Articles | Volume 16, issue 10
https://doi.org/10.5194/tc-16-4473-2022
© Author(s) 2022. 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-16-4473-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A comparison between Envisat and ICESat sea ice thickness in the Southern Ocean
Jinfei Wang
School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
Robert Ricker
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Bremerhaven 27570, Germany
School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
Bo Han
School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
Stefan Hendricks
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Bremerhaven 27570, Germany
Renhao Wu
School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
Qinghua Yang
School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
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Cited
13 citations as recorded by crossref.
- Intercomparison of Antarctic Sea-Ice Thickness Estimates from Satellite Altimetry and Assessment over the 2019 Data-Rich Year M. Mangatane & M. Vichi
- Reconstruction of Antarctic sea ice thickness from sparse satellite laser altimetry data via deep learning Z. Ma et al.
- Detecting Sea Ice Leads and Floes in the Northwest Passage Using CryoSat-2 A. Swiggs et al.
- Evaluation of MITgcm-based ocean reanalyses for the Southern Ocean Y. Nakayama et al.
- Toward an Advanced Method for Full-Waveform Hyperspectral LiDAR Data Processing J. Bai et al.
- The Impacts of Optimizing Model‐Dependent Parameters on the Antarctic Sea Ice Data Assimilation H. Luo et al.
- Evaluation of Antarctic sea ice thickness and volume during 2003–2014 in CMIP6 using Envisat and CryoSat-2 observations Y. Hou et al.
- Impact of satellite-derived sea ice data assimilation over Antarctica using a variational data assimilation system S. Sahoo et al.
- Sensitivity of NEMO4.0-SI3 model parameters on sea ice budgets in the Southern Ocean Y. Nie et al.
- An assessment of Antarctic sea-ice thickness in CMIP6 simulations with comparison to the satellite-based observations and reanalyses S. Trivedi et al.
- Synergistic atmosphere-ocean-ice influences have driven the 2023 all-time Antarctic sea-ice record low J. Wang et al.
- Seasonal and Interannual Variations in Sea Ice Thickness in the Weddell Sea, Antarctica (2019–2022) Using ICESat-2 M. Joshi et al.
- Retrieval of Antarctic sea ice freeboard and thickness from HY-2B satellite altimeter data Y. Chen et al.
13 citations as recorded by crossref.
- Intercomparison of Antarctic Sea-Ice Thickness Estimates from Satellite Altimetry and Assessment over the 2019 Data-Rich Year M. Mangatane & M. Vichi
- Reconstruction of Antarctic sea ice thickness from sparse satellite laser altimetry data via deep learning Z. Ma et al.
- Detecting Sea Ice Leads and Floes in the Northwest Passage Using CryoSat-2 A. Swiggs et al.
- Evaluation of MITgcm-based ocean reanalyses for the Southern Ocean Y. Nakayama et al.
- Toward an Advanced Method for Full-Waveform Hyperspectral LiDAR Data Processing J. Bai et al.
- The Impacts of Optimizing Model‐Dependent Parameters on the Antarctic Sea Ice Data Assimilation H. Luo et al.
- Evaluation of Antarctic sea ice thickness and volume during 2003–2014 in CMIP6 using Envisat and CryoSat-2 observations Y. Hou et al.
- Impact of satellite-derived sea ice data assimilation over Antarctica using a variational data assimilation system S. Sahoo et al.
- Sensitivity of NEMO4.0-SI3 model parameters on sea ice budgets in the Southern Ocean Y. Nie et al.
- An assessment of Antarctic sea-ice thickness in CMIP6 simulations with comparison to the satellite-based observations and reanalyses S. Trivedi et al.
- Synergistic atmosphere-ocean-ice influences have driven the 2023 all-time Antarctic sea-ice record low J. Wang et al.
- Seasonal and Interannual Variations in Sea Ice Thickness in the Weddell Sea, Antarctica (2019–2022) Using ICESat-2 M. Joshi et al.
- Retrieval of Antarctic sea ice freeboard and thickness from HY-2B satellite altimeter data Y. Chen et al.
Saved (final revised paper)
Latest update: 11 May 2026
Short summary
The differences between Envisat and ICESat sea ice thickness (SIT) reveal significant temporal and spatial variations. Our findings suggest that both overestimation of Envisat sea ice freeboard, potentially caused by radar backscatter originating from inside the snow layer, and the AMSR-E snow depth biases and sea ice density uncertainties can possibly account for the differences between Envisat and ICESat SIT.
The differences between Envisat and ICESat sea ice thickness (SIT) reveal significant temporal...