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CMIP5耦合模式对欧亚大陆冬季雪水当量的模拟及预估

作者:

杨笑宇 1, 2 林朝晖1, 3 王雨曦 1, 2 陈红1 俞越1, 2

 

1 中国科学院大气物理研究所国际气候与环境科学中心,北京 100029
2 中国科学院大学,北京 100049
3 南京信息工程大学气象灾害预报预警与评估协同创新中心,南京 210044


 

关键词

CMIP5 模式 雪水当量 模式评估 气候预估

CMIP5 models, Snow water equivalent, Model evaluation, Climate projection

 

摘要:

基于美国冰雪资料中心( NSIDC)提供的卫星遥感雪水当量资料,评估了 26 个 CMIP5( Coupled Model
Inter-comparison Project)耦合模式对 1981~2005 年欧亚大陆冬季雪水当量的模拟能力,在此基础上应用多模式集
合平均结果,预估了 21 世纪欧亚大陆雪水当量的变化情况。结果表明, CMIP5 耦合模式对欧亚大陆冬季雪水当
量空间分布具有一定的模拟能力,能够再现出欧亚大陆冬季雪水当量由南向北递增、青藏高原积雪多于同纬度其
他地区的特征;就雪水当量的幅值而言,几乎所有模式均显著低估了西伯利亚中部雪水当量的大值中心,对中国
东北地区雪水当量的模拟也显著偏低,但模式对乌拉尔山以西的东欧平原、我国北方及蒙古地区冬季雪水当量的
模拟却比卫星遥感资料显著偏大,此外模式对堪察加半岛及以北的西伯利亚东北部地区的雪水当量也明显偏大。
对于青藏高原地区,虽然部分模式可以模拟出青藏高原东部的雪水当量大值区,但大多数模式对青藏高原西部雪
水当量的模拟却明显偏大,存在虚假的大值中心。对遥感反演资料的 EOF( Empirical Orthogonal Function)分解
表明,对于 EOF 第一个模态所对应欧亚大陆全区一致的年代际变化特征,仅有少数模式具有一定的模拟能力,大
多数模式以及多模式集合的结果均未能予以反映;对应于欧亚大陆雪水当量年际变化的 EOF 第二模态而言,仅有
少数模式(如俄罗斯的 INMCM4)具有一定的再现能力,绝大多数模式对该模态及其时间演变的特征没有模拟能
力。比较 CMIP5 多模式的集合预估结果与 1981~2005 年基准时段的雪水当量,可以发现在 RCP4.5 排放情景下,
西伯利亚中东部地区的雪水当量相对于基准时段显著增加,区域平均的增加量在 21 世纪前、中、后期分别为 4.1
mm、 5.4 mm 和 6.8 mm,且随时间增加得更显著;对 90°E 以西的欧洲大陆和青藏高原地区,其雪水当量则相对
减少,减少的幅度和显著性也随时间而增大。就雪水当量的相对变化而言,在欧亚大陆东北部存在雪水当量相对
变化的大值区,在 21 世纪后期相对变化显著区大都在 5%~10%;但在青藏高原、斯堪的纳维亚半岛进和东欧平
原,并没有发现雪水当量相对变化的髙值区,这是由于这些区域冬季雪水当量的幅值较大的缘故。 RCP8.5 情景下
欧亚大陆雪水当量的变化特征与 RCP4.5 相类似,只是变化的幅度更大。

Based on the remote sensing data from National Snow and ICE Data Center (NSIDC), the performance of
CMIP5 (Coupled Model Inter-comparison Project) models in reproducing the winter snow water equivalent (SWE) in theEurasian continent during 1981−2005 was evaluated first, and the multi-model ensemble (MME) technique was thenapplied to project the SWE changes over Eurasian continent in the 21st century under the conditions of two differentrepresentative concentration pathways (RCP4.5 and RCP8.5) using eight good CMIP models out of total 26 models. Theresults show that the models were able to reproduce the spatial pattern of winter mean SWE in the Eurasia, i.e. the 25-yearaverage of SWE increased from south to north and SWE in the Tibetan Plateau was much higher than those in otherregions of the same latitude. However, some errors still existed in the models. For example, almost all modelsunderestimated the maximum SWE in central Siberia, and SWE in northeastern China was also underestimated. It wasfound that SWE to the west of Ural Mountains and over northern part of China and Mongolia was overestimated whencompared with observation. Meanwhile, only a subset of the models could produce the maximum SWE on the easternTibetan Plateau, and the spurious maximum SWE could be found on the western Tibetan Plateau in most CMIP5 models.The spatial and temporal characteristics of winter SWE from CMIP5 model simulations and observations were furtheranalyzed using the Empirical Orthogonal Function (EOF) analysis, and the results suggested that only a small number ofCMIP5 models could reproduce main features of the first eigenvector that reflects the decadal variation of SWE over thewhole Eurasia. The second mode reflects the annual variation of SWE over the Eurasia, and only a few models (e.g.,INMCM4) could reproduce the spatial and temporal characteristics of the second mode to some extent. With respect to thereference period 1981−2005, projection of SWE by the MME under the RCP4.5 shows that SWE in the northeastern

Eurasia continent would increase significantly with an increase of 4.1 mm for the 25-year averaged winter SWE in theearly stage of the 21st century, followed by 5.4-mm and 6.8-mm increases in the middle and late 21st century, respectively.In contrast, there would exist a decrease of SWE in continental Europe to the west of 90°E and over the Tibetan Plateauand the decrease would become more severe with time. In terms of percentage change of SWE, the region with largemagnitudes was found in the northeastern Eurasian continent, where the increase of SWE could be around 5%−10%.However, no maximum centers were found in the Tibetan Plateau, Scandinavian Peninsula and East European Plain
possibly because of the large values of winter SWE in these regions. Projection of SWE changes by the MME under thehigh emission scenario RCP8.5 shows a similar pattern with results under the emission scenario RCP4.5, but with largeramplitudes of changes in snow water equivalence.


引用:

杨笑宇, 林朝晖, 王雨曦, 等. 2017. CMIP5 耦合模式对欧亚大陆冬季雪水当量的模拟及预估 [J]. 气候与环境研究, 22 (3): 253−270. Yang Xiaoyu, Lin Zhaohui, Wang Yuxi, et al. 2017. Simulation and projection of snow water equivalent over the Eurasian continent by CMIP5 coupled models [J]. Climatic and Environmental Research (in Chinese), 22 (3): 253−270, doi:10.3878/j.issn.1006-9585.2016.16104.

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