Exploration of C-band synthetic aperture RADAR (SAR) backscatter dependence on snow-mass related information
Abstract
Snow plays a significant role in the Earth's water and energy budgets, and impacts climate variability across regional and continental scales. The utility of remotely-sensed measurements of C-band synthetic aperture radar (SAR) in observing the spatiotemporal dynamics of terrestrial snow is explored here. Observations of C-band SAR backscatter derived from Sentinel-1A/1B are considered a signal of opportunity in estimating snow mass and snow wetness given the sensitivity of C-band backscatter to the dielectric properties of snow while providing observations at a relatively fine spatial scale and at multiple polarizations. Accordingly, cross-polarized (σVV) and co-polarized (σVH) backscatter observations from Sentinel-1A/1B were evaluated against snow water equivalent (SWE) and snow depth measurementsfrom ground-based observational networks as well as land surface model (LSM) output over western Colorado. Backscatter observations were also compared against a number of geophysical variables that were modeled using the NOAH-Multiparameterization (NOAH-MP) LSM with Modern-Era Retrospective analysis for Research and Application, Version 2 (MERRA2) meteorological fields as the boundary conditions. The results suggest that C-band SAR backscatter exhibits a reasonable correlation structure with SWE, snow depth, and snow wetness. However, results also yield moderate correlation coefficients with other geophysical variables such as soil moisture, near-surface soil temperature, and near-surface air temperature. This suggests that C-band backscatter contains some information content related to snow mass as well as other hydro-meteorological variables. Additionally, comparison of backscatter and snowpack information (e.g., SWE and snow depth) suggests that the influence of overlying vegetation and complex terrain also has a significant influence on the backscatter. In summary, these results tell a cautionary tale on the efficacy of C-band backscatter and assimilation into an advanced land surface model for the purpose of improving snow mass estimates, but that continued exploration on the topic is merited.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFM.C33E1640F
- Keywords:
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- 0736 Snow;
- CRYOSPHERE;
- 0740 Snowmelt;
- CRYOSPHERE;
- 0758 Remote sensing;
- CRYOSPHERE;
- 1863 Snow and ice;
- HYDROLOGY