Abstract
This study compares numerical simulations and observations of C-band radar backscatter in a wide region (2300 km 2 ) in the Northern French Alps. Numerical simulations were performed using a model chain composed of the SAFRAN meteorological reanalysis, the Crocus snowpack model and the radiative transfer model Microwave Emission Model for Layered Snowpacks (MEMLS3&a), operating at a spatial resolution of 250-m. The simulations, without any bias correction, were evaluated against 141 Sentinel-1 synthetic aperture radar observation scenes with a resolution of 20 m over three snow seasons from October 2014 to June 2017. Results show that there is good agreement between observations and simulations under snow-free or dry snow conditions, consistent with the fact that dry snow is almost transparent at C-band. Under wet snow conditions, although the changes in time and space are well correlated, there is a significant deviation, up to 5 dB, between observations and simulations. The reasons for these discrepancies were explored, including a sensitivity analysis on the impact of the liquid water percolation scheme in Crocus. This study demonstrates the feasibility of performing end-to-end simulations of radar backscatter over extended geographical region. This makes it possible to envision data assimilation of radar data into snowpack models in the future, pending that deviations are mitigated, either through bias corrections or improved physical modeling of both snow properties and corresponding radar backscatter.
Highlights
Monitoring and predicting snow conditions in mountain regions is critical for avalanche forecasting, water resource and flood risk management, and mountain tourism activities
We evaluated simulations of the backscatter coefficients obtained using the model chain SAFRAN-Crocus-MEMLS3&a against observation scenes from Sentinel-1 during three snow seasons from October 2014 to June 2017 over a large study area in the French Alps
Simulations were performed at a 250-m resolution, and compared to 141 observation scenes, without any bias correction applied to model results
Summary
Monitoring and predicting snow conditions in mountain regions is critical for avalanche forecasting, water resource and flood risk management, and mountain tourism activities. Microwave backscatter coefficients over snow result from the combination of several phenomena including reflection on the snow surface, scattering within the snowpack and reflection at the snow–soil boundary This depends, in particular, on internal snow properties such as the layering of microstructure variables (density, specific surface area, etc.) and liquid water content [4]. Most previous studies were carried out at the point scale, using in-situ snow observations or using in-situ meteorological observations to drive snowpack models, and comparing to in-situ SAR observations rather than from satellite-borne sensors While they demonstrated potential in using such data for larger scale use operationally, few studies have attempted to simulate explicitly radar backscatter at the regional scale, this is a prerequisite for data assimilation in snowpack models.
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