Snow thickness estimation using correlation functions at C-band

An accurate measurement of snow-layer thickness on the ground is a critical process for estimating the equivalent water content of snow. Previous studies were mainly based on the analysis of the backscattering cross-section of two co-polarized signals at different frequencies. The snow thickness was inferred by comparison with the analytical model. Recently, we have applied the angular and frequency correlation functions (ACF/FCF) for the estimation of sea-ice thickness. One of the advantages of the ACF/FCF method is suppression of the interfering volume scattering, which results in better accuracy and reliability of thickness estimation. We apply a simplified 1D three-layer model for the analysis. The layers are air, snow, and ground. The interfaces between layers are modeled as rough surfaces. Within the layers, there are small inclusions which introduce the volume scattering. Rough surfaces are modeled by the Kirchhoff approximation methods. The volume scattering is calculated using the quasi-crystalline approximation with coherent potential approximation (QCA-CP) for small particles. The ACF/FCF works by correlating two signals with different frequencies and/or incident angles. Using this model, we can determine the behavior of ACF/FCF and use it for snow thickness retrieval