Articles | Volume 13, issue 1
https://doi.org/10.5194/tc-13-125-2019
© Author(s) 2019. 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-13-125-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Jan 2019
Research article |
| 14 Jan 2019
| 14 Jan 2019
New insight from CryoSat-2 sea ice thickness for sea ice modelling
Centre for Polar Observation and Modelling, Department of
Meteorology, University of Reading, Reading, RG6 6BB, UK
Danny L. Feltham
Centre for Polar Observation and Modelling, Department of
Meteorology, University of Reading, Reading, RG6 6BB, UK
Michel Tsamados
Centre
for Polar Observation and Modelling, Department of Earth Sciences,
University College London, London, WC1E 6BT, UK
Andy Ridout
Centre
for Polar Observation and Modelling, Department of Earth Sciences,
University College London, London, WC1E 6BT, UK
Rachel Tilling
Centre for Polar Observation and Modelling, School of Earth and
Environment, University of Leeds, Leeds, LS2 9JT, UK
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30 citations as recorded by crossref.
- Impact of sea ice floe size distribution on seasonal fragmentation and melt of Arctic sea ice A. Bateson et al. 10.5194/tc-14-403-2020
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- A Lagrangian Snow‐Evolution System for Sea‐Ice Applications (SnowModel‐LG): Part I—Model Description G. Liston et al. 10.1029/2019JC015913
- Lake Level Change From Satellite Altimetry Over Seasonally Ice-Covered Lakes in the Mackenzie River Basin Y. Yang et al. 10.1109/TGRS.2020.3040853
- Modern Arctic Climate Research: Progress, Change of Concepts, and Urgent Problems V. Semenov 10.1134/S0001433821010114
- Navigability of the Northern Sea Route for Arc7 ice-class vessels during winter and spring sea-ice conditions S. CHEN et al. 10.1016/j.accre.2022.09.005
- The effects of assimilating a sub-grid-scale sea ice thickness distribution in a new Arctic sea ice data assimilation system N. Williams et al. 10.5194/tc-17-2509-2023
- A year-round satellite sea-ice thickness record from CryoSat-2 J. Landy et al. 10.1038/s41586-022-05058-5
- An inter-comparison of the mass budget of the Arctic sea ice in CMIP6 models A. Keen et al. 10.5194/tc-15-951-2021
- Estimating the sea ice floe size distribution using satellite altimetry: theory, climatology, and model comparison C. Horvat et al. 10.5194/tc-13-2869-2019
- The opening of the Transpolar Sea Route: Logistical, geopolitical, environmental, and socioeconomic impacts M. Bennett et al. 10.1016/j.marpol.2020.104178
- Summer sea ice floe perimeter density in the Arctic: high-resolution optical satellite imagery and model evaluation Y. Wang et al. 10.5194/tc-17-3575-2023
- Suitability of the CICE sea ice model for seasonal prediction and positive impact of CryoSat-2 ice thickness initialization S. Sun & A. Solomon 10.5194/tc-18-3033-2024
- Faster decline and higher variability in the sea ice thickness of the marginal Arctic seas when accounting for dynamic snow cover R. Mallett et al. 10.5194/tc-15-2429-2021
- A Bayesian approach towards daily pan-Arctic sea ice freeboard estimates from combined CryoSat-2 and Sentinel-3 satellite observations W. Gregory et al. 10.5194/tc-15-2857-2021
- Inter-comparison of snow depth over Arctic sea ice from reanalysis reconstructions and satellite retrieval L. Zhou et al. 10.5194/tc-15-345-2021
- Atmospheric forcing dominates winter Barents-Kara sea ice variability on interannual to decadal time scales Z. Liu et al. 10.1073/pnas.2120770119
- Snow redistribution onto young sea ice: Observations and implications for climate models D. Clemens-Sewall et al. 10.1525/elementa.2021.00115
- The Evaluation of the North Atlantic Climate System in UKESM1 Historical Simulations for CMIP6 J. Robson et al. 10.1029/2020MS002126
- Evaluating the physical and biogeochemical state of the global ocean component of UKESM1 in CMIP6 historical simulations A. Yool et al. 10.5194/gmd-14-3437-2021
- Changes of the Arctic marginal ice zone during the satellite era R. Rolph et al. 10.5194/tc-14-1971-2020
- Bias correction of Arctic sea ice thickness products based on factor selection and machine learning methods H. Wu et al. 10.1016/j.apor.2024.104069
- Optimization of the design of an agrophotovoltaic system in future climate conditions in South Korea S. Kim & S. Kim 10.1016/j.renene.2023.02.090
- Network connectivity between the winter Arctic Oscillation and summer sea ice in CMIP6 models and observations W. Gregory et al. 10.5194/tc-16-1653-2022
- Sea ice floe size: its impact on pan-Arctic and local ice mass and required model complexity A. Bateson et al. 10.5194/tc-16-2565-2022
- Possibilities of investigating ice development of the Kara sea based on CryoSat-2 and SMOS data V. Kirillov et al. 10.30758/0555-2648-2023-69-1-10-28
- Sea Ice Roughness Overlooked as a Key Source of Uncertainty in CryoSat‐2 Ice Freeboard Retrievals J. Landy et al. 10.1029/2019JC015820
- Improved Arctic Sea Ice Freeboard Retrieval From Satellite Altimetry Using Optimized Sea Surface Decorrelation Scales J. Landy et al. 10.1029/2021JC017466
- A 10-year record of Arctic summer sea ice freeboard from CryoSat-2 G. Dawson et al. 10.1016/j.rse.2021.112744
30 citations as recorded by crossref.
- Impact of sea ice floe size distribution on seasonal fragmentation and melt of Arctic sea ice A. Bateson et al. 10.5194/tc-14-403-2020
- Optimization of the Design of an Agrophotovoltaic System in Future Climate Conditions in South Korea S. Kim & S. Kim 10.2139/ssrn.4088352
- Optimization of the Design of an Agrophotovoltaic System in Future Climate Conditions in South Korea S. Kim & S. Kim 10.2139/ssrn.4171639
- A Lagrangian Snow‐Evolution System for Sea‐Ice Applications (SnowModel‐LG): Part I—Model Description G. Liston et al. 10.1029/2019JC015913
- Lake Level Change From Satellite Altimetry Over Seasonally Ice-Covered Lakes in the Mackenzie River Basin Y. Yang et al. 10.1109/TGRS.2020.3040853
- Modern Arctic Climate Research: Progress, Change of Concepts, and Urgent Problems V. Semenov 10.1134/S0001433821010114
- Navigability of the Northern Sea Route for Arc7 ice-class vessels during winter and spring sea-ice conditions S. CHEN et al. 10.1016/j.accre.2022.09.005
- The effects of assimilating a sub-grid-scale sea ice thickness distribution in a new Arctic sea ice data assimilation system N. Williams et al. 10.5194/tc-17-2509-2023
- A year-round satellite sea-ice thickness record from CryoSat-2 J. Landy et al. 10.1038/s41586-022-05058-5
- An inter-comparison of the mass budget of the Arctic sea ice in CMIP6 models A. Keen et al. 10.5194/tc-15-951-2021
- Estimating the sea ice floe size distribution using satellite altimetry: theory, climatology, and model comparison C. Horvat et al. 10.5194/tc-13-2869-2019
- The opening of the Transpolar Sea Route: Logistical, geopolitical, environmental, and socioeconomic impacts M. Bennett et al. 10.1016/j.marpol.2020.104178
- Summer sea ice floe perimeter density in the Arctic: high-resolution optical satellite imagery and model evaluation Y. Wang et al. 10.5194/tc-17-3575-2023
- Suitability of the CICE sea ice model for seasonal prediction and positive impact of CryoSat-2 ice thickness initialization S. Sun & A. Solomon 10.5194/tc-18-3033-2024
- Faster decline and higher variability in the sea ice thickness of the marginal Arctic seas when accounting for dynamic snow cover R. Mallett et al. 10.5194/tc-15-2429-2021
- A Bayesian approach towards daily pan-Arctic sea ice freeboard estimates from combined CryoSat-2 and Sentinel-3 satellite observations W. Gregory et al. 10.5194/tc-15-2857-2021
- Inter-comparison of snow depth over Arctic sea ice from reanalysis reconstructions and satellite retrieval L. Zhou et al. 10.5194/tc-15-345-2021
- Atmospheric forcing dominates winter Barents-Kara sea ice variability on interannual to decadal time scales Z. Liu et al. 10.1073/pnas.2120770119
- Snow redistribution onto young sea ice: Observations and implications for climate models D. Clemens-Sewall et al. 10.1525/elementa.2021.00115
- The Evaluation of the North Atlantic Climate System in UKESM1 Historical Simulations for CMIP6 J. Robson et al. 10.1029/2020MS002126
- Evaluating the physical and biogeochemical state of the global ocean component of UKESM1 in CMIP6 historical simulations A. Yool et al. 10.5194/gmd-14-3437-2021
- Changes of the Arctic marginal ice zone during the satellite era R. Rolph et al. 10.5194/tc-14-1971-2020
- Bias correction of Arctic sea ice thickness products based on factor selection and machine learning methods H. Wu et al. 10.1016/j.apor.2024.104069
- Optimization of the design of an agrophotovoltaic system in future climate conditions in South Korea S. Kim & S. Kim 10.1016/j.renene.2023.02.090
- Network connectivity between the winter Arctic Oscillation and summer sea ice in CMIP6 models and observations W. Gregory et al. 10.5194/tc-16-1653-2022
- Sea ice floe size: its impact on pan-Arctic and local ice mass and required model complexity A. Bateson et al. 10.5194/tc-16-2565-2022
- Possibilities of investigating ice development of the Kara sea based on CryoSat-2 and SMOS data V. Kirillov et al. 10.30758/0555-2648-2023-69-1-10-28
- Sea Ice Roughness Overlooked as a Key Source of Uncertainty in CryoSat‐2 Ice Freeboard Retrievals J. Landy et al. 10.1029/2019JC015820
- Improved Arctic Sea Ice Freeboard Retrieval From Satellite Altimetry Using Optimized Sea Surface Decorrelation Scales J. Landy et al. 10.1029/2021JC017466
- A 10-year record of Arctic summer sea ice freeboard from CryoSat-2 G. Dawson et al. 10.1016/j.rse.2021.112744
Latest update: 19 Nov 2024
Short summary
This paper uses sea ice thickness data (CryoSat-2) to identify and correct shortcomings in simulating winter ice growth in the widely used sea ice model CICE. Adding a model of snow drift and using a different scheme for calculating the ice conductivity improve model results. Sensitivity studies demonstrate that atmospheric winter conditions have little impact on winter ice growth, and the fate of Arctic summer sea ice is largely controlled by atmospheric conditions during the melting season.
This paper uses sea ice thickness data (CryoSat-2) to identify and correct shortcomings in...
