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Volume 9, issue 5 | Copyright
The Cryosphere, 9, 1797-1817, 2015
https://doi.org/10.5194/tc-9-1797-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 15 Sep 2015

Research article | 15 Sep 2015

Inter-comparison and evaluation of sea ice algorithms: towards further identification of challenges and optimal approach using passive microwave observations

N. Ivanova1, L. T. Pedersen2, R. T. Tonboe2, S. Kern3, G. Heygster4, T. Lavergne5, A. Sørensen5, R. Saldo6, G. Dybkjær2, L. Brucker7,8, and M. Shokr9 N. Ivanova et al.
  • 1Nansen Environmental and Remote Sensing Center, Bergen, Norway
  • 2Danish Meteorological Institute, Copenhagen, Denmark
  • 3University of Hamburg, Hamburg, Germany
  • 4University of Bremen, Bremen, Germany
  • 5Norwegian Meteorological Institute, Oslo, Norway
  • 6Technical University of Denmark, Lyngby, Denmark
  • 7NASA Goddard Space Flight Center, Cryospheric Sciences Laboratory, Code 615, Greenbelt, Maryland 20771, USA
  • 8Universities Space Research Association, Goddard Earth Sciences Technology and Research Studies and Investigations, Columbia, Maryland 21044, USA
  • 9Environment Canada, Ontario, Canada

Abstract. Sea ice concentration has been retrieved in polar regions with satellite microwave radiometers for over 30 years. However, the question remains as to what is an optimal sea ice concentration retrieval method for climate monitoring. This paper presents some of the key results of an extensive algorithm inter-comparison and evaluation experiment. The skills of 30 sea ice algorithms were evaluated systematically over low and high sea ice concentrations. Evaluation criteria included standard deviation relative to independent validation data, performance in the presence of thin ice and melt ponds, and sensitivity to error sources with seasonal to inter-annual variations and potential climatic trends, such as atmospheric water vapour and water-surface roughening by wind. A selection of 13 algorithms is shown in the article to demonstrate the results. Based on the findings, a hybrid approach is suggested to retrieve sea ice concentration globally for climate monitoring purposes. This approach consists of a combination of two algorithms plus dynamic tie points implementation and atmospheric correction of input brightness temperatures. The method minimizes inter-sensor calibration discrepancies and sensitivity to the mentioned error sources.

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Thirty sea ice algorithms are inter-compared and evaluated systematically over low and high sea ice concentrations, as well as in the presence of thin ice and melt ponds. A hybrid approach is suggested to retrieve sea ice concentration globally for climate monitoring purposes. This approach consists of a combination of two algorithms plus the implementation of a dynamic tie point and atmospheric correction of input brightness temperatures.
Thirty sea ice algorithms are inter-compared and evaluated systematically over low and high sea...
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