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Snow depth on arctic sea ice derived from radar: in situ comparisons and time series analysis

Holt, Benjamin et al.

Journal of geophysical research. Oceans. VOL 120; NUMBER 6, ; 2015, 4260-4287 -- John Wiley & Sons, Ltd

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  • Title:
    Snow depth on arctic sea ice derived from radar: in situ comparisons and time series analysis
  • Author: Holt, Benjamin;
    Johnson, Michael P.;
    Perkovic�Martin, Dragana;
    Panzer, Ben
  • Found In: Journal of geophysical research. Oceans. VOL 120; NUMBER 6, ; 2015, 4260-4287
  • Journal Title: Journal of geophysical research. Oceans.
  • Subjects: Earth Sciences; Environment; Dewey: 551.4605
  • Publication Details: John Wiley & Sons, Ltd
  • Language: English
  • Abstract: The snow radar being flown on NASA's Operation IceBridge, ongoing aircraft campaigns to the Arctic and the Antarctic are providing unique observations of the depth of snow on the sea ice cover. In this paper, we focus on the radarâ€?derived snow depth results from the 2009–2012 Arctic campaigns. We develop and evaluate the use of a distinct snow layer tracker to measure snow depth based on a Support Vector Machine (SVM) supervised learning algorithm. The snow radar is designed to detect both the airâ€?snow and snowâ€?ice interfaces using ultrawideband frequencies from 2 to 8 GHz. The quality, errors, and repeatability of the snow radar snow depth estimates are examined, based on comparisons with in situ data obtained during two separate sea ice field campaigns, the GreenArc 2009 and the CryoVEx 2011 campaigns off Greenland in the Lincoln Sea. Finally, we analyze 4 years (2009–2012) of three annually repeated sea ice flight lines obtained in early spring, located off Greenland and the Canadian Arctic. We examine the annual variations of snow depth differences between perennial and seasonal ice when available. Overall, the snow layer tracker produced consistent, accurate results for snow depths between 0.10 and ∼0.60 m. This was confirmed with comparisons with the two data sets from the in situ measurement campaigns as well as with the time series analysis, and is consistent with other published results.
  • Identifier: System Number: ETOCRN389234781; Journal ISSN: 2169-9275
  • Publication Date: 2015
  • Physical Description: Electronic
  • Accrual Information: Monthly
  • Shelfmark(s): 4995.005000
  • UIN: ETOCRN389234781

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