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Publication - Dr Jack Landy

    Evaluating Scattering Contributions to C-Band Radar Backscatter From Snow-Covered First-Year Sea Ice at the Winter-Spring Transition Through Measurement and Modeling

    Citation

    Komarov, AS, Landy, JC, Komarov, SA & Barber, DG, 2017, ‘Evaluating Scattering Contributions to C-Band Radar Backscatter From Snow-Covered First-Year Sea Ice at the Winter-Spring Transition Through Measurement and Modeling’. IEEE Transactions on Geoscience and Remote Sensing, vol 55., pp. 5702-5718

    Abstract

    In this paper, we present model and measurement results for time-series angular dependencies of C-band HH and VV normalized radar cross-sections (NRCS) over first-year snow-covered sea ice during a winter-spring transition period. Experimental scatterometer and physical data were collected near Cambridge Bay, Nunavut, Canada, between May 20 and May 28, 2014, covering a severe storm event on May 25. We use the small perturbation scattering theory to model small-scale surface scattering, the Mie scattering theory to estimate the level of volume scattering in snow, and the Kirchhoff physical optics model to compute the large-scale surface scattering component. We observed good agreement between the model and experimental HH and VV NRCS. Before the storm, R² between model and experimental NRCS was 0.88 and 0.82 for VV and HH, respectively. After the storm, R² was 0.81 and 0.78 for VV and HH, respectively. Our model results suggest an overall increase in surface roughness after the storm event, supported by LiDAR measurements of the snow surface topography. Before the storm, the large-scale and small-scale surface scattering from the air-snow interface as well as volume scattering components dominated. After the storm, the large- and small-scale scattering contributions increased, while the volume scattering component considerably dropped. We attribute these effects to the increase in surface roughness and snow moisture content during the poststorm period. Our results could aid in interpretation of time-series synthetic aperture radar images with respect to physical properties of snow and ice during the winter-spring transition period.

    Full details in the University publications repository