Snow spectral albedo at Summit, Greenland: measurements and numerical simulations based on physical and chemical properties of the snowpack

Abstract

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.

Measurements and modelling of snow particle size and shortwave infrared albedo over a melting Antarctic ice sheet

“…Overall, spherical particles caused smaller α b, λ biases than droxtal particles in the clear-sky cases, because of the smaller positive bias in the 1.0-1.4 µm region. The biases in the sphere-based α b, λ and in the associated Swn λ are in qualitative agreement with the biases obtained by Carmagnola et al (2013) using the same modelling approach, although Carmagnola et al (2013) showed the albedo and the absorbed energy integrated over different wavebands and therefore a direct quantitative comparison is not possible.…”

“…Data sets including contemporary in situ observations of albedo and grain texture are few, compared to the large variety of existing snow conditions (Aoki et al, 2000;Carmagnola et al, 2013;Dominé et al, 2006;Nakamura et al, 2001;Painter and Dozier, 2004). These data sets only include short measurement periods, as both spectral albedo and snow observations rely on very laborious and time consuming methods.…”

Development and calibration of an automatic spectral albedometer to estimate near-surface snow SSA time series

“…10. The differences between the fit and the observation are small; we can note a slight overestimation at 800 nm and underestimation at 970 nm, both of which are very likely due to a small error in the refractive index of the ice already pointed out in other studies (e.g., Carmagnola et al, 2013). In contrast, the overestimation at 1030 nm is more likely an error in the observations resulting from the low sensitivity of the spectrometer in this wavelength range.…”

“…They attributed this to the deposition of snow particles having been shrunk by sublimation during blowing snow events. Carmagnola et al (2013) at Summit in Greenland use spectral data in the visible, near-and shortwave infrared and found that tuning the surface layer SSA helped to improve the agreement with the observations but did not explore values as high as Grenfell et al (1994) did. In contrast, Gallet et al (2011) measured SSA vertical profiles at Dome C and obtained radiative transfer calculations in agreement with Hudson et al (2006) observations without adding such a layer.…”

“…It has been normalized by the ideal cosine and considering exact response at 0 • following (Grenfell et al, 1994). For angles lower than 70 • , the deviation remains within ±6 % of the ideal response which is comparable to Grenfell et al (1994) but twice better than Carmagnola et al (2013), who used a flat collector. The deviation between 70 and 80 • degrades significantly, which suggests uncorrectable measurements in this range of SZA; however, it remains within ±15 % while Grenfell et al (1994) show twice larger errors.…”