| CMIP5模式对中国东北气候模拟能力的评估 |
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| 引用本文： | 陶纯苇,姜超,孙建新.CMIP5模式对中国东北气候模拟能力的评估[J].气候与环境研究,2016,21(3):357-366. |
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| 作者姓名： | 陶纯苇 姜超 孙建新 |
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| 作者单位： | 北京林业大学林学院, 北京 100083,北京林业大学林学院, 北京 100083,北京林业大学林学院, 北京 100083 |
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| 基金项目： | 国家林业公益性行业科研专项201404201,北京林业大学青年科技启动基金资助项目BLX2011002 |
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| 摘 要： | 利用CN05观测资料和参与IPCC第五次评估报告的45个全球气候系统模式的模拟结果,分析了新一代全球气候模式对中国东北三省(1961~2005年)气温和降水的模拟能力。结果表明:1)绝大多数模式都能较好地模拟出研究区内显著增温的趋势,对气温的年际变化模拟能力则相对有限;2)所有模式均能很好地再现气温气候态的空间分布特征,且多模式集合模拟结果优于绝大多数单个模式,空间相关系数达到了0.96;3)对于降水的模拟结果,模式间差异较大,多模式集合能较好地再现其空间分布规律(空间相关系数为0.86),对降水年际变化及线性变化趋势的模拟能力则较差。总体来说,多模式集合对东北气候的时空变化特征具有一定的模拟能力,且对气温模拟效果优于降水,对空间分布的模拟能力优于时间变化。
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| 关 键 词： | CMIP5模式 气温 降水 评估 中国东北三省 |
| 收稿时间： | 2015/5/10 0:00:00 |
| 修稿时间： | 2015/12/14 0:00:00 |
Evaluation of CMIP5 Models Performance on Climate Simulation in Northeast China |
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| TAO Chunwei,JIANG Chao and SUN Jianxin.Evaluation of CMIP5 Models Performance on Climate Simulation in Northeast China[J].Climatic and Environmental Research,2016,21(3):357-366. |
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| Authors: | TAO Chunwei JIANG Chao and SUN Jianxin |
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| Institution: | College of Forestry, Beijing Forestry University, Beijing 100083,College of Forestry, Beijing Forestry University, Beijing 100083 and College of Forestry, Beijing Forestry University, Beijing 100083 |
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| Abstract: | Based on observational data of CN05 (daily observations on a 0.5° latitude-longitude grid over China) and outputs of 45 CMIP5 (Coupled Model Inter-comparison Project Phase 5) models adopted in the Fifth Assessment of the Intergovernmental Panel on Climate Change (IPCC AR5), the capability of new generation climate models on simulating air temperature and precipitation over the three provinces in Northeast China during 1961-2005 are evaluated. Results show that: 1) Most of the models are capable of reproducing the significant warming trend during 1961-2005 in the three provinces in Northeast China; however, they have limited ability to realistically simulate the interannual variation of mean surface air temperature. 2) All models can well capture the spatial distribution of surface air temperature, with the MME (the multi-model ensemble mean) more consistent with observations than results of most individual models (the spatial correlation coefficient between MME and observations is up to 0.96). 3) There are large differences in precipitation simulations between various climate models. Although the multi-model ensemble approach has limited ability in simulating the interannual variation and linear trend of regional mean precipitation, it can better capture the spatial pattern of precipitation than any individual models (the spatial correlation coefficient is up to 0.86). Generally speaking, the multi-model ensemble approach has proven effective at simulating the spatial-temporal variations of surface climate in Northeast China. Specifically, it performs better in the simulation of surface air temperature than the simulation of precipitation. The spatial patterns of surface air temperature and precipitation are also better represented than their temporal variations in the model results. |
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| Keywords: | CMIP5 models Air temperature Precipitation Evaluation Northeast China |
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