux extinction coefficient depends on snow grain shape. While representing snow by a collection of spherical particles has been successful in the numerical computation of albedo, such a description poorly explains the decrease of irradiance in snow with depth. Here we explore the limits of the spherical representation. Under the assumption of geometric optics and weak absorption by snow, the grain shape can be simply described by two parameters: the absorption enhancement parameter B and the geometric asymmetry factor g G . Theoretical calculations show that the albedo depends on the ratio B/(1−g G ) and the asymptotic flux extinction coefficient depends on the product B(1 − g G ). To understand the influence of grain shape, the values of B and g G are calculated for a variety of simple geometric shapes using ray tracing simulations. The results show that B and (1 − g G ) generally covary so that the asymptotic flux extinction coefficient exhibits larger sensitivity to the grain shape than albedo. In particular it is found that spherical grains propagate light deeper than any other investigated shape. In a second step, we developed a method to estimate B from optical measurements in snow. A multi-layer, two-stream, radiative transfer model, with explicit grain shape dependence, is used to retrieve values of the B parameter of snow by comparing the model to joint measurements of reflectance and irradiance profiles. Such measurements were performed in Antarctica and in the Alps yielding estimates of B between 0.8 and 2.0. In addition, values of B were estimated from various measurements found in the literature, leading to a wider range of values (1.0-9.9) which may be partially explained by the limited accuracy of the data. This work highlights the large variety of snow microstructure and experimentally demonstrates that spherical grains, with B = 1.25, are inappropriate to model irradiance profiles in snow, an important result that should be considered in further studies dedicated to subsurface absorption of short-wave radiation and snow photochemistry.

Abstract. The broadband albedo of surface snow is determined both by the near-surface profile of the physical and chemical properties of the snowpack and by the spectral and angular characteristics of the incident solar radiation. Simultaneous measurements of the physical and chemical properties of snow were carried out at Summit Camp, Greenland (72 • 36 N, 38 • 25 W, 3210 m a.s.l.) in May and June 2011, along with spectral albedo measurements. One of the main objectives of the field campaign was to test our ability to predict snow spectral albedo by comparing the measured albedo to the albedo calculated with a radiative transfer model, using measured snow physical and chemical properties. To achieve this goal, we made daily measurements of the snow spectral albedo in the range 350-2200 nm and recorded snow stratigraphic information down to roughly 80 cm. The snow specific surface area (SSA) was measured using the DUFISSS instrument (DUal Frequency Integrating Sphere for Snow SSA measurement, Gallet et al., 2009). Samples were also collected for chemical analyses including black carbon (BC) and dust, to evaluate the impact of light absorbing particulate matter in snow. This is one of the most comprehensive albedo-related data sets combining chemical analysis, snow physical properties and spectral albedo measurements obtained in a polar environment. The surface albedo was calculated from density, SSA, BC and dust profiles using the DISORT model (DIScrete Ordinate Radiative Transfer, Stamnes et al., 1988) and compared to the measured values. Results indicate that the energy absorbed by the snowpack through the whole spectrum considered can be inferred within 1.10 %. This accuracy is only slightly better than that which can be obtained considering pure snow, meaning that the impact of impurities on the snow albedo is small at Summit. In the near infrared, minor deviations in albedo up to 0.014 can be due to the accuracy of radiation and SSA measurements and to the surface roughness, whereas deviations up to 0.05 can be explained by the spatial heterogeneity of the snowpack at small scales, the assumption of spherical snow grains made for DISORT simulations and the vertical resolution of measurements of surface layer physical properties. At 1430 and around 1800 nm the discrepancies are larger and independent of the snow properties; we propose that they are due to errors in the ice refractive index at these wavelengths. This work contributes to the development of physically based albedo schemes in detailed snowpack models, and to the improvement of retrieval algorithms for estimating snow properties from remote sensing data.

Abstract. The European Alps stretch over a range of climate zones which affect the spatial distribution of snow. Previous analyses of station observations of snow were confined to regional analyses. Here, we present an Alpine-wide analysis of snow depth from six Alpine countries – Austria, France, Germany, Italy, Slovenia, and Switzerland – including altogether more than 2000 stations of which more than 800 were used for the trend assessment. Using a principal component analysis and k-means clustering, we identified five main modes of variability and five regions which match the climatic forcing zones: north and high Alpine, north-east, north-west, south-east, and south and high Alpine. Linear trends of monthly mean snow depth between 1971 and 2019 showed decreases in snow depth for most stations from November to May. The average trend among all stations for seasonal (November to May) mean snow depth was −8.4 % per decade, for seasonal maximum snow depth −5.6 % per decade, and for seasonal snow cover duration −5.6 % per decade. Stronger and more significant trends were observed for periods and elevations where the transition from snow to snow-free occurs, which is consistent with an enhanced albedo feedback. Additionally, regional trends differed substantially at the same elevation, which challenges the notion of generalizing results from one region to another or to the whole Alps. This study presents an analysis of station snow depth series with the most comprehensive spatial coverage in the European Alps to date.