Abstract
This study investigates the spatial signatures of seasonal snow in Synthetic Aperture Radar (SAR) observations at different spatial scales and for different physiographic regions. Sentinel-1 C-band (SAR) backscattering coefficients (BSC) were analyzed in the Swiss Alps (SA), in high elevation forest and grasslands in Grand Mesa (GM), Colorado, and in North Dakota (ND) croplands. GM BSC exhibit 10 dB sensitivity to wetness at small scales (~100 m) over homogeneous grassland. Sensitivity decreases to 5 dB in the presence of trees, and it is demonstrated that VH BSC sensitivity enables wet snow mapping below the tree-line. Area-variance scaling relationships show minima at ~100 m and 150–250 m, respectively, in barren and grasslands in SA and GM, increasing up to 1 km and longer in GM forests and ND agricultural fields. The spatial organization of BSC (as described by 1D-directional BSC wavelength spectra) exhibits multi-scaling behavior in the 100–1000 m range with a break at (180–360 m) that is also present in UAVSAR L-band measurements in GM. Spectral slopes in GM forested areas steepen during accumulation and flatten in the melting season with mirror behavior for grasslands reflecting changes in scattering mechanisms with snow depth and wetness, and vegetation mass and structure. Overall, this study reveals persistent patterns of SAR scattering variability spatially organized by land-cover, topography and regional winds with large inter-annual variability tied to precipitation. This dynamic scaling behavior emerges as an integral physical expression of snowpack variability that can be used to model sub-km scales and for downscaling applications.
Highlights
Seasonal snow-covered area (SCA) plays an important role in the Earth’s water cycle
The temporal evolution of Sentinel-1 backscattering coefficients (BSC) sensitivity for Grand Mesa, Swiss Alps, and North Dakota is shown in Figure 9, taking advantage of multiple overpasses of Sentinel-1 C-Band dual-polarization (VV and VH)
This is in contrast with [30], the authors of which reported that the backscattering coefficient for dry snow was 5 dB lower than snow-free conditions at C- band irrespective of the polarization in the Swiss Alps at mid-elevations (~2500 m), which highlights the importance of regional controls in seasonal backscattering
Summary
Seasonal snow-covered area (SCA) plays an important role in the Earth’s water cycle. SCA inter-annual variability is tied to the Earth’s climate because its high surface albedo governs the energy exchange between the land surface and the atmosphere in the cold regions of the world [1,2,3,4], where seasonal snowpacks represent the most important freshwater resource (quantified as snow water equivalent SWE). The temporal evolution of the spectral slope (scaling factor) and local changes in spectral slope (scaling breaks) with scale are interpreted considering the snowpack condition, land-cover, and landform This information can be used to capture (parameterize) scale-aware subgrid-scale variability in coupled snow hydrology–microwave models, and to downscale snow products (e.g., passive microwave) as illustrated by [41] for soil moisture. Supplementary data presented in tables and figures are referred to using the notation S# throughout the manuscript
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