Articles | Volume 8, issue 2
The Cryosphere, 8, 439–451, 2014
https://doi.org/10.5194/tc-8-439-2014
The Cryosphere, 8, 439–451, 2014
https://doi.org/10.5194/tc-8-439-2014
Research article
18 Mar 2014
Research article | 18 Mar 2014

Empirical sea ice thickness retrieval during the freeze-up period from SMOS high incident angle observations

M. Huntemann et al.

Related authors

Wind Transport of Snow Impacts Ka- and Ku-band Radar Signatures on Arctic Sea Ice
Vishnu Nandan, Rosemary Willatt, Robbie Mallett, Julienne Stroeve, Torsten Geldsetzer, Randall Scharien, Rasmus Tonboe, Jack Landy, David Clemens-Sewall, Arttu Jutila, David N. Wagner, Daniela Krampe, Marcus Huntemann, John Yackel, 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 Hoppman
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-116,https://doi.org/10.5194/tc-2022-116, 2022
Preprint under review for TC
Short summary
Weddell Sea polynya analysis using SMOS–SMAP apparent sea ice thickness retrieval
Alexander Mchedlishvili, Gunnar Spreen, Christian Melsheimer, and Marcus Huntemann
The Cryosphere, 16, 471–487, https://doi.org/10.5194/tc-16-471-2022,https://doi.org/10.5194/tc-16-471-2022, 2022
Short summary
Sea ice and water classification on dual-polarized Sentinel-1 imagery during melting season
Yu Zhang, Tingting Zhu, Gunnar Spreen, Christian Melsheimer, Marcus Huntemann, Nick Hughes, Shengkai Zhang, and Fei Li
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-85,https://doi.org/10.5194/tc-2021-85, 2021
Revised manuscript not accepted
Short summary
Improved machine-learning-based open-water–sea-ice–cloud discrimination over wintertime Antarctic sea ice using MODIS thermal-infrared imagery
Stephan Paul and Marcus Huntemann
The Cryosphere, 15, 1551–1565, https://doi.org/10.5194/tc-15-1551-2021,https://doi.org/10.5194/tc-15-1551-2021, 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

Related subject area

Sea Ice
Predictability of Arctic sea ice drift in coupled climate models
Simon Felix Reifenberg and Helge Friedrich Goessling
The Cryosphere, 16, 2927–2946, https://doi.org/10.5194/tc-16-2927-2022,https://doi.org/10.5194/tc-16-2927-2022, 2022
Short summary
Recovering and monitoring the thickness, density, and elastic properties of sea ice from seismic noise recorded in Svalbard
Agathe Serripierri, Ludovic Moreau, Pierre Boue, Jérôme Weiss, and Philippe Roux
The Cryosphere, 16, 2527–2543, https://doi.org/10.5194/tc-16-2527-2022,https://doi.org/10.5194/tc-16-2527-2022, 2022
Short summary
Influences of changing sea ice and snow thicknesses on simulated Arctic winter heat fluxes
Laura L. Landrum and Marika M. Holland
The Cryosphere, 16, 1483–1495, https://doi.org/10.5194/tc-16-1483-2022,https://doi.org/10.5194/tc-16-1483-2022, 2022
Short summary
Reassessing seasonal sea ice predictability of the Pacific-Arctic sector using a Markov model
Yunhe Wang, Xiaojun Yuan, Haibo Bi, Mitchell Bushuk, Yu Liang, Cuihua Li, and Haijun Huang
The Cryosphere, 16, 1141–1156, https://doi.org/10.5194/tc-16-1141-2022,https://doi.org/10.5194/tc-16-1141-2022, 2022
Short summary
A new state-dependent parameterization for the free drift of sea ice
Charles Brunette, L. Bruno Tremblay, and Robert Newton
The Cryosphere, 16, 533–557, https://doi.org/10.5194/tc-16-533-2022,https://doi.org/10.5194/tc-16-533-2022, 2022
Short summary

Cited articles

Bilello, M.: Formation, growth, and decay of sea-ice in the Canadian Arctic Archipelago, Arctic, 1961.
Brown, M., Torres, F., Corbella, I., and Colliander, A.: SMOS Calibration, IEEE Transactions on Geoscience and Remote Sensing, 46, 646–658, https://doi.org/10.1109/TGRS.2007.914810, 2008.
Camps, A., Gourrion, J., Tarongi, J. M., Gutierrez, A., Barbosa, J., and Castro, R.: RFI Analysis in SMOS Imagery, in: Geoscience and Remote Sensing Symposium (IGARSS proceedings 2010), 2007–2010, 2010.
Castro, R.: Analytical Pixel Footprint, Tech. rep., available at: http://www.smos.com.pt/downloads/release/documents/SO-TN-DME-L1PP-0172-Analytical-Pixel-Footprint.pdf (last access: 17 March 2014), 2008.
Corbella, I., Duffo, N., Vall-llossera, M., Camps, A., and Torres, F.: The visibility function in interferometric aperture synthesis radiometry, IEEE Trans. Geosci. Remote Sens. 42, 1677–1682, https://doi.org/10.1109/TGRS.2004.830641, 2004.
Download