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| 基于T106L26全球大气环流模式的夏季集合预报 | |
| 引用本文： | 朱春子,李清泉,王兰宁,王在志,刘文泉.基于T106L26全球大气环流模式的夏季集合预报[J].大气科学学报,2013,36(2):192-201. |
| 作者姓名： | 朱春子 李清泉 王兰宁 王在志 刘文泉 |
| 作者单位： | 1. 南京信息工程大学大气科学学院,江苏南京210044;国家气候中心,北京100081 2. 国家气候中心,北京,100081 3. 北京师范大学全球变化与地球系统科学研究院,北京,100875 4. 中国气象局,北京,100081 |
| 基金项目： | 国家重点基础研究发展计划项目，国家高技术研究发展计划项目，公益性行业(气象)科研专项(GYHY |
| 摘 要： | 使用国家气候中心新一代大气环流模式BCC_AGCM2.0(T106L26)进行22 a夏季(6-8月)、11个成员的集合回报试验;针对500 hPa高度场、降水和气温的预测能力进行交叉检验,并计算其均方根误差.结果表明:模式对热带地区、海洋和欧亚大陆部分地区500 hPa高度场的模拟较好;对我国长江中下游、华南大部分地区降水的模拟具有一定可信度;2m温度距平在我国北方大部分地区呈现正相关且相关系数通过90％的信度检验,在南方地区则有待改善.集合预报效果好于单样本预报.模式分辨率的提高在一定程度上有助于改进预报效果. |
| 关 键 词： | 高分辨率大气环流模式 季节预测 交叉检验 集合预报 |
| 收稿时间： | 2011/3/26 0:00:00 |
| 修稿时间： | 2012/12/12 0:00:00 |
An ensemble forecast for summer with a global atmospheric general circulation model T106L26 |
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| ZHU Chun-zi,LI Qing-quan,WANG Lan-ning,WANG Zai-zhi and LIU Wen-quan.An ensemble forecast for summer with a global atmospheric general circulation model T106L26[J].大气科学学报,2013,36(2):192-201. | |
| Authors: | ZHU Chun-zi LI Qing-quan WANG Lan-ning WANG Zai-zhi and LIU Wen-quan |
| Institution: | School of Atmospheric Sciences, NUIST, Nanjing 210044, China;National Climate Center, Beijing 100081, China;National Climate Center, Beijing 100081, China;College of Global Change and Earth System, Beijing Normal University, Beijing 100875, China;National Climate Center, Beijing 100081, China;China Meteorological Administration, Beijing 100081, China |
| Abstract: | The ensemble hindcast experiments of 11 members in summer(JJA) of 22 years were conducted by the BCC_AGCM2.0(T106L26) developed by National Climate Center.The capability of prediction in 500 hPa geopotential height,precipitation,and 2 m air temperature were tested by the cross validation and root mean square error methods.Results indicate that the model shows a good performance of 500 hPa geopotential height in the tropical region,oceans and parts of Eurasia.The simulation of precipitation over the mid-lower reaches of Yangtze River and most parts of South China has considerable reliability.The correlation coefficients of the 2 m air temperature anomalies in most parts of northern China are positive and pass the local significance test at 90% confidence level.However,the results in southern China are needed to be improved.Meanwhile,the ensemble forecast is much better than the single-sample prediction.The forecasting results can be improved by using the higher resolution atmospheric general circulation model. |
| Keywords: | high resolution atmospheric general circulation model seasonal forecast cross validation ensemble forecast |
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