Articles | Volume 9, issue 5
The Cryosphere, 9, 1797–1817, 2015
The Cryosphere, 9, 1797–1817, 2015

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. Ivanova et al.

Related authors

The impact of melt ponds on summertime microwave brightness temperatures and sea-ice concentrations
Stefan Kern, Anja Rösel, Leif Toudal Pedersen, Natalia Ivanova, Roberto Saldo, and Rasmus Tage Tonboe
The Cryosphere, 10, 2217–2239,,, 2016
Short summary
Error assessment of satellite-derived lead fraction in the Arctic
Natalia Ivanova, Pierre Rampal, and Sylvain Bouillon
The Cryosphere, 10, 585–595,,, 2016
Short summary
Uncertainties in Arctic sea ice thickness and volume: new estimates and implications for trends
M. Zygmuntowska, P. Rampal, N. Ivanova, and L. H. Smedsrud
The Cryosphere, 8, 705–720,,, 2014

Related subject area

Sea Ice
The influence of snow on sea ice as assessed from simulations of CESM2
Marika M. Holland, David Clemens-Sewall, Laura Landrum, Bonnie Light, Donald Perovich, Chris Polashenski, Madison Smith, and Melinda Webster
The Cryosphere, 15, 4981–4998,,, 2021
Short summary
Meltwater sources and sinks for multiyear Arctic sea ice in summer
Don Perovich, Madison Smith, Bonnie Light, and Melinda Webster
The Cryosphere, 15, 4517–4525,,, 2021
Short summary
An X-ray micro-tomographic study of the pore space, permeability and percolation threshold of young sea ice
Sönke Maus, Martin Schneebeli, and Andreas Wiegmann
The Cryosphere, 15, 4047–4072,,, 2021
Short summary
Calibration of sea ice drift forecasts using random forest algorithms
Cyril Palerme and Malte Müller
The Cryosphere, 15, 3989–4004,,, 2021
Short summary
Multiscale variations in Arctic sea ice motion and links to atmospheric and oceanic conditions
Dongyang Fu, Bei Liu, Yali Qi, Guo Yu, Haoen Huang, and Lilian Qu
The Cryosphere, 15, 3797–3811,,, 2021
Short summary

Cited articles

Andersen, S., Tonboe, R., Kern, S., and Schyberg, H.: Improved retrieval of sea ice total concentration from spaceborne passive microwave observations using numerical weather prediction model fields: an intercomparison of nine algorithms, Remote Sens. Environ., 104, 374–392, 2006.
Andersen, S., Tonboe, R., Kaleschke, L., Heygster, G., and Pedersen, L. T.: Intercomparison of passive microwave sea ice concentration retrievals over the high-concentration Arctic sea ice, J. Geophys. Res., 112, C08004,, 2007.
Ashcroft, P. and Wentz, F. J.: AMSR-E/Aqua L2A Global Swath Spatially-Resampled Brightness Temperatures, Version 2, NASA DAAC at the National Snow and Ice Data Center, Boulder, Colorado USA,, 2003.
Brucker, L., Cavalieri, D. J., Markus, T., and Ivanoff, A.: NASA Team 2 Sea Ice Concentration Algorithm Retrieval Uncertainty, IEEE T. Geosci. Remote, 52, 7336–7352,, 2014.
Cavalieri, D. J.: A microwave technique for mapping thin sea ice, J. Geophys. Res., 99, 12561–12572,, 1994.
Short summary
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.