Assessment of Snow Depth over Arctic Sea Ice in CMIP6 Models Using Satellite Data
Assessment of Snow Depth over Arctic Sea Ice in CMIP6 Models Using Satellite Data
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DOI：
10.1007/s00376-020-0213-5
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发表时间：
2021-01
影响因子：
5.8
通讯作者：
Shengzhe Chen;Jiping Liu;Yifan Ding;Yuanyuan Zhang;Xiao Cheng;Yongyun Hu
中科院分区：
文献类型：
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作者：
Shengzhe Chen;Jiping Liu;Yifan Ding;Yuanyuan Zhang;Xiao Cheng;Yongyun Hu
海冰上的积雪深度是了解北极能源收支的一个重要变量。在这项研究中，我们评估了1993-2014年期间北极海冰上的雪深，这些雪深是由来自耦合模型相互比较项目（CMIP 6）第6阶段的31个模型模拟的。CMIP 6模式捕捉到了观测到的雪深、气候学和变率的某些方面。观察到的变异性位于模型模拟的中间。1993-2014年，所有模型都显示出积雪深度的负趋势。然而，大量的时空差异被确定。与观测结果相比，大多数模式的季节最大雪深较晚（两个月），季节最小值的雪明显较薄，从增长期到衰减期的过渡不正确，以及在多年海冰频繁发生的地区，雪深的年际变化和变薄趋势被大大低估。大多数模型无法重现从加拿大北极到外部地区的观测到的雪深梯度和北极中部最大的变薄率。未来的预测表明，从2015年到2099年，北极的积雪深度将继续减少。在SSP 5 -8.5情景下，北极在夏季和秋季几乎无雪，积雪从1月开始积累。进一步调查的问题的可能原因的模拟雪深的一些模型的基础上，同一系列的模型表明，分辨率，包括一个高顶大气模型，和地球化学过程是雪深模拟的重要因素。
Snow depth over sea ice is an essential variable for understanding the Arctic energy budget. In this study, we evaluate snow depth over Arctic sea ice during 1993–2014 simulated by 31 models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) against recent satellite retrievals. The CMIP6 models capture some aspects of the observed snow depth climatology and variability. The observed variability lies in the middle of the models’ simulations. All the models show negative trends of snow depth during 1993–2014. However, substantial spatiotemporal discrepancies are identified. Compared to the observation, most models have late seasonal maximum snow depth (by two months), remarkably thinner snow for the seasonal minimum, an incorrect transition from the growth to decay period, and a greatly underestimated interannual variability and thinning trend of snow depth over areas with frequent occurrence of multi-year sea ice. Most models are unable to reproduce the observed snow depth gradient from the Canadian Arctic to the outer areas and the largest thinning rate in the central Arctic. Future projections suggest that snow depth in the Arctic will continue to decrease from 2015 to 2099. Under the SSP5-8.5 scenario, the Arctic will be almost snow-free during the summer and fall and the accumulation of snow starts from January. Further investigation into the possible causes of the issues for the simulated snow depth by some models based on the same family of models suggests that resolution, the inclusion of a high-top atmospheric model, and biogeochemistry processes are important factors for snow depth simulation.