Toward the Estimation of Oil Slick Thickness on Newly Formed Sea Ice Using C-Band Radar Backscatter

Oil thickness in oil spills involving sea ice is a key parameter required for an effective oil spill response; however, quantifying it from radar backscatter data remains a difficult task. We investigated a possible solution for estimating oil slick thickness by using electromagnetic (EM) forward and inverse scattering models of oil-covered newly formed sea ice (NI). Our forward model employs a first-order approximation of a multilayered small perturbation method (SPM) to predict two copolarization C-band radar backscatters of NI covered by an oil slick with thicknesses ranging from 0 to 7 mm. The results showed that the backscatter decreases as slick thickness increases, which we attributed to signal attenuation within the saline-oil layer. Our inverse model relies on the particle swarm optimization (PSO) algorithm to determine the slick thickness on NI using synthetic backscatter data, and it requires the input of several important ice and oil physical parameters (thickness, dielectrics, and roughness). Moreover, the estimated slick thickness was validated using scatterometer data from an oil-on-ice experiment at the University of Manitoba’s Sea-ice Environmental Research Facility (SERF). With synthetic data, the 5 mm oil slick thickness was overestimated by 25%, while with experimental data, it was overestimated by 8%. Overall, our findings have laid the groundwork for future inversion studies to identify the thickest oil spill zone from current and future C-band radar satellites for immediate response.