Articles | Volume 10, issue 5
The Cryosphere, 10, 2275–2290, 2016
https://doi.org/10.5194/tc-10-2275-2016
The Cryosphere, 10, 2275–2290, 2016
https://doi.org/10.5194/tc-10-2275-2016

Research article 28 Sep 2016

Research article | 28 Sep 2016

The EUMETSAT sea ice concentration climate data record

Rasmus T. Tonboe et al.

Related authors

Deriving Arctic 2 m air temperatures over snow and ice from satellite surface temperature measurements
Pia Nielsen-Englyst, Jacob L. Høyer, Kristine S. Madsen, Rasmus T. Tonboe, Gorm Dybkjær, and Sotirios Skarpalezos
The Cryosphere, 15, 3035–3057, https://doi.org/10.5194/tc-15-3035-2021,https://doi.org/10.5194/tc-15-3035-2021, 2021
Short summary
Simulated Ka- and Ku-band radar altimeter height and freeboard estimation on snow-covered Arctic sea ice
Rasmus T. Tonboe, Vishnu Nandan, John Yackel, Stefan Kern, Leif Toudal Pedersen, and Julienne Stroeve
The Cryosphere, 15, 1811–1822, https://doi.org/10.5194/tc-15-1811-2021,https://doi.org/10.5194/tc-15-1811-2021, 2021
Short summary
Surface-based Ku- and Ka-band polarimetric radar for sea ice studies
Julienne Stroeve, Vishnu Nandan, Rosemary Willatt, Rasmus Tonboe, Stefan Hendricks, Robert Ricker, James Mead, Robbie Mallett, Marcus Huntemann, Polona Itkin, Martin Schneebeli, Daniela Krampe, Gunnar Spreen, Jeremy Wilkinson, Ilkka Matero, Mario Hoppmann, and Michel Tsamados
The Cryosphere, 14, 4405–4426, https://doi.org/10.5194/tc-14-4405-2020,https://doi.org/10.5194/tc-14-4405-2020, 2020
Short summary
Simultaneous estimation of wintertime sea ice thickness and snow depth from space-borne freeboard measurements
Hoyeon Shi, Byung-Ju Sohn, Gorm Dybkjær, Rasmus Tage Tonboe, and Sang-Moo Lee
The Cryosphere, 14, 3761–3783, https://doi.org/10.5194/tc-14-3761-2020,https://doi.org/10.5194/tc-14-3761-2020, 2020
Short summary
Satellite passive microwave sea-ice concentration data set inter-comparison for Arctic summer conditions
Stefan Kern, Thomas Lavergne, Dirk Notz, Leif Toudal Pedersen, and Rasmus Tonboe
The Cryosphere, 14, 2469–2493, https://doi.org/10.5194/tc-14-2469-2020,https://doi.org/10.5194/tc-14-2469-2020, 2020
Short summary

Related subject area

Sea Ice
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, https://doi.org/10.5194/tc-15-4517-2021,https://doi.org/10.5194/tc-15-4517-2021, 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, https://doi.org/10.5194/tc-15-4047-2021,https://doi.org/10.5194/tc-15-4047-2021, 2021
Short summary
Calibration of sea ice drift forecasts using random forest algorithms
Cyril Palerme and Malte Müller
The Cryosphere, 15, 3989–4004, https://doi.org/10.5194/tc-15-3989-2021,https://doi.org/10.5194/tc-15-3989-2021, 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, https://doi.org/10.5194/tc-15-3797-2021,https://doi.org/10.5194/tc-15-3797-2021, 2021
Short summary
The flexural strength of bonded ice
Andrii Murdza, Arttu Polojärvi, Erland M. Schulson, and Carl E. Renshaw
The Cryosphere, 15, 2957–2967, https://doi.org/10.5194/tc-15-2957-2021,https://doi.org/10.5194/tc-15-2957-2021, 2021
Short summary

Cited articles

Andersen, S.: Monthly Arctic sea ice signatures for use in passive microwave algorithms, Danish Meteorological Institute, Technical Report 98-18, 29 pp., 1998.
Andersen, S., Tonboe, R. T., and Kaleschke, L.: Satellite thermal microwave sea ice concentration algorithm comparison, in: Arctic Sea Ice Thickness: Past, Present and Future, edited by: Wadhams, P. and Amanatidis, G., Climate Change and Natural Hazards Series, 10, EUR 22416, 2006a.
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, 2006b.
Andersen, S., Toudal Pedersen, L., Heygster, G., Tonboe, R., and Kaleschke, L.: Intercomparison of passive microwave sea ice concentration retrievals over the high concentration Arctic sea ice, J. Geophys. Res., 112, C08004, https://doi.org/10.1029/2006JC003543, 2007.
Belchansky, G. I. and Douglas, D. C.: Seasonal comparison of sea ice concentration estimates derived from SSM/I, OKEAN, and Radarsat data, Remote Sens. Environ., 81, 67–81, 2002.
Download
Short summary
The EUMETSAT sea ice climate record (ESICR) is based on the Nimbus 7 SMMR (1978–1987), the SSM/I (1987–2009), and the SSMIS (2003–today) microwave radiometer data. It uses a combination of two sea ice concentration algorithms with dynamical tie points, explicit atmospheric correction using numerical weather prediction data for error reduction and it comes with spatially and temporally varying uncertainty estimates describing the residual uncertainties.