Abstract
AbstractTwo satellite datasets are used to characterize winter landfast first-year sea-ice (FYI), deformed FYI (DFYI) and multiyear sea-ice (MYI) roughness in the Canadian Arctic Archipelago (CAA): (1) optical Multi-angle Imaging SpectroRadiometer (MISR) and (2) synthetic aperture radar Sentinel-1. The Normalized Difference Angular Index (NDAI) roughness proxy derived from MISR, and backscatter from Sentinel-1 are intercompared. NDAI and backscatter are also compared to surface roughness derived from an airborne LiDAR track covering a subset of FYI and MYI (no DFYI). Overall, NDAI and backscatter are significantly positively correlated when all ice type samples are considered. When individual ice types are evaluated, NDAI and backscatter are only significantly correlated for DFYI. Both NDAI and backscatter are correlated with LiDAR-derived roughness (r= 0.71 andr= 0.74, respectively). The relationship between NDAI and roughness is greater for MYI than FYI, whereas for backscatter and ice roughness, the relationship is greater for FYI than MYI. Linear regression models are created for the estimation of FYI and MYI roughness from NDAI, and FYI roughness from backscatter. Results suggest that using a combination of Sentinel-1 backscatter for FYI and MISR NDAI for MYI may be optimal for mapping winter sea-ice roughness in the CAA.
Highlights
Sea-ice surface roughness is heterogeneous in time and space, with seasonal and multiyear ice types undergoing thermodynamic and dynamic-deformation processes
Better functionality of Normalized Difference Angular Index (NDAI) for rougher surfaces is seen in our study, with significant correlations found between NDAI and roughness for multiyear sea-ice (MYI), and between NDAI and HH backscatter for deformed FYI (DFYI)
A broad-scale inter-comparison was done of the Multi-angle Imaging SpectroRadiometer (MISR)-derived roughness index NDAI and calibrated HH backscatter from Sentinel-1 for an area of winter sea ice comprising first-year sea-ice (FYI), DFYI and MYI
Summary
Sea-ice surface roughness is heterogeneous in time and space, with seasonal and multiyear ice types undergoing thermodynamic and dynamic-deformation processes. Macroscale sea-ice topography is characterized by a range of features, including level, undeformed sea ice; structures formed by convergent or divergent stressors like pressure ridges, cracks, leads, ice rubble, rafted ice and hummocks; snow features like sastrugi, dunes and variable depth; and melt features like saturated snow (slush) and meltwater ponds. These surface features are linked to season; atmospheric and oceanic forcing; and ice qualities like ice age, salt content and thickness (Weeks and Ackley, 1982). Sea-ice surface topography (hereafter roughness) is an active area of research across many disciplines, involving a wide variety of sensors and methods of measurement
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