欧亚大陆积雪覆盖率的模拟评估及未来情景预估

夏坤; 王斌

doi:10.3878/j.issn.1006-9585.2014.13126

欧亚大陆积雪覆盖率的模拟评估及未来情景预估

doi: 10.3878/j.issn.1006-9585.2014.13126

夏坤,
王斌

清华大学地球系统数值模拟教育部重点实验室/清华大学地球系统科学研究中心, 北京100084;中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室, 北京100029

基金项目: 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

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出版历程
- 收稿日期: 2013-07-26

Evaluation and Projection of Snow Cover Fraction over Eurasia

XIA Kun,
WANG Bin

Ministry of Education Key Laboratory for Earth System Modeling, Center of Earth System Sciences, Tsinghua University, Beijing 100084;State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029

摘要

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.
- 积雪覆盖率 /
- 欧亚大陆 /
- CMIP5试验 /
- 评估
Abstract: 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.
- Snow cover fraction /
- Eurasia /
- CMIP5 /
- Evaluation

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参考文献(24)

[1]	Brutel-Vuilmet C, Ménégoz M, Krinner G. 2013. An analysis of present and future seasonal northern hemisphere land snow cover simulated by CMIP5 coupled climate models [J]. The Cryosphere, 7: 67-80.
[2]	Foster D F Jr, Davy R D. 1988. Global snow depth climatology [R]. USAFETAC/TN-88/006. Illinois: Scott Air Force Base, 48pp.
[3]	郭彦,董文杰,任福民,等. 2013. CMIP5模式对中国年平均气温模拟及其与CMIP3模式的比较 [J]. 气候变化研究进展,9 (3): 181-186. Guo Yan, Dong Wenjie, Ren Fumin, et al. 2013. Assessment of CMIP5 simulations for China annual average surface temperature and its comparison with CMIP3 simulations [J]. Advances in Climate Change Research (in Chinese), 9 (3): 181-186.
[4]	Lemke P, Ren J, Alley R B, et al. 2007. Observations: Changes in snow, ice and frozen ground [C]// Climate Change 2007: The Physical Science Basis, Summary for Policymakers, Technical Summary and Frequently Asked Questions. Part of the Working Group 1 ContributionⅠto the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press.
[5]	李伟平, 刘新, 聂肃平, 等. 2009. 气候模式中积雪覆盖率参数化方案的对比研究 [J]. 地球科学进展, 24: 512-522. Li Weiping, Liu Xin, Nie Suping, et al. 2009. Comparative studies of snow cover parameterization schemes used in climate models [J]. Advances in Earth Science (in Chinese), 24: 512-522.
[6]	马丽娟, 罗勇, 秦大河. 2011. CMIP3模式对未来50 a欧亚大陆雪水当量的预估 [J]. 冰川冻土, 33: 707-720. Ma Lijuan, Luo Yong, Qin Dahe. 2011. Snow water equivalent over Eurasia in next 50 years projected by CMIP3 models [J]. Journal of Glaciology and Geocryology (in Chinese), 33: 707-720.
[7]	Masson D, Knutti R. 2011. Climate model genealogy [J]. Geophys. Res. Lett., 38: L08703, doi: 10.1175/2011GL046864.
[8]	穆松宁, 周广庆. 2012. 欧亚北部冬季增雪"影响"我国夏季气候异常的机理研究——陆面季节演变异常的"纽带"作用 [J]. 大气科学, 36: 297-315. Mu Songning, Zhou Guangqing. 2012. Mechanism for the correlation of winter fresh snow extent over Northern Eurasia and summer climate anomalies in China: Anomalous seasonal transition of land as a bond [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 36: 297-315.
[9]	Qu X, Hall A. 2014. On the persistent spread in snow-albedo feedback [J]. Climate Dyn., 42: 69-81, doi: 10.1007/s00382-013-1774-0.
[10]	Roesch A. 2006. Evaluation of surface albedo and snow cover in AR4 coupled climate models [J]. J. Geophys. Res., 111: D15111, doi: 10.1029/ 2005JD006473.
[11]	Stroeve J C, Kattsov V, Barrett A, et al. 2012. Trends in arctic sea ice extent from CMIP5, CMIP3, and observations [J]. Geophys. Res. Lett., 39: L16502, doi: 10.1029/2012GL052676.
[12]	Su F G, Duan X L, Chen D L, et al. 2013. Evaluation of the global climate models in the CMIP5 over the Tibetan Plateau [J]. J. Climate, 26: 3187-3208.
[13]	Vavrus S. 2007. The role of terrestrial snow cover in the climate system [J]. Climate Dyn., 29: 73-88.
[14]	汪方, 丁一汇. 2011. 不同排放情景下模拟的21世纪东亚积雪面积变化趋势 [J]. 高原气象, 30: 869-977. Wang Fang, Ding Yihui. 2011. Trend of snow cover fraction in East Asia in 21th century under different scenarios [J]. Plateau Meteorology (in Chinese), 30: 869-977.
[15]	Willmott C J, Matsuura K. 2000. Terrestrial air temperature and precipitation: Monthly and annual climatologies [R]. University of Delaware, version 3.02.
[16]	Wu B Y, Yang K, Zhang R H. 2009. Eurasian snow cover variability and its association with summer rainfall in China [J]. Advances in Atmospheric Sciences, 26: 31-44.
[17]	Wu T W, Wu G X. 2004. An Empirical formula to compute snow cover fraction in GCMs [J]. Advances in Atmospheric Sciences, 21: 529-535.
[18]	Xia K, Wang B, Li L J, et al. 2014. Evaluation of snow depth and snow cover fraction simulated by two versions of the flexible global ocean-atmosphere-land system model [J]. Advances in Atmospheric Sciences, 31: 407-420, doi: 10.1007/s00376-013-3026-y.
[19]	Yao Y, Luo Y, Huang J B, et al. 2013. Comparison of monthly temperature extremes simulated by CMIP3 and CMIP5 models [J]. J. Climate, 26: 7692-7707, doi: 10.1175/JCLI-D-12-00560.1.
[20]	Zhang T J. 2005. Influence of the seasonal snow cover on the ground thermal regime: An overview [J]. Reviews of Geophysics, 43, doi: 10.1029/2004RG000157.
[21]	赵宗慈, 罗勇, 黄建斌. 2013. 对地球系统模式评估方法的回顾 [J]. 气候变化研究进展, 9: 1-8. Zhao Zongci, Luo Yong, Huang Jianbin. 2013. A review on evaluation methods of climate modeling [J]. Progressus Inquisitiones De Mutatione Climatis (in Chinese), 9: 1-8.
[22]	朱献, 董文杰. 2013. CMIP5耦合模式对北半球3～4月积雪面积的历史模拟和未来预估 [J]. 气候变化研究进展, 9: 173-180. Zhu Xian, Dong Wenjie. 2013. Evaluation and projection of Northern Hemisphere march-april snow covered area simulated by CMIP5 coupled climate models [J]. Adrances in Climate Change Research (in Chinese), 9: 173-180.
[23]	朱玉祥, 丁一汇. 2007. 青藏高原积雪对气候影响的研究进展和问题 [J]. 气象科技, 35: 1-8. Zhu Yuxiang, Ding Yihui. 2007. Influences of snow cover over Tibetan Plateau on weather and climate: Advances and problems [J]. Meteorological Science and Technology (in Chinese), 35: 1-8.
[24]	朱玉祥, 丁一汇, 刘海文. 2009. 青藏高原冬季积雪影响我国夏季降水的模拟研究 [J]. 大气科学, 33: 903-915. Zhu Yuxiang, Ding Yihui, Liu Haiwen. 2009. Simulation of the influence of winter snow depth over the Tibetan Plateau on summer rainfall in China [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 33: 903-915.