| CMIP5多模式集合对江苏省气候变化模拟评估及情景预估 |
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| 引用本文： | 赵亮,刘健,靳春寒.CMIP5多模式集合对江苏省气候变化模拟评估及情景预估[J].气象科学,2019,39(6):739-746. |
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| 作者姓名： | 赵亮 刘健 靳春寒 |
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| 作者单位： | 南京师范大学 虚拟地理环境教育部重点实验室/江苏省地理环境演化国家重点实验室培育建设点/江苏省地理信息资源开发与利用协同创新中心/地理科学学院, 南京 210023,南京师范大学 虚拟地理环境教育部重点实验室/江苏省地理环境演化国家重点实验室培育建设点/江苏省地理信息资源开发与利用协同创新中心/地理科学学院, 南京 210023;南京师范大学 江苏省大规模复杂系统数值模拟重点实验室/数学科学学院, 南京 210023;青岛海洋科学与技术试点国家实验室海洋-气候-同位素模拟开放工作室, 山东 青岛, 266237,南京师范大学 虚拟地理环境教育部重点实验室/江苏省地理环境演化国家重点实验室培育建设点/江苏省地理信息资源开发与利用协同创新中心/地理科学学院, 南京 210023 |
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| 基金项目： | 国家自然科学基金资助项目（41420104002）；国家重点研发计划项目（2016YFA0600401）；江苏省高校大学生创新创业计划项目（201610319099X）；江苏省高校优秀科技创新团队项目（111110B11511）；江苏省高校优势学科建设项目（164320H116） |
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| 摘 要： | 利用中国气象局所属的2 400余个台站观测资料制作的分辨率为0.25°×0.25°数据集中的气温、降水量资料评估了CMIP5中17个模式对于1961—2004年江苏省气温和降水量空间分布特征的模拟能力,筛选出了5个对江苏省气候特征模拟较好的模式。之后基于5个优选模式集合平均的结果预估了3种典型浓度路径(Representative Concentration Pathways,RCPs)下江苏省2006—2100年的气温和降水量变化趋势。结果表明:(1)全球耦合气候模式对江苏省的气温和降水量空间分布特征具有一定的模拟能力,并且模式集合平均的气温和降水量与观测资料的空间相关系数分别为0.85和0.93;(2)在低浓度路径(RCP2.6)、中浓度路径(RCP4.5)和高浓度路径(RCP8.5)3种温室气体排放情景下,江苏省2006—2100年的地表温度均呈现明显的增温趋势,并且苏北的增温幅度要高于苏南;(3)3种温室气体排放情景下,江苏省未来百年降水量均呈现出北方增多南方减少的趋势;(4)未来百年江苏省降水量随气温变化的趋势并不稳定,RCP2.6和RCP4.5情景下降水量随气温的升高而增加,而RCP8.5情景下降水量随气温的增加而减少。
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| 关 键 词： | 气候变化 气候预估 多模式集合 典型浓度路径 江苏省 |
| 收稿时间： | 2018/3/31 0:00:00 |
| 修稿时间： | 2018/6/8 0:00:00 |
Evaluation and projection of climate change in Jiangsu Province based on the CMIP5 multi-model ensemble mean datasets |
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| ZHAO Liang,LIU Jian and JIN Chunhan.Evaluation and projection of climate change in Jiangsu Province based on the CMIP5 multi-model ensemble mean datasets[J].Scientia Meteorologica Sinica,2019,39(6):739-746. |
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| Authors: | ZHAO Liang LIU Jian and JIN Chunhan |
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| Institution: | Key Laboratory for Virtual Geographic Environment of Ministry of Education/State Key Laboratory of Geographical Evolution of Jiangsu Provincial Cultivation Base/Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application/School of Geography Science, Nanjing Normal University, Nanjing 210023, China,Key Laboratory for Virtual Geographic Environment of Ministry of Education/State Key Laboratory of Geographical Evolution of Jiangsu Provincial Cultivation Base/Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application/School of Geography Science, Nanjing Normal University, Nanjing 210023, China;Jiangsu Provincial Key Laboratory for Numerical Simulation of Large Scale Complex Systems/School of Mathematical Science, Nanjing Normal University, Nanjing 210023, China;Open Studio for the Simulation of Ocean-Climate-Isotope, Pilot National Laboratory for Marine Science and Technology, Shandong Qingdao 266237, China and Key Laboratory for Virtual Geographic Environment of Ministry of Education/State Key Laboratory of Geographical Evolution of Jiangsu Provincial Cultivation Base/Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application/School of Geography Science, Nanjing Normal University, Nanjing 210023, China |
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| Abstract: | Based on the CN05.1 dataset and the simulations of the historical simulation from 17 CMIP5 models, their simulating capabilities for the climatology of the annual mean surface temperature and daily mean precipitation over the Jiangsu Province from 1961 to 2004 have been examined. Five optimal models are selected to estimate the climate change under the representative concentration pathways over the Jiangsu Province from 2006 to 2100. The results are as followings:(1) Global Coupled Climate Model has a certain ability to stimulate the spatial distribution characteristics of temperature and precipitation in Jiangsu Province, and the correlation coefficients between the multi-model ensemble mean and the observation data of the temperature and precipitation are 0.85 and 0.93, respectively. (2) The temperature in Jiangsu Province from 2006 to 2100 presents a significant increasing trend under the low concentration path(RCP2.6), medium stable concentration path(RCP4.5) and high concentration path(RCP8.5). The warming range over northern Jiangsu is higher than that over southern Jiangsu. (3) However, the precipitation in the coming 100 years does not show an obvious tendency under the three RCPs, as the precipitation over the southern Jiangsu decreases and that over the northern Jiangsu increases. (4) Moreover, under the three RCPs, the trend of precipitation in Jiangsu is not stable with the surface temperature change. The precipitation increases with the increase of the temperature under the RCP2.6 and RCP 4.5, while the precipitation under the RCP8.5 decreases with the increase of temperature. |
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| Keywords: | climate change climate projection multi-model ensemble mean representative concentration pathways(RCPs) Jiangsu Province |
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