Combined airborne profiling over Fram Strait sea ice: Fractional sea-ice types, albedo and thickness measurements


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Christian.Haas [ at ] awi.de

Abstract

This paper presents the data collected during an expedition from the marginal ice zone into the multi year sea ice in the Fram Strait in May-June 2005 to measure the variance in sea-ice types, albedo and thickness. It also describes the techniques used to analyze the data. The principal information from the methodologies applied derives the sea-ice types from digital photography, the spectral and broadband reflectance from spectrometer measurements and the total sea-ice thickness profile from an electromagnetic-probe. A combination of methods was used to extract more information from each data set compared to what traditionally are obtained. The digital images were standardized, textural features extracted and a trained neural network was used for classification, while the optical measurements were normalized and standardized to minimize effects from the set-up and atmospheric conditions. Measurements from June 3rd (before the onset of summer melt) showed that the fractional sea-ice types had large spatial variability, with average fractions for snow-covered sea ice of 81.0%, thick bare ice 4.0%, thin ice 5.3% and open water 9.6%, hence an average ice concentration of 90.3%. The average broadband reflectance factor was 0.73, while the average total sea-ice thickness (including snow) was 2.1 m. Relative high correlations were found between the measured albedo and sea-ice concentration (0.69). The paper also addresses the lessons learned for future fusion of data from large field campaigns. © 2008 Elsevier B.V. All rights reserved.



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Eprint ID
18656
DOI https://www.doi.org/10.1016/j.coldregions.2008.08.004

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Pedersen, C. , Hall, R. , Gerland, S. , Sivertsen, A. , Svenøe, T. and Haas, C. (2009): Combined airborne profiling over Fram Strait sea ice: Fractional sea-ice types, albedo and thickness measurements , Cold Regions Science and Technology, 55 (1), pp. 23-32 . doi: https://www.doi.org/10.1016/j.coldregions.2008.08.004


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