Effect of sastrugi on snow bidirectional reflectance and its application to MODIS data

Abstract

[1] Snow surface roughness such as sastrugi on the Antarctic ice sheet can be a cause of error for remote sensing of snow parameters. The effect of sastrugi on snow bidirectional reflectance was assessed by a field experiment, model simulations, and satellite measurements. The hemispherical-directional reflectance factor (HDRF) of artificial sastrugi-like linear ridges measured at Nakasatsunai, Hokkaido, Japan, exhibited different patterns from that of a flat surface, with the difference of more than ±50% for some geometries. A 3-D Monte Carlo radiative transfer model (MC model) reproduced both the HDRF measurements for the artificial ideal sastrugi and previous measurements for natural sastrugi at the South Pole. Furthermore, the sastrugi effect was applied to remote sensing. Failure to include the surface roughness in models for developing snow-grain-size lookup tables can lead to order-of-magnitude retrieval errors. Using the MC model and multiangle data derived from the Moderate Resolution Imaging Spectrometer over the South Pole during the 2003-2004 summer, the sastrugi and snow parameters were retrieved. The height-to-width ratio of sastrugi reduced from 0.1 to 0.02, whereas the azimuth angle was nearly constant within the range of 0°-30°during the summer. The snow grain size showed a seasonal variation, which depended on the spectral channel. These retrieved parameters were consistent with existing ground measurements. The results suggest that a combination of multiangle data and a 3-D radiative transfer model can be used to quantitatively estimate surface roughness, along with snow grain size, on ice sheets.Citation: Kuchiki, K., T. Aoki, M. Niwano, H. Motoyoshi, and H. Iwabuchi (2011), Effect of sastrugi on snow bidirectional reflectance and its application to MODIS data,

Intercomparison of retrieval algorithms for the specific surface area of snow from near-infrared satellite data in mountainous terrain, and comparison with the output of a semi-distributed snowpack model

“…Surface roughness also induces changes in BRDF (e.g. Leroux and Fily, 1998;Hudson and Warren, 2007;Zhuravleva and Kokhanovsky, 2011;Kuchiki et al, 2011). This point is not taken into account in our retrieval and consequently, on highly rugged pixels the accuracy of retrieved SSA is likely to decrease.…”

Numerical simulation of spectral albedos of glacier surfaces covered with glacial microbes in Northwestern Greenland

“…Snow densities in the two snow layers were 550 and 460 kg m -3 , respectively. The major mass contents of red snow were mineral dust and the others were organic matters, in which the organic carbon concentrations measured with the Lab OC-EC Aerosol Analyzer [9] were 80.8 and 3.2 ppmw for the two snow layers, respectively. The cryoconite surface we measured at Site-2 (Figure2b) consisted of ice grains with a radius of 5 to 10 mm and thickness of 3 cm above bare ice.…”

Albedo over rough snow and ice surfaces

“…One decisive factor for the representativeness is the "macroscopic" roughness of the surface, which has a strong effect on the surface albedo (Warren et al, 1998;Zhuravleva and Kokhanovsky, 2011). Although this effect has been extensively quantified over sastrugis and crevasses (Hudson and Warren, 2007;Kuchiki et al, 2011;Leroux and Fily, 1998;Pfeffer and Bretherton, 1987;Warren et al, 1998), its effect over penitentes (spike formations of snow and ice up to several meters high; Lliboutry, 1953), typical of several high altitude mountain glaciers and snow fields, remains less understood and limited to individual measurements. For example, Corripio and Purves (2005) and Kotlyakov and Lebedeva (1974) noted albedo reductions of 8-10 % over penitentes.…”

“…For example, Corripio and Purves (2005) and Kotlyakov and Lebedeva (1974) noted albedo reductions of 8-10 % over penitentes. Penitentes, however, have a surface roughness that is often much larger than sastrugis (Kuchiki et al, 2011) and which evolves over the ablation season (Cathles et al, 2014). Therefore, variable effects on the surface albedo can be expected and quantifying these is essential to model and understand the energy balance of glaciers with penitentes.…”