Relationship between Microwave-Derived Snow Thickness on Winter First-Year Sea Ice and Melt-Pond Fraction - Ramjan, Saroat (Arts, 2018)
Early summer melt pond fraction is predicted using late winter C-band backscatter of snow-covered first-year sea ice. Considering the association between melt pond fraction and winter were collected during the 2012 field campaign in Resolute Passage, Nunavut, Canada on relatively smooth first year sea ice to estimate the aerial melt pond fractions. RADARSAT-2 Synthetic Aperture Radar (SAR) data were acquired over the study area in late winter. The correlations between the aerial melt pond fractions and late winter SAR parameters (e.g., linear and polarimetric) and texture measures derived from SAR parameters, are utilized to develop multivariate regression models. These regression models are finally employed to predict melt pond fractions. Results demonstrate substantial capability of the regression models to predict melt pond fractions at near range and far range incidence angles (RMSE = 0.11), compared to the mid-range (RMSE = 0.16). These predictions also act as a proxy to estimate the snow thickness variability, as higher pond fraction evolves from the thinner snow cover. We also found that the strength of the regression models enhances when we combined SAR parameters with texture measures. The results also indicate that at far range incidence angles, SAR polarimetric data are needed, whereas for near range and mid-range, linear SAR data are adequate.