1D-Var multilayer assimilation of X-band SAR data into a detailed snowpack model

The structure and physical properties of a snow- pack and their temporal evolution may be simulated using meteorological data and a snow metamorphism model. Such an approach may meet limitations related to potential diver- gences and accumulated errors, to a limited spatial resolu- tion, to wind or topography-induced local modulations of the physical properties of a snow cover, etc. Exogenous data are then required in order to constrain the simulator and im- prove its performance over time. Synthetic-aperture radars (SARs) and, in particular, recent sensors provide reflectivity maps of snow-covered environments with high temporal and spatial resolutions. The radiometric properties of a snowpack measured at sufficiently high carrier frequencies are known to be tightly related to some of its main physical parame- ters, like its depth, snow grain size and density. SAR acqui- sitions may then be used, together with an electromagnetic backscattering model (EBM) able to simulate the reflectiv- ity of a snowpack from a set of physical descriptors, in or- der to constrain a physical snowpack model. In this study, we introduce a variational data assimilation scheme coupling TerraSAR-X radiometric data into the snowpack evolution model Crocus. The physical properties of a snowpack, such as snow density and optical diameter of each layer, are simu- lated by Crocus, fed by the local reanalysis of meteorological data (SAFRAN) at a French Alpine location. These snow- pack properties are used as inputs of an EBM based on dense media radiative transfer (DMRT) theory, which simulates the total backscattering coefficient of a dry snow medium at X and higher frequency bands. After evaluating the sensi- tivity of the EBM to snowpack parameters, a 1D-Var data assimilation scheme is implemented in order to minimize the discrepancies between EBM simulations and observa- tions obtained from TerraSAR-X acquisitions by modifying the physical parameters of the Crocus-simulated snowpack. The algorithm then re-initializes Crocus with the modified snowpack physical parameters, allowing it to continue the simulation of snowpack evolution, with adjustments based on remote sensing information. This method is evaluated us- ing multi-temporal TerraSAR-X images acquired over the specific site of the Argentiere glacier (Mont-Blanc massif, French Alps) to constrain the evolution of Crocus. Results indicate that X-band SAR data can be taken into account to modify the evolution of snowpack simulated by Crocus.

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