[1] A physically based snow albedo model (PBSAM), which can be used in a general circulation model, is developed. PBSAM calculates broadband albedos and the solar heating profile in snowpack as functions of snow grain size and concentrations of snow impurities, black carbon and mineral dust, in snow with any layer structure and under any solar illumination condition. The model calculates the visible and near-infrared (NIR) albedos by dividing each broadband spectrum into several spectral subbands to simulate the change in spectral distribution of solar radiation in the broadband spectra at the snow surface and in the snowpack. PBSAM uses (1) the look-up table method for calculations of albedo and transmittance in spectral subbands for a homogeneous snow layer, (2) an "adding" method for calculating the effect of an inhomogeneous snow structure on albedo and transmittance, and (3) spectral weighting of radiative parameters to obtain the broadband values from the subbands. We confirmed that PBSAM can calculate the broadband albedos of single-and two-layer snow models with good accuracy by comparing them with those calculated by a spectrally detailed radiative transfer model (RTM). In addition, we used radiation budget measurements and snow pit data obtained during the two winters from 2007 to 2009 at Sapporo, Hokkaido, Japan, for simulation of the broadband albedos by PBSAM and compared the results with the in situ measurements. A five-layer snow model with one visible subband and three NIR subbands were necessary for accurate simulation. Comparison of solar heating profiles calculated by PBSAM with those calculated by the spectrally detailed RTM showed that PBSAM calculated accurate solar heating profiles when at least three subbands were used in both the visible and NIR bands.Citation: Aoki, T., K. Kuchiki, M. Niwano, Y. Kodama, M. Hosaka, and T. Tanaka (2011), Physically based snow albedo model for calculating broadband albedos and the solar heating profile in snowpack for general circulation models, J. Geophys.

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[1] We developed a multilayered physical snowpack model named Snow Metamorphism and Albedo Process (SMAP), which is intended to be incorporated into general circulation models for climate simulations. To simulate realistic physical states of snowpack, SMAP incorporates a state-of-the-art physically based snow albedo model, which calculates snow albedo and solar heating profile in snowpack considering effects of snow grain size and snow impurities explicitly. We evaluated the performance of SMAP with meteorological and snow impurities (black carbon and dust) input data measured at Sapporo, Japan during two winters: 2007-2008 and 2008-2009, and found SMAP successfully reproduced all observed variations of physical properties of snowpack for both winters. We have thus confirmed that SMAP is suitable for climate simulations. With SMAP, we also investigated the effects of snow impurities on snowmelt at Sapporo during the two winters. We found that

Light-absorbingsnowimpuritiesofelementalcarbon(EC),organiccarbon(OC),andmineraldusthave been measured at three locations at elevations from 1,469 to 1,992m on August 1, 2011, and at the site SIGMA-A (78 N, 68 W, elevation 1,490m) on the northwest Greenland ice sheet (GrIS) during the period from June 28 to July 12, 2012. At SIGMA-A, a remarkable snow surface lowering together with snow meltingwasobservedduringtheobservationperiodin2012,whenarecordsurfacemeltingeventoccurred over the GrIS. The concentrations in the surface were 0.9, 3.8, and 107ppbw for EC, OC, and dust, respectively,atthebeginningoftheperiod,whichincreasedto4.9,17.2,and1327ppbwforEC,OC,anddust, respectively,attheend. TheECanddustconcentrationswereremarkablyhigherthanthoseatthethree locations in 2011 and the recent measurements at Summit. However, our measurements for EC and OC could be underestimated because a recent study indicates that the collection efficiency of a quartz fiber filter, which we employed, is low. We confirm that the snow surface impurity concentrations were enhanced in the observation period, which can be explained by the effects of sublimation/evaporation and snowmeltamplificationassociatedwithdrasticmelting. Scanningelectronmicroscopyanalysisofsurface snowimpuritiesonJuly12revealedthatthemajorcomponentofsnowimpuritiesismineraldustwithsize larger than 5µm, which suggests possible emission source areas are peripheral bare soil regions of Greenlandand/ortheCanadianArctic.

The mass concentrations of light-absorbing snow impurities at Sapporo, Japan, were measured during six winters from 2007 to 2013. Elemental carbon (EC) and organic carbon (OC) concentrations were measured with the thermal optical method, and dust concentration was determined by filter gravimetric measurement. The measurement results using the different filters were compared to assess the filtration efficiency. Adding NH 4 H 2 PO 4 coagulant to melted snow samples improved the collection efficiency for EC particles by a factor of 1.45. The mass concentrations of EC, OC, and dust in the top 2 cm layer ranged in 0.007-2.8, 0.01-13, and 0.14-260 ppmw, respectively, during the six winters. The mass concentrations and their short-term variations were larger in the surface than in the subsurface. The snow impurity concentrations varied seasonally; that is, they remained relatively low during the accumulation season and gradually increased during the melting season. Although the surface snow impurities showed no discernible trend over the six winters, they varied from year to year, with a negative correlation between the snow impurity concentrations and the amount of snowfall. The surface snow impurities generally increased with the number of days elapsed since snowfall and showed a different rate for EC (1.44), OC (9.96), and dust (6.81). The possible processes causing an increase in surface snow impurities were dry deposition of atmospheric aerosols, melting of surface snow, and sublimation/evaporation of surface snow.

A ground-based spectral radiometer system for albedo and flux (GSAF) was developed to retrieve a mass concentration of snow impurities and effective snow grain size automatically. The GSAF measures spectral albedo and diffuse fraction with a single sensor to omit a radiometric calibration. The deviation from an ideal cosine response of the sensor to insolation is precisely corrected. The snow physical parameters can be retrieved with the GSAF even under cloudy conditions, because the effect of illumination conditions on albedo is considered in a retrieval algorithm. Continuous measurements with the GSAF at two snowfields in Hokkaido, Japan, showed the correlations between the retrieved parameters and in situ measurements (R=0.595 to 0.940).

[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,

Abstract. The surface energy balance (SEB) from 30 June to 14 July 2012 at site SIGMA (Snow Impurity and Glacial Microbe effects on abrupt warming in the Arctic)-A, (78 • 03 N, 67 • 38 W; 1490 m a.s.l.) on the northwest Greenland Ice Sheet (GrIS) was investigated by using in situ atmospheric and snow measurements as well as numerical modeling with a one-dimensional multi-layered physical snowpack model called SMAP (Snow Metamorphism and Albedo Process). At SIGMA-A, remarkable near-surface snowmelt and continuous heavy rainfall (accumulated precipitation between 10 and 14 July was estimated to be 100 mm) were observed after 10 July 2012. Application of the SMAP model to the GrIS snowpack was evaluated based on the snow temperature profile, snow surface temperature, surface snow grain size, and shortwave albedo, all of which the model simulated reasonably well. Above all, the fact that the SMAP model successfully reproduced frequently observed rapid increases in snow albedo under cloudy conditions highlights the advantage of the physically based snow albedo model (PBSAM) incorporated in the SMAP model. Using such data and model, we estimated the SEB at SIGMA-A from 30 June to 14 July 2012. Radiation-related fluxes were obtained from in situ measurements, whereas other fluxes were calculated with the SMAP model. By examining the components of the SEB, we determined that low-level clouds accompanied by a significant temperature increase played an important role in the melt event observed at SIGMA-A. These conditions induced a remarkable surface heating via cloud radiative forcing in the polar region.