A study of sea ice topography in the Weddell and Ross seas using dual-polarimetric TanDEM-X imagery

• Published in: The Cryosphere
• Main Authors: Huang, Lanqing, Hajnsek, Irena
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2024
• Subjects: Radarkonzepte; Antarctic; Ross Sea; The Antarctic; Weddell; Weddell Sea; Antarc*; Sea ice; The Cryosphere
• Online Access: https://elib.dlr.de/211022/; https://tc.copernicus.org/articles/18/3117/2024/

The total freeboard, which is the ice layer above water level and includes the snow thickness, is needed to retrieve the ice thickness and ice surface topography. Single-pass interferometric synthetic aperture radar (InSAR) allows for the generation of digital elevation models (DEMs) over the drifting sea ice. However, accurate sea ice DEMs (i.e., the total freeboard) derived from InSAR are impeded due to variation in the penetration of the radar signals into the snow and ice layers. This research introduces a novel methodology for retrieving sea ice DEMs using dual-polarization interferometric SAR images, considering the variation in radar penetration bias across multiple ice types. The accuracy of the method is verified through photogrammetric measurements, demonstrating that the derived DEM has a root-mean-square error of 0.26 m over a 200 km ×19 km area. The method is further applied to broader regions in the Weddell Sea and the Ross Sea, offering new insights into the regional variations of the sea ice topography in the Antarctic. We also characterize the non-Gaussian statistical behavior of the total freeboard using log-normal and exponential-normal distributions. The results suggest that the exponential-normal distribution is superior in the thicker-sea-ice region (average total freeboard >0.5 m), whereas the two distributions exhibit similar performance in the thinner-ice region (average total freeboard <0.5 m). These findings offer an in-depth representation of the total freeboard and roughness in the Weddell and Ross seas. The novel methodology introduced here can be conducted on time series data to comprehend the dynamics of the sea ice, including its growth and deformation.