New insight from CryoSat-2 sea ice thickness for sea ice modelling
New insight from CryoSat-2 sea ice thickness for sea ice modelling
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DOI：
10.5194/tc-13-125-2019
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发表时间：
2018-08
期刊：
影响因子：
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通讯作者：
D. Schröder;D. Feltham;M. Tsamados;A. Ridout;R. Tilling
中科院分区：
文献类型：
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作者：
D. Schröder;D. Feltham;M. Tsamados;A. Ridout;R. Tilling
抽象。自2010年以来，通过CryoSat-2（CS2）雷达测高使命任务，可获得冰生长季节期间北极海冰厚度的估计值。我们得到的亚网格尺度的冰厚度分布（ITD）相对于五个冰厚度类别中使用的海冰组件（社区冰代码，CICE）的气候模拟。这使我们能够初始化ITD在独立的模拟与CICE和验证冰厚度的模拟周期。我们发现，一个默认的CICE模拟强烈低估了冰的厚度，尽管再现夏季海冰范围的年际变化。我们可以确定低估的冬季冰的增长是负责任的，并表明，增加冰的传导通量较低的温度（气泡盐水计划），并占在模拟的海冰增长的损失是更现实的结果。敏感性研究提供了对初始条件和大气条件的影响的深入了解，从而提供了对正反馈和负反馈过程的作用的深入了解。在夏季，大气条件是负责50%的9月海冰厚度的变化，通过积极的海冰和融化池的负反馈。而冬季大气条件对冬季冰增长的影响很小，主要是负传导反馈过程：秋季冰雪越薄，冬季冰增长越强。我们的结论是，北极夏季海冰的命运在很大程度上是由大气条件在融化季节，而不是由冬季温度控制。我们的最佳模式配置不仅提高了模拟的海冰厚度，但夏季海冰浓度，融化池分数，和融化季节的长度。这是CS2海冰厚度数据首次成功应用于改进海冰模式物理。
Abstract. 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.