Modélisation de l'émission micro-onde du manteau neigeux: applications en Antarctique et au Québec

The cryosphere has a key role in the climate system, among others because it reflects a significant fraction of solar energy reaching the Earth's surface and contains a large amount of fresh water in solid form. Because of the sensitivity of the cryosphere to climatic variables such as temperature and precipitation, the various elements of the cryosphere, such as the Antarctic ice cap and the seasonal snow over the subarctic regions, are indicators of global climate change. However, our knowledge of polar regions are limited by a lack of in situ observations reflecting the remoteness of these regions and the hard weather conditions. The analysis of these sparse observations can be enhanced through remote sensing to reduce uncertainties about climate trends observed at high latitudes. Indeed, remote sensing allows continuous and large-scale observations of polar and subpolar regions. Passive remote sensing, especially in the microwave domain is suitable to interpret and monitor the physical properties of the snowpack. Indeed, the microwave radiation emanates from the ground or snow itself, and then propagates to the surface. Thus, the emerging radiation contains information on vertical variations of snow properties, such as temperature and microstructure properties (grain size and density). These three properties determine the snow microwave emission of a dry snowpack. For wet snowpacks, the liquid water content is the property which dominate the emission. The temporal evolution and vertical variations of these different properties are defined by the metamorphism. Their link with the microwave emission is considered by the radiative transfer. This thesis aims at explaining the microwave emission from snow by forward modeling to understand the evolution of the main physical properties of snow. The radiative transfer in snow has been calculated with the multilayer model Microwave Emission Model of Layered Snowpack (MEMLS) and multilayered Dense Media Radiative Transfer (DMRT-ML), based on semi-empirical and theoretical approaches, respectively. The stratigraphic profiles of snow used as input were measured, randomly generated, modeled with a simple relationship of metamorphism or with the thermodynamic snow evolution model Crocus. These models and approaches have been applied on two types of snow, permanent (Antarctica) and seasonal (Quebec). In the first case, the temporal evolution of brightness temperatures has been modeled locally, at Dome C, from in situ measurements of snow properties. Using this approach, the emissivity is modeled from measurements and is therefore applicable locally. To model the emissivity across Antarctica, various synthetic profiles of grain size and density were tested. In all cases, the vertical variation of grain size appeared crucial to predict the emissivity in vertical polarization. This sensitivity was used to estimate, at the continental scale, the grain size profile, an important glaciological variable. The density profile and surface properties determine the difference between vertical and horizontal polarizations. The microwave emission of a seasonal snowpack in Quebec has also been discussed. The specificity of the study is to predict the timeseries of brightness temperatures with a coupled snow evolution-emission model, here Crocus-MEMLS. This approach allows to finely interpret the temporal evolution of the brightness temperatures measured with a surface based radiometer. In addition, this approach allows to doubt some physical relationships of Crocus. The results highlight the complexity of the microwave signal for snowpacks evolving rapidly at temperatures near the melting point.

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