Observations of Thin First Year Sea Ice Using a Suite of Surface Radar, LiDAR, and Drone Sensors

Abstract

Arctic sea ice is rapidly transitioning into a perennial first year ice pack and this is being observed with satellite remote sensing. Satellite image interpretation requires accurate knowledge of the physical conditions and how they give rise to the microwave scattering response that is present within a single image pixel. This study addresses this issue through a focused remote sensing study of thin first year sea ice. We present results from an experiment that fused datasets from surface-based C- and Ku-band polarimetric scatterometers, LiDAR, and drone-based optical and thermal infrared sensors. We grew frost-flower-covered thin first year sea ice in a mesocosm facility and measured the time-series evolution of C- and Ku-band scattering response as it evolved into snow-covered sea ice. Drone surveys, LiDAR scans, and physical sampling provided complementary characterization of the ice. Results quantify the sensitivity of C- and Ku-band to the presence of frost flowers, the addition of snow, and the meteorological conditions. Drone surveys enhanced the characterization by rapidly performing observations over a larger representative region. In essence, they are helping to close the gap between surface-based sensing and satellite imagery. Furthermore, this study complements and enhances our understanding of the snow-covered sea ice system.