当前位置: X-MOL 学术Adv. Atmos. Sci. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Assessment of Snow Depth over Arctic Sea Ice in CMIP6 Models Using Satellite Data
Advances in Atmospheric Sciences ( IF 5.8 ) Pub Date : 2021-01-05 , DOI: 10.1007/s00376-020-0213-5
Shengzhe Chen , Jiping Liu , Yifan Ding , Yuanyuan Zhang , Xiao Cheng , Yongyun Hu

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.

中文翻译:

使用卫星数据评估 CMIP6 模型中北极海冰上的积雪深度

海冰上的积雪深度是了解北极能量收支的重要变量。在这项研究中,我们评估了 1993 年至 2014 年期间北极海冰上的雪深,这些模型由耦合模型比对项目 (CMIP6) 第 6 阶段的 31 个模型根据最近的卫星反演结果模拟。CMIP6 模型捕捉了观测到的雪深气候学和变异性的某些方面。观察到的可变性位于模型模拟的中间。1993-2014年所有模型都显示出雪深的负趋势。然而,发现了大量的时空差异。与观测相比,大多数模型具有晚的季节性最大雪深(两个月),季节性最小值的雪明显更薄,从生长期到衰退期的过渡不正确,多年海冰频繁发生地区的年际变化和雪深变薄趋势被大大低估。大多数模型无法再现观测到的从加拿大北极到外围地区的雪深梯度和北极中部最大的减薄率。未来预测表明,2015年至2099年北极地区的积雪深度将继续减少。在SSP5-8.5情景下,北极地区夏秋季几乎无雪,积雪从1月开始。对一些基于同一系列模型的模型进行的模拟雪深问题的可能原因的进一步调查表明,分辨率、包含高顶大气模型和生物地球化学过程是雪深模拟的重要因素。
更新日期:2021-01-05
down
wechat
bug