Climate Change Data Portal
| DOI | 10.5194/tc-13-125-2019 |
| New insight from CryoSat-2 sea ice thickness for sea ice modelling | |
| Schröder D.; Feltham D.L.; Tsamados M.; Ridout A.; Tilling R. | |
| 发表日期 | 2019 |
| ISSN | 19940416 |
| EISSN | 13 |
| 起始页码 | 125 |
| 结束页码 | 139 |
| 卷号 | 13期号:1 |
| 英文摘要 | Estimates of Arctic sea ice thickness have been available from the CryoSat-2 (CS2) radar altimetry mission during ice growth seasons since 2010. We derive the sub-grid-scale ice thickness distribution (ITD) with respect to five ice thickness categories used in a sea ice component (Community Ice CodE, CICE) of climate simulations. This allows us to initialize the ITD in stand-alone simulations with CICE and to verify the simulated cycle of ice thickness. We find that a default CICE simulation strongly underestimates ice thickness, despite reproducing the inter-annual variability of summer sea ice extent. We can identify the underestimation of winter ice growth as being responsible and show that increasing the ice conductive flux for lower temperatures (bubbly brine scheme) and accounting for the loss of drifting snow results in the simulated sea ice growth being more realistic. Sensitivity studies provide insight into the impact of initial and atmospheric conditions and, thus, on the role of positive and negative feedback processes. During summer, atmospheric conditions are responsible for 50 % of September sea ice thickness variability through the positive sea ice and melt pond albedo feedback. However, atmospheric winter conditions have little impact on winter ice growth due to the dominating negative conductive feedback process: the thinner the ice and snow in autumn, the stronger the ice growth in winter. We conclude that the fate of Arctic summer sea ice is largely controlled by atmospheric conditions during the melting season rather than by winter temperature. Our optimal model configuration does not only improve the simulated sea ice thickness, but also summer sea ice concentration, melt pond fraction, and length of the melt season. It is the first time CS2 sea ice thickness data have been applied successfully to improve sea ice model physics. © Author(s) 2019. |
| 学科领域 | CryoSat; ice thickness; melting; modeling; sea ice; simulation; temperature |
| 语种 | 英语 |
| scopus关键词 | CryoSat; ice thickness; melting; modeling; sea ice; simulation; temperature |
| 来源期刊 | The Cryosphere
 |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/118948 |
| 作者单位 | Centre for Polar Observation and Modelling, Department of Meteorology, University of Reading, Reading, RG6 6BB, United Kingdom; Centre for Polar Observation and Modelling, Department of Earth Sciences, University College London, London, WC1E 6BT, United Kingdom; Centre for Polar Observation and Modelling, School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, United Kingdom |
| 推荐引用方式 GB/T 7714 | Schröder D.,Feltham D.L.,Tsamados M.,et al. New insight from CryoSat-2 sea ice thickness for sea ice modelling[J],2019,13(1). |
| APA | Schröder D.,Feltham D.L.,Tsamados M.,Ridout A.,&Tilling R..(2019).New insight from CryoSat-2 sea ice thickness for sea ice modelling.The Cryosphere,13(1). |
| MLA | Schröder D.,et al."New insight from CryoSat-2 sea ice thickness for sea ice modelling".The Cryosphere 13.1(2019). |
| 条目包含的文件 | 条目无相关文件。 | |||||
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