Articles | Volume 12, issue 6
https://doi.org/10.5194/tc-12-2051-2018
© Author(s) 2018. 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-12-2051-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Jun 2018
Research article |
| 14 Jun 2018
| 14 Jun 2018
Thin Arctic sea ice in L-band observations and an ocean reanalysis
European Centre for Medium-Range Weather Forecasts, Reading, UK
Magdalena Alonso-Balmaseda
European Centre for Medium-Range Weather Forecasts, Reading, UK
Patricia Rosnay
European Centre for Medium-Range Weather Forecasts, Reading, UK
European Centre for Medium-Range Weather Forecasts, Reading, UK
Xiangshan Tian-Kunze
Institute of Oceanography, University of Hamburg, Hamburg, Germany
Lars Kaleschke
Institute of Oceanography, University of Hamburg, Hamburg, Germany
now at: Max Planck Institute for Meteorology, Hamburg, Germany
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Cited
17 citations as recorded by crossref.
- Year-round impact of winter sea ice thickness observations on seasonal forecasts B. Balan-Sarojini et al. 10.5194/tc-15-325-2021
- Ensemble-based estimation of sea-ice volume variations in the Baffin Bay C. Min et al. 10.5194/tc-15-169-2021
- Southern Ocean polynyas in CMIP6 models M. Mohrmann et al. 10.5194/tc-15-4281-2021
- Copernicus Marine Service Ocean State Report, Issue 4 K. von Schuckmann et al. 10.1080/1755876X.2020.1785097
- DASSO: a data assimilation system for the Southern Ocean that utilizes both sea-ice concentration and thickness observations H. Luo et al. 10.1017/jog.2021.57
- An improved algorithm for retrieving thin sea ice thickness in the Arctic Ocean from SMOS and SMAP L-band radiometer data L. He et al. 10.1007/s13131-023-2280-9
- Cyclone Impacts on Sea Ice Concentration in the Atlantic Arctic Ocean: Annual Cycle and Recent Changes L. Aue & A. Rinke 10.1029/2023GL104657
- Retrieval of sea ice thickness using FY-3E/GNOS-II data Y. Xie & Q. Yan 10.1186/s43020-024-00138-5
- Benefits of sea ice initialization for the interannual-to-decadal climate prediction skill in the Arctic in EC-Earth3 T. Tian et al. 10.5194/gmd-14-4283-2021
- An Improved Estimate of the Coupled Arctic Energy Budget M. Mayer et al. 10.1175/JCLI-D-19-0233.1
- On the importance to consider the cloud dependence in parameterizing the albedo of snow on sea ice L. Foth et al. 10.5194/tc-18-4053-2024
- Assessment with Controlled In-Situ Data of the Dependence of L-Band Radiometry on Sea-Ice Thickness P. Sánchez-Gámez et al. 10.3390/rs12040650
- Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review G. Balsamo et al. 10.3390/rs10122038
- Rain on snow (ROS) understudied in sea ice remote sensing: a multi-sensor analysis of ROS during MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) J. Stroeve et al. 10.5194/tc-16-4223-2022
- Spatial Correlation Length Scales of Sea-Ice Concentration Errors for High-Concentration Pack Ice S. Kern 10.3390/rs13214421
- The ECMWF operational ensemble reanalysis–analysis system for ocean and sea ice: a description of the system and assessment H. Zuo et al. 10.5194/os-15-779-2019
- Estimation of sea ice parameters from sea ice model with assimilated ice concentration and SST S. Prasad et al. 10.5194/tc-12-3949-2018
17 citations as recorded by crossref.
- Year-round impact of winter sea ice thickness observations on seasonal forecasts B. Balan-Sarojini et al. 10.5194/tc-15-325-2021
- Ensemble-based estimation of sea-ice volume variations in the Baffin Bay C. Min et al. 10.5194/tc-15-169-2021
- Southern Ocean polynyas in CMIP6 models M. Mohrmann et al. 10.5194/tc-15-4281-2021
- Copernicus Marine Service Ocean State Report, Issue 4 K. von Schuckmann et al. 10.1080/1755876X.2020.1785097
- DASSO: a data assimilation system for the Southern Ocean that utilizes both sea-ice concentration and thickness observations H. Luo et al. 10.1017/jog.2021.57
- An improved algorithm for retrieving thin sea ice thickness in the Arctic Ocean from SMOS and SMAP L-band radiometer data L. He et al. 10.1007/s13131-023-2280-9
- Cyclone Impacts on Sea Ice Concentration in the Atlantic Arctic Ocean: Annual Cycle and Recent Changes L. Aue & A. Rinke 10.1029/2023GL104657
- Retrieval of sea ice thickness using FY-3E/GNOS-II data Y. Xie & Q. Yan 10.1186/s43020-024-00138-5
- Benefits of sea ice initialization for the interannual-to-decadal climate prediction skill in the Arctic in EC-Earth3 T. Tian et al. 10.5194/gmd-14-4283-2021
- An Improved Estimate of the Coupled Arctic Energy Budget M. Mayer et al. 10.1175/JCLI-D-19-0233.1
- On the importance to consider the cloud dependence in parameterizing the albedo of snow on sea ice L. Foth et al. 10.5194/tc-18-4053-2024
- Assessment with Controlled In-Situ Data of the Dependence of L-Band Radiometry on Sea-Ice Thickness P. Sánchez-Gámez et al. 10.3390/rs12040650
- Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review G. Balsamo et al. 10.3390/rs10122038
- Rain on snow (ROS) understudied in sea ice remote sensing: a multi-sensor analysis of ROS during MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) J. Stroeve et al. 10.5194/tc-16-4223-2022
- Spatial Correlation Length Scales of Sea-Ice Concentration Errors for High-Concentration Pack Ice S. Kern 10.3390/rs13214421
- The ECMWF operational ensemble reanalysis–analysis system for ocean and sea ice: a description of the system and assessment H. Zuo et al. 10.5194/os-15-779-2019
- Estimation of sea ice parameters from sea ice model with assimilated ice concentration and SST S. Prasad et al. 10.5194/tc-12-3949-2018
Discussed (final revised paper)
Latest update: 20 Nov 2024
Short summary
We compare Arctic sea-ice thickness from L-band microwave satellite observations and an ocean–sea ice reanalysis. There is good agreement for some regions and times but systematic discrepancy in others. Errors in both the reanalysis and observational products contribute to these discrepancies. Thus, we recommend proceeding with caution when using these observations for model validation or data assimilation. At the same time we emphasise their unique value for improving sea-ice forecast models.
We compare Arctic sea-ice thickness from L-band microwave satellite observations and an...
