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

Journal metrics

Journal metrics

  • IF value: 4.524 IF 4.524
  • IF 5-year value: 5.558 IF 5-year
    5.558
  • CiteScore value: 4.84 CiteScore
    4.84
  • SNIP value: 1.425 SNIP 1.425
  • IPP value: 4.65 IPP 4.65
  • SJR value: 3.034 SJR 3.034
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 55 Scimago H
    index 55
  • h5-index value: 52 h5-index 52
Volume 11, issue 4
The Cryosphere, 11, 1987-2002, 2017
https://doi.org/10.5194/tc-11-1987-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
The Cryosphere, 11, 1987-2002, 2017
https://doi.org/10.5194/tc-11-1987-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 30 Aug 2017

Research article | 30 Aug 2017

New methodology to estimate Arctic sea ice concentration from SMOS combining brightness temperature differences in a maximum-likelihood estimator

Carolina Gabarro et al.
Viewed  
Total article views: 1,400 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
902 407 91 1,400 49 114
  • HTML: 902
  • PDF: 407
  • XML: 91
  • Total: 1,400
  • BibTeX: 49
  • EndNote: 114
Views and downloads (calculated since 03 Nov 2016)
Cumulative views and downloads (calculated since 03 Nov 2016)
Viewed (geographical distribution)  
Total article views: 1,347 (including HTML, PDF, and XML) Thereof 1,344 with geography defined and 3 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Cited  
Saved (final revised paper)  
No saved metrics found.
Saved (discussion paper)  
No saved metrics found.
Discussed (final revised paper)  
No discussed metrics found.
Discussed (discussion paper)  
No discussed metrics found.
Latest update: 18 Jun 2019
Publications Copernicus
Download
Short summary
We present a new method to estimate sea ice concentration in the Arctic Ocean using different brightness temperature observations from the Soil Moisture Ocean Salinity (SMOS) satellite. The method employs a maximum-likelihood estimator. Observations at L-band frequencies such as those from SMOS (i.e. 1.4 GHz) are advantageous to remote sensing of sea ice because the atmosphere is virtually transparent at that frequency and little affected by physical temperature changes.
We present a new method to estimate sea ice concentration in the Arctic Ocean using different...
Citation