摘要
基于国际耦合模式比较计划第五阶段(CMIP5)历史模拟试验(historical run)的模式输出结果以及遥感数据,采用相关分析、均方根误差、标准差等统计方法,评估了13个气候(或地球)系统模式对欧亚大陆积雪覆盖率的模拟能力,在此基础上,采用多模式集合平均的方法对未来不同温室气体排放情景下(rcp2.6、rcp4.5和rcp8.5)欧亚大陆积雪覆盖率的变化进行预估。结果显示:尽管各模式模拟的积雪覆盖率在高原地区与观测差异较大,但总体看来模式能够对欧亚大陆积雪覆盖率的空间形态、季节变化及年际变化特征做出较好地模拟。未来预估结果表明,多模式集合平均预估的欧亚大陆积雪覆盖率从2006年到2040年左右减少趋势非常明显,且不同排放情景下模式模拟的积雪减少速率非常接近;然而,大约从2040年之后,不同排放情景下的积雪覆盖率减小趋势的差异越来越大,rcp2.6和rcp4.5下积雪覆盖率的变化趋于平缓,而rcp8.5情景下,积雪覆盖率一直减少,冬季、春季和秋季都明显减少,减少最显著的区域位于西欧和青藏高原地区。由此可见,控制温室气体的排放对于未来欧亚大陆积雪的变化是至关重要的。
Based on a combination of historical runs, one of the core experiments of the 5th Coupled Model Inter-comparison Project (CMIP5), and remote sensing data, simulations of the snow cover fraction over Eurasia from 13 coupled climate models were evaluated, using correlation analysis, root-mean-square error (RMSE), standard deviation, and other statistical metrics. The ensemble mean of the 13 models was used to project changes in snow cover fraction (SCF) over Eurasia under the conditions of three different representative concentration pathways (rcp2.6, rcp4.5, and rcp8.5). The results show that, although large differences are seen among simulations and between simulation and observation on the Tibetan Plateau, on the whole, the models were able to adequately simulate the spatial patterns, seasonal changes, and annual variation in SCF. The projection scenarios indicated a clearly decreasing trend from 2006 to 2040 under the different emission scenarios, with little difference between them. However, after 2040, the decreasing trend tends to be smoother under rcp2.6 and rcp4.5, whereas under rcp8.5 the trend is less pronounced. In this, the areas experiencing the most significant decrease are located to the west of Europe and on the Tibetan Plateau, and the greatest decrease is seen in winter, spring, and autumn. The results suggest that to maintain Eurasian snow cover, it is important to control greenhouse gas emissions in the future.
出处
《气候与环境研究》
CSCD
北大核心
2015年第1期41-52,共12页
Climatic and Environmental Research
基金
国家科技支撑计划项目2012BAC22B02
国家重点基础研究发展计划项目2013CBA802