Journal cover Journal topic
The Cryosphere An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 4.790 IF 4.790
  • IF 5-year value: 5.921 IF 5-year
    5.921
  • CiteScore value: 5.27 CiteScore
    5.27
  • SNIP value: 1.551 SNIP 1.551
  • IPP value: 5.08 IPP 5.08
  • SJR value: 3.016 SJR 3.016
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 63 Scimago H
    index 63
  • h5-index value: 51 h5-index 51
Volume 10, issue 5
The Cryosphere, 10, 2275–2290, 2016
https://doi.org/10.5194/tc-10-2275-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
The Cryosphere, 10, 2275–2290, 2016
https://doi.org/10.5194/tc-10-2275-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

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

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 Discuss., https://doi.org/10.5194/tc-2020-27,https://doi.org/10.5194/tc-2020-27, 2020
Preprint under review for TC
Short summary
Satellite Passive Microwave Sea-Ice Concentration Data Set Intercomparison for Arctic Summer Conditions
Stefan Kern, Thomas Lavergne, Dirk Notz, Leif Toudal Pedersen, and Rasmus Tage Tonboe
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-35,https://doi.org/10.5194/tc-2020-35, 2020
Preprint under review for TC
Short summary
The Arctic Ocean Observation Operator for 6.9 GHz (ARC3O) – Part 1: How to obtain sea-ice brightness temperatures at 6.9 GHz from climate model output
Clara Burgard, Dirk Notz, Leif T. Pedersen, and Rasmus T. Tonboe
The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-317,https://doi.org/10.5194/tc-2019-317, 2020
Preprint under review for TC
Short summary
The Arctic Ocean Observation Operator for 6.9 GHz (ARC3O) – Part 2: Development and evaluation
Clara Burgard, Dirk Notz, Leif T. Pedersen, and Rasmus T. Tonboe
The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-318,https://doi.org/10.5194/tc-2019-318, 2020
Preprint under review for TC
Short summary
Satellite passive microwave sea-ice concentration data set intercomparison: closed ice and ship-based observations
Stefan Kern, Thomas Lavergne, Dirk Notz, Leif Toudal Pedersen, Rasmus Tage Tonboe, Roberto Saldo, and Atle MacDonald Sørensen
The Cryosphere, 13, 3261–3307, https://doi.org/10.5194/tc-13-3261-2019,https://doi.org/10.5194/tc-13-3261-2019, 2019
Short summary

Related subject area

Sea Ice
Sea ice volume variability and water temperature in the Greenland Sea
Valeria Selyuzhenok, Igor Bashmachnikov, Robert Ricker, Anna Vesman, and Leonid Bobylev
The Cryosphere, 14, 477–495, https://doi.org/10.5194/tc-14-477-2020,https://doi.org/10.5194/tc-14-477-2020, 2020
Short summary
Sea ice export through the Fram Strait derived from a combined model and satellite data set
Chao Min, Longjiang Mu, Qinghua Yang, Robert Ricker, Qian Shi, Bo Han, Renhao Wu, and Jiping Liu
The Cryosphere, 13, 3209–3224, https://doi.org/10.5194/tc-13-3209-2019,https://doi.org/10.5194/tc-13-3209-2019, 2019
Short summary
Estimating early-winter Antarctic sea ice thickness from deformed ice morphology
M. Jeffrey Mei, Ted Maksym, Blake Weissling, and Hanumant Singh
The Cryosphere, 13, 2915–2934, https://doi.org/10.5194/tc-13-2915-2019,https://doi.org/10.5194/tc-13-2915-2019, 2019
Short summary
Variability Scaling and Consistency of Airborne and Satellite Altimetry Measurements of Arctic Sea Ice
Shiming Xu, Lu Zhou, and Bin Wang
The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-220,https://doi.org/10.5194/tc-2019-220, 2019
Revised manuscript accepted for TC
Short summary
On the multi-fractal scaling properties of sea ice deformation
Pierre Rampal, Véronique Dansereau, Einar Olason, Sylvain Bouillon, Timothy Williams, Anton Korosov, and Abdoulaye Samaké
The Cryosphere, 13, 2457–2474, https://doi.org/10.5194/tc-13-2457-2019,https://doi.org/10.5194/tc-13-2457-2019, 2019
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.
Publications Copernicus
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.
The EUMETSAT sea ice climate record (ESICR) is based on the Nimbus 7 SMMR (1978–1987), the SSM/I...
Citation