Journal
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
Volume 45, Issue 10, Pages 3131-3137Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2007.895419
Keywords
Arctic; remote sensing; scatterometry; sea ice
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Enhanced-resolution QuikSCAT/SeaWinds (QS(er)) data recently entered the daily ice chart operation of the national ice services. Algorithms have been developed to extract four important sea ice parameters from this data over the whole Arctic: sea ice edge, type, concentration, and drift. This paper will summarize the different algorithms with a more detailed presentation of the sea ice concentration (IQ algorithm that has not been previously published. The sea ice edge can be detected to IC as low as 10%. Sea ice types can be roughly separated by a single threshold of -12 dB in the horizontal polarization. The IC algorithm gives reasonable qualitative results, separating into three classes: high, medium, and low ICs. It resolves even some characteristic ice features in the marginal ice zone and dynamic areas like the Fram Strait. However, it is very empirical and quantitatively not reliable. Sea ice drift can be determined with an accuracy of about 2.6 cm/s for a 48-h drift. Operating since 1999, QS is an important global data set for climate research, and two crucial applications how these sea ice products can be used for climate research are presented: the seasonal evolution of the sea ice cover and the export of sea ice volume through Fram Strait.
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