[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.

Band bending is a fundamental issue for discussing organic devices. Band bending with Fermi level alignment between semiconductors and metals are often assumed, although the validity of this scheme in the case of organic semiconductors has been not yet established. In this paper, our recent efforts to examine band bending in organic semiconductors using Kelvin probe method (KPM) are reported. After discussing the applicability of KPM to organic thick film -metal substrate system, the results for C 60 , TPD, and Alq 3 are shown to discuss band bending of the films without intentional doping in ultrahigh vacuum condition. Gradual band bending was observed for C 60 /metal interfaces although the width of the space charge layer is in the order of 100 nm. In contrast, flat band feature was observed for TPD/metal interfaces probably because of its high purity. These results demonstrate that the frame work of band bending used in inorganic semiconductor interfaces is still valid for organic semiconductors although much thicker films are often necessary to achieve bulk Fermi level alignment. For Alq 3 / metal interfaces formed in dark condition, we found a new type of band bending where the energy levels change as a linear function of the distance from the interface. The observed location of the vacuum level was far below the Fermi level of the metal substrates, clearly indicating that Fermi level varies place by place in the system. Such electronically non-equilibrium state was quite stable for the order of years. The concept of Fermi level alignment is also discussed in relation to the observed energy diagrams.

We have studied the initial stages of oxidation of the hydrogen-terminated Si(111) and (100) surfaces stored in air, using infrared spectroscopy in the multiple internal reflection geometry. We investigate the effect of surface roughness and humidity of air on the oxidation of the hydrogen-terminated Si surfaces. We suggest that surface roughness on a microscopic scale does not significantly affect the oxidation of the hydrogen-terminated Si surface and the oxidation occurs on the entire surface. It is demonstrated that water is predominantly involved in the oxidation of the surface Si—H bond, and that the surface Si—H bond is quite inert to the oxygen molecule.

Abstract. Observations and models agree that the Greenland Ice Sheet (GrIS) surface mass balance (SMB) has decreased since the end of the 1990s due to an increase in meltwater runoff and that this trend will accelerate in the future. However, large uncertainties remain, partly due to different approaches for modelling the GrIS SMB, which have to weigh physical complexity or low computing time, different spatial and temporal resolutions, different forcing fields, and different ice sheet topographies and extents, which collectively make an inter-comparison difficult. Our GrIS SMB model intercomparison project (GrSMBMIP) aims to refine these uncertainties by intercomparing 13 models of four types which were forced with the same ERA-Interim reanalysis forcing fields, except for two global models. We interpolate all modelled SMB fields onto a common ice sheet mask at 1 km horizontal resolution for the period 1980–2012 and score the outputs against (1) SMB estimates from a combination of gravimetric remote sensing data from GRACE and measured ice discharge; (2) ice cores, snow pits and in situ SMB observations; and (3) remotely sensed bare ice extent from MODerate-resolution Imaging Spectroradiometer (MODIS). Spatially, the largest spread among models can be found around the margins of the ice sheet, highlighting model deficiencies in an accurate representation of the GrIS ablation zone extent and processes related to surface melt and runoff. Overall, polar regional climate models (RCMs) perform the best compared to observations, in particular for simulating precipitation patterns. However, other simpler and faster models have biases of the same order as RCMs compared with observations and therefore remain useful tools for long-term simulations or coupling with ice sheet models. Finally, it is interesting to note that the ensemble mean of the 13 models produces the best estimate of the present-day SMB relative to observations, suggesting that biases are not systematic among models and that this ensemble estimate can be used as a reference for current climate when carrying out future model developments. However, a higher density of in situ SMB observations is required, especially in the south-east accumulation zone, where the model spread can reach 2 m w.e. yr−1 due to large discrepancies in modelled snowfall accumulation.

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.