CSIRO Mk3.6.0模式及其驱动下RegCM4.4模式对中国气候变化的预估

doi:10.12006/j.issn.1673-1719.2017.101

气候变化研究进展 ›› 2017, Vol. 13 ›› Issue (6): 557-568.doi: 10.12006/j.issn.1673-1719.2017.101

CSIRO Mk3.6.0模式及其驱动下RegCM4.4模式对中国气候变化的预估

张冬峰¹, 韩振宇², 石英²

1 山西省气候中心, 太原 030006;
2 中国气象局国家气候中心, 北京 100081

收稿日期:2017-05-25 修回日期:2017-07-02 出版日期:2017-11-30 发布日期:2017-11-30
作者简介:张冬峰,女,正研级高工,minczdf@hotmail.com
基金资助:
中国气象局气候变化专项（CCSF201509，CCSF201626）

Comparison of Climate Projection Between the Driving CSIRO-Mk3.6.0 and the Downscaling Simulation of RegCM4.4 over China

Zhang Dongfeng¹, Han Zhenyu², Shi Ying²

1 Shanxi Climate Center, Taiyuan 030006, China;
2 National Climate Center, China Meteorological Administration, Beijing 100081, China

Received:2017-05-25 Revised:2017-07-02 Online:2017-11-30 Published:2017-11-30

摘要/Abstract

摘要：

使用区域气候模式RegCM4.4，对全球模式CSIRO-Mk3.6.0在RCP4.5情景下的气候变化试验结果（1950-2100年）在东亚地区进行25 km动力降尺度试验，比较了CSIRO-Mk3.6.0和RegCM4.4预估中国地区的21世纪气候变化。结果表明，两个模式预估未来中国地区气温持续升高，升温幅度具有区域性特征，RegCM4.4预估区域平均升温幅度低于CSIRO-Mk3.6.0，但二者年际波动基本一致。两个模式预估未来降水在中国西部以持续增加为主，东部则表现出较大的不一致性，预估区域平均年降水量变化不大，呈现冬季明显增加，夏季微弱减少的特点。此外，为了解区域气候模式对中国降水预估的不确定性，对本研究和以往RegCM3使用相同分辨率模拟得到的未来降水预估进行了对比，两个区域模式预估中国西部大部分地区未来降水一致性增加，东部存在明显不一致（冬季中、高纬除外）。

关键词: 气候变化预估, RegCM4.4, 中国区域, RCP4.5

Abstract:

A 151-year (1950-2100) dynamical downscaling simulation over East Asia is conducted by using the regional climate model RegCM4.4 at 25 km grid spacing, which is nested within CSIRO-Mk3.6.0. Climate changes over China during the 21st century under the RCP4.5 scenario from CSIRO-Mk3.6.0 and RegCM4.4 are analyzed. Both simulations project that continuous warming with large regional variations will occur in the future. The two simulations obtain similar inter-annual fluctuations of regional average warming, with RegCM4.4 obtaining somewhat smaller values than CSIRO-Mk3.6.0. Projected precipitation changes are even more regionally variable than temperature changes. In western China, both models project increased precipitation, while the projections from two models show different regional details in eastern China. In both simulations, projected annual mean precipitation on national scale does not change significantly due to the contrast changes between dry and wet seasons. To analyze uncertainties of the projected climate change in China, the simulation of RegCM4.4 is compared with a previous simulation of the RegCM3 at the same horizontal resolution. The overall consistency in precipitation change between RegCM3 and RegCM4.4 is projected across western China, while inconsistency is identified in most of eastern China.

Key words: climate change projection, RegCM4.4, China, RCP4.5

张冬峰, 韩振宇, 石英. CSIRO Mk3.6.0模式及其驱动下RegCM4.4模式对中国气候变化的预估[J]. 气候变化研究进展, 2017, 13(6): 557-568.

Zhang Dongfeng, Han Zhenyu, Shi Ying. Comparison of Climate Projection Between the Driving CSIRO-Mk3.6.0 and the Downscaling Simulation of RegCM4.4 over China[J]. Climate Change Research, 2017, 13(6): 557-568.

参考文献

[1] Meinshausen M, Smith S J, Calvin K, et al. The RCP greenhouse gas concentrations and their extensions from 1765 to 2300[J]. Climatic Change, 2011, 109:213-241
[2] IPCC. Climate change 2013:the physical science basis[M]. Cambridge:Cambridge University Press, 2013
[3] Gao X J, Zhao Z C, Ding Y H, et al. Climate change due to greenhouse effects in China as simulated by a regional climate model[J]. Advances in Atmospheric Sciences, 2001, 18(6):1224-1230
[4] Gao X J, Xu Y, Zhao Z C, et al. On the role of resolution and topography in the simulation of East Asia precipitation[J]. Theoretical and Applied Climatology, 2006, 86(1):173-185
[5] Yu E T, Wang H J, Sun J Q. A quick report on a dynamical downscaling simulation over China using the nested model[J]. Atmospheric Ocean Science Letters, 2010, 3(6):325-329
[6] Gao X J, Wang M L, Giorgi F. Climate change over China in the 21st century as simulated by BCC_CSM1.1-RegCM4.0[J]. Atmospheric Ocean Science Letters, 2013, 6(5):381-386
[7] Zou L W, Zhou T J. Near future (2016-40) summer precipitation changes over China as projected by a regional climate model (RCM) under the RCP8.5 emissions scenario:comparison between RCM downscaling and the driving GCM[J]. Advances in Atmospheric Sciences, 2013, 30(3):806-818
[8] Giorgi F, Coppola E, Solmon F, et al. RegCM4:model description and preliminary tests over multiple CORDEX domains[J]. Climate Research, 2012, 52:7-29
[9] Gao X J, Zhang D F, Chen Z X, et al. Land use effects on climate in China as simulated by a regional climate model[J]. Science in China Series:Earth Sciences Earth Sci, 2007, 50(4):620-628
[10] Zhang D F, Zakey A S, Gao X J, et al. Simulation of dust aerosol and its regional feedbacks over East Asia using a regional climate model[J]. Atmospheric Chemistry and Physics, 2009, 9:1095-1110
[11] Gao X J, Shi Y, Zhang D F, et al. Uncertainties in monsoon precipitation projections over China:result from two high-resolution RCM simulations[J]. Climate Research, 2012, 52:213-226
[12] 张冬峰, 高学杰, 罗勇, 等. RegCM4.0对一个全球模式20世纪气候变化试验的中国区域降尺度:温室气体和自然变率的贡献[J]. 科学通报, 2015, 60(17):1631-1642
[13] Gordon H B, Rotstayn L D, McGregor J L, et al. The CSIRO Mk3 climate system model[R]. Technical report No. 60, CSIRO atmospheric research, Aspendale, Victoria, Australia, 2002:130
[14] Gordon H, O'Farrell S, Collier M, et al. The CSIRO Mk3.5 climate model[R]. Technical report No. 21, The center for Australian weather and climate research, Aspendale, Victoria, Australia, 2010:62
[15] Rotstayn L D, Jeffrey S J, Collier M A, et al. Aerosol and greenhouse gas induced changes in summer rainfall and circulation in the Australasian region:a study using single-forcing climate simulations[J]. Atmospheric Chemistry and Physics, 2012, 12:6377-6404
[16] Giorgi F, Jones C, Asrar G, et al. Addressing climate information needs at the regional level:the CORDEX framework[J]. WMO Bulletin, 2009, 58(3):175-183
[17] Gao X J, Shi Y, Giorgi F. Comparison of convective parameterizations in RegCM4 experiments over China with CLM as the land surface model[J]. Atmospheric Ocean Science Letters, 2016, 9(4):246-254
[18] Gao X J, Shi Y, Han Z Y et al. Performance of RegCM4 over major river basins in China[J]. Advances in Atmospheric Sciences, 2017, 34(4):441-455
[19] Kiehl J, Hack J, Bonan G, et al. Description of the NCAR community climate model (CCM3)[R]. NCAR Technical Note, 1993, 11(2):55-60
[20] Holtslag A, Bruijn E, Pan H L. A high resolution air mass transformation model for short-range weather forecasting[J]. Monthly Weather Review, 1990, 118:1561-1575
[21] Pal J S, Small E E, Eltahir E. Simulation of regional-scale water and energy budgets:representation of subgrid cloud and precipitation processes within RegCM[J]. Journal of Geophysical Research Atmospheres, 2000, 105(D24):29579-29594
[22] Emanuel K A. A scheme for representing cumulus convection in large-scale models[J]. Journal of the Atmospheric Sciences, 1991, 48(21):2313-2335
[23] Oleson K W, Niu G Y, Yang Z L, et al. Improvements to the community land model and their impact on the hydrological cycle[J]. Journal of Geophysical Research Atmospheres, 2008, 113:G01021
[24] 韩振宇, 高学杰, 石英, 等. 中国高精度土地覆盖数据在RegCM4/CLM模式中的引入及其对区域气候模拟影响的分析[J]. 冰川冻土, 2015, 37(4):857-866
[25] 吴佳, 高学杰. 一套格点化的中国区域逐日观测资料及与其它资料的对比[J]. 地球物理学报, 2013, 56(4):1102-1111
[26] Xu C H, Xu Y. The projection of temperature and precipitation over China under RCP scenarios using a CMIP5 multi-model ensemble[J]. Atmospheric Ocean Science Letters, 2012, 5(6):527-533
[27] 《第三次气候变化国家评估报告》编写委员会. 第三次气候变化国家评估报告[M]. 北京:科学出版社, 2015
[28] 高学杰, 石英, 张冬峰, 等. RegCM43对21世纪中国区域气候变化的高分辨率模拟[J]. 科学通报, 2012, 57(5):374-381
[29] Diallo I, Sylla M B, Giorgi F, et al. Multimodel GCM-RCM ensemble-based projections of temperature and precipitation over West Africa for the early 21st century[J]. International Journal of Geophysics, 2012, 972896. DOI:10.1155/2012/972896

CSIRO Mk3.6.0模式及其驱动下RegCM4.4模式对中国气候变化的预估

Comparison of Climate Projection Between the Driving CSIRO-Mk3.6.0 and the Downscaling Simulation of RegCM4.4 over China

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