Articles | Volume 17, issue 7
https://doi.org/10.5194/tc-17-3013-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-3013-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Jul 2023
Research article |
| 25 Jul 2023
| 25 Jul 2023
Arctic sea ice radar freeboard retrieval from the European Remote-Sensing Satellite (ERS-2) using altimetry: toward sea ice thickness observation from 1995 to 2021
Marion Bocquet
CORRESPONDING AUTHOR
LEGOS, Université de Toulouse, CNES, CNRS, IRD, UPS, Toulouse, France
Collecte Localisation Satellites (CLS), Toulouse, France
Sara Fleury
LEGOS, Université de Toulouse, CNES, CNRS, IRD, UPS, Toulouse, France
Fanny Piras
Collecte Localisation Satellites (CLS), Toulouse, France
Eero Rinne
Marine Research, Finnish Meteorological Institute, Helsinki, Finland
University Centre in Svalbard (UNIS), P.O. Box 156, 9171 Longyearbyen, Norway
Heidi Sallila
Marine Research, Finnish Meteorological Institute, Helsinki, Finland
Florent Garnier
LEGOS, Université de Toulouse, CNES, CNRS, IRD, UPS, Toulouse, France
Frédérique Rémy
LEGOS, Université de Toulouse, CNES, CNRS, IRD, UPS, Toulouse, France
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Short summary
Sea ice has a large interannual variability, and studying its evolution requires long time series of observations. In this paper, we propose the first method to extend Arctic sea ice thickness time series to the ERS-2 altimeter. The developed method is based on a neural network to calibrate past missions on the current one by taking advantage of their differences during the mission-overlap periods. Data are available as monthly maps for each year during the winter period between 1995 and 2021.
Sea ice has a large interannual variability, and studying its evolution requires long time...
