Arctic Sea Ice Topography Information From RADARSAT Constellation Mission (RCM) Synthetic Aperture Radar (SAR) Backscatter

Sea ice topography information can be obtained from altimetry but these data are spatially and temporally limited compared to recent synthetic aperture radar (SAR) missions such as the RADARSAT Constellation Mission (RCM). We analyze the relationship between sea ice roughness and height obtained from three Ice, Cloud, and Land Elevation Satellite (ICESat)‐2 tracks on two dates in March 2022, with RCM backscatter from 17 images in the McClintock Channel, Canadian Arctic. We analyze how this relationship varies with ice type, polarization, and incidence angle. We find particularly notable relationships between sea ice roughness and horizontal‐transmit/vertical‐receive backscatter for first‐year ice, and sea ice height and backscatter for multi‐year ice. We develop a preliminary model for winter sea ice roughness retrieval using RCM. In comparison with independent ICESat‐2 data in our study region, we find the model performs effectively at estimating a roughness distribution and key roughness statistics, and characterizes spatial variations in roughness at a sub‐kilometer scale. Plain Language Summary Sea ice topography estimates are important for improving ocean‐climate models, understanding sea ice evolution, and planning ice travel. Estimates can be obtained from altimetry missions, but these data are spatially and/or temporally limited compared to recent synthetic aperture radar missions such as the C‐band RADARSAT Constellation Mission (RCM). By comparing RCM backscatter with measurements of height and roughness obtained using Ice, Cloud, and Land Elevation Satellite (ICESat)‐2 in the Canadian Arctic, we demonstrate the potential for using RCM to estimate sea ice topography. We show there is a notable relationship between sea ice roughness and backscatter on first‐year ice in late winter, particularly in the horizontal‐transmit/vertical‐receive channel, and a notable relationship between sea ice height and backscatter on multi‐year ice. We also observe that the relationship between the RCM signal and roughness varies with incidence angle. Based on this analysis we develop a preliminary model for winter sea ice roughness retrieval using RCM. In comparison with ICESat‐2 data, we find the model performs effectively at estimating key roughness statistics, and characterizes spatial variations in roughness at a sub‐kilometer scale. These findings will facilitate the use of RCM to validate geophysical models, map rough areas of ice, assess ice evolution and dev