Abstract. To evaluate the impact of vapor diffusion on isotopic composition variations in snow pits and then in ice cores, we introduced water isotopes in the detailed snowpack model Crocus. At each step and for each snow layer, (1) the initial isotopic composition of vapor is taken at equilibrium with the solid phase, (2) a kinetic fractionation is applied during transport, and (3) vapor is condensed or snow is sublimated to compensate for deviation to vapor pressure at saturation.

We study the different effects of temperature gradient, compaction, wind compaction, and precipitation on the final vertical isotopic profiles. We also run complete simulations of vapor diffusion along isotopic gradients and of vapor diffusion driven by temperature gradients at GRIP, Greenland and at Dome C, Antarctica over periods of 1 or 10 years. The vapor diffusion tends to smooth the original seasonal signal, with an attenuation of 7 to 12% of the original signal over 10 years at GRIP. This is smaller than the observed attenuation in ice cores, indicating that the model attenuation due to diffusion is underestimated or that other processes, such as ventilation, influence attenuation. At Dome C, the attenuation is stronger (18%), probably because of the lower accumulation and stronger δ¹⁸O gradients.

Abstract. This study aims to better understand and quantify the uncertainties in microwave snow emission models using the Dense Media Radiative Theory Multi-Layer model (DMRT-ML) with in situ measurements of snow properties. We use surface-based radiometric measurements at 10.67, 19 and 37 GHz in boreal forest and subarctic environments and a new in situ data set of measurements of snow properties (profiles of density, snow grain size and temperature, soil characterization and ice lens detection) acquired in the James Bay and Umiujaq regions of Northern Québec, Canada. A snow excavation experiment – where snow was removed from the ground to measure the microwave emission of bare frozen ground – shows that small-scale spatial variability (less than 1 km) in the emission of frozen soil is small. Hence, in our case of boreal organic soil, variability in the emission of frozen soil has a small effect on snow-covered brightness temperature (T_B). Grain size and density measurement errors can explain the errors at 37 GHz, while the sensitivity of T_B at 19 GHz to snow increases during the winter because of the snow grain growth that leads to scattering. Furthermore, the inclusion of observed ice lenses in DMRT-ML leads to significant improvements in the simulations at horizontal polarization (H-pol) for the three frequencies (up to 20 K of root mean square error). However, representation of the spatial variability of T_B remains poor at 10.67 and 19 GHz at H-pol given the spatial variability of ice lens characteristics and the difficulty in simulating snowpack stratigraphy related to the snow crust. The results also show that, in our study with the given forest characteristics, forest emission reflected by the snow-covered surface can increase the T_B up to 40 K. The forest contribution varies with vegetation characteristics and a relationship between the downwelling contribution of vegetation and the proportion of pixels occupied by vegetation (trees) in fisheye pictures was found. We perform a comprehensive analysis of the components that contribute to the snow-covered microwave signal, which will help to develop DMRT-ML and to improve the required field measurements. The analysis shows that a better consideration of ice lenses and snow crusts is essential to improve T_B simulations in boreal forest and subarctic environments.