A dense medium electromagnetic scattering model for the InSAR correlation of snow

Abstract

AbstractSnow characteristics, such as snow water equivalent (SWE) and snow grain size, are important characteristics for the monitoring of the global hydrological cycle and as indicators of climate change. This paper derives an interferometric synthetic aperture radar (InSAR) scattering model for dense media, such as snow, which takes into account multiple scattering effects through the Quasi‐Crystalline Approximation. The result of this derivation is a simplified version of the InSAR correlation model derived for relating the InSAR correlation measurements to the snowpack characteristics of grain size, volume fraction, and layer depth as well as those aspects of the volume‐ground interaction that affects the interferometric observation (i.e., the surface topography and the ratio of ground‐to‐volume scattering). Based on the model, the sensitivity of the InSAR correlation measurements to the snow characteristics is explored by simulation. Through this process, it is shown that Ka‐band InSAR phase has a good sensitivity to snow grain size and volume fraction, while for lower frequency signals (Ku‐band to L‐band), the InSAR correlation magnitude and phase have a sensitivity to snow depth. Since the formulation depends, in part, on the pair distribution function, three functional forms of the pair distribution function are implemented and their effects on InSAR phase measurements compared. The InSAR scattering model described in this paper is intended to be an observational prototype for future Ka‐band and L‐band InSAR missions, such as NASA's Surface Water and Ocean Topography and NASA‐ISRO Synthetic Aperture Radar missions, planned for launch in the 2020–2021 time frame. This formulation also enables further investigation of the InSAR‐based snow retrieval approaches.