Preprint Technical Note Version 1 This version is not peer-reviewed

Arctic Sea Ice Surface Roughness Derived from Multi-Angular Reflectance Satellite Imagery

Version 1 : Received: 21 October 2018 / Approved: 22 October 2018 / Online: 22 October 2018 (09:50:48 CEST)

A peer-reviewed article of this Preprint also exists.

Nolin, A.W.; Mar, E. Arctic Sea Ice Surface Roughness Estimated from Multi-Angular Reflectance Satellite Imagery. Remote Sens. 2019, 11, 50. Nolin, A.W.; Mar, E. Arctic Sea Ice Surface Roughness Estimated from Multi-Angular Reflectance Satellite Imagery. Remote Sens. 2019, 11, 50.

Journal reference: Remote Sens. 2018, 11, 50
DOI: 10.3390/rs11010050

Abstract

Sea ice surface roughness affects ice-atmosphere interactions, serves as an indicator of ice age, shows patterns of ice convergence and divergence, affects the spatial extent of summer melt ponds, and ice albedo. We have developed a method for mapping sea ice surface roughness using angular reflectance data from the Multi-angle Imaging SpectroRadiometer (MISR) and lidar-derived roughness measurements from the Airborne Topographic Mapper (ATM). Using an empirical data modeling approach, we derived estimates of Arctic sea ice roughness ranging from centimeters to decimeters meters within the MISR 275-m pixel size. Using independent ATM data for validation, we find that histograms of lidar and multi-angular roughness values are nearly identical for areas with roughness <20 cm but that for rougher regions, the MISR-derived roughness has a narrower range of values than the ATM data. The algorithm is able to accurately identify areas that transition between smooth and rough ice. Because of its coarser spatial scale, MISR-derived roughness data have a variance of about half that ATM roughness data.

Subject Areas

ice; surface roughness; remote sensing; MISR

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