Articles | Volume 10, issue 5
https://doi.org/10.5194/tc-10-2275-2016
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, Steinar Eastwood, Thomas Lavergne, Atle M. Sørensen, Nicholas Rathmann, Gorm Dybkjær, Leif Toudal Pedersen, Jacob L. Høyer, and Stefan Kern

Related authors

Mapping of sea ice concentration using the NASA NIMBUS 5 Electrically Scanning Microwave Radiometer data from 1972–1977
Wiebke Margitta Kolbe, Rasmus T. Tonboe, and Julienne Stroeve
Earth Syst. Sci. Data, 16, 1247–1264, https://doi.org/10.5194/essd-16-1247-2024,https://doi.org/10.5194/essd-16-1247-2024, 2024
Short summary
Wind redistribution of snow impacts the Ka- and Ku-band radar signatures of Arctic sea ice
Vishnu Nandan, Rosemary Willatt, Robbie Mallett, Julienne Stroeve, Torsten Geldsetzer, Randall Scharien, Rasmus Tonboe, John Yackel, Jack Landy, David Clemens-Sewall, Arttu Jutila, David N. Wagner, Daniela Krampe, Marcus Huntemann, Mallik Mahmud, David Jensen, Thomas Newman, Stefan Hendricks, Gunnar Spreen, Amy Macfarlane, Martin Schneebeli, James Mead, Robert Ricker, Michael Gallagher, Claude Duguay, Ian Raphael, Chris Polashenski, Michel Tsamados, Ilkka Matero, and Mario Hoppmann
The Cryosphere, 17, 2211–2229, https://doi.org/10.5194/tc-17-2211-2023,https://doi.org/10.5194/tc-17-2211-2023, 2023
Short summary
Rain on snow (ROS) understudied in sea ice remote sensing: a multi-sensor analysis of ROS during MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate)
Julienne Stroeve, Vishnu Nandan, Rosemary Willatt, Ruzica Dadic, Philip Rostosky, Michael Gallagher, Robbie Mallett, Andrew Barrett, Stefan Hendricks, Rasmus Tonboe, Michelle McCrystall, Mark Serreze, Linda Thielke, Gunnar Spreen, Thomas Newman, John Yackel, Robert Ricker, Michel Tsamados, Amy Macfarlane, Henna-Reetta Hannula, and Martin Schneebeli
The Cryosphere, 16, 4223–4250, https://doi.org/10.5194/tc-16-4223-2022,https://doi.org/10.5194/tc-16-4223-2022, 2022
Short summary
Satellite passive microwave sea-ice concentration data set intercomparison using Landsat data
Stefan Kern, Thomas Lavergne, Leif Toudal Pedersen, Rasmus Tage Tonboe, Louisa Bell, Maybritt Meyer, and Luise Zeigermann
The Cryosphere, 16, 349–378, https://doi.org/10.5194/tc-16-349-2022,https://doi.org/10.5194/tc-16-349-2022, 2022
Short summary
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

Related subject area

Sea Ice
Suitability of the CICE sea ice model for seasonal prediction and positive impact of CryoSat-2 ice thickness initialization
Shan Sun and Amy Solomon
The Cryosphere, 18, 3033–3048, https://doi.org/10.5194/tc-18-3033-2024,https://doi.org/10.5194/tc-18-3033-2024, 2024
Short summary
A large-scale high-resolution numerical model for sea-ice fragmentation dynamics
Jan Åström, Fredrik Robertsen, Jari Haapala, Arttu Polojärvi, Rivo Uiboupin, and Ilja Maljutenko
The Cryosphere, 18, 2429–2442, https://doi.org/10.5194/tc-18-2429-2024,https://doi.org/10.5194/tc-18-2429-2024, 2024
Short summary
Experimental modelling of the growth of tubular ice brinicles from brine flows under sea ice
Sergio Testón-Martínez, Laura M. Barge, Jan Eichler, C. Ignacio Sainz-Díaz, and Julyan H. E. Cartwright
The Cryosphere, 18, 2195–2205, https://doi.org/10.5194/tc-18-2195-2024,https://doi.org/10.5194/tc-18-2195-2024, 2024
Short summary
Why is summertime Arctic sea ice drift speed projected to decrease?
Jamie L. Ward and Neil F. Tandon
The Cryosphere, 18, 995–1012, https://doi.org/10.5194/tc-18-995-2024,https://doi.org/10.5194/tc-18-995-2024, 2024
Short summary
Seasonal Evolution of the Sea Ice Floe Size Distribution from Two Decades of MODIS Data
Ellen Margaret Buckley, Leela Cañuelas, Mary-Louise Timmermans, and Monica Martinez Wilhelmus
EGUsphere, https://doi.org/10.5194/egusphere-2024-89,https://doi.org/10.5194/egusphere-2024-89, 2024
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.