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地球科学进展  2017, Vol. 32 Issue (4): 396-408    DOI: 10.11867/j.issn.1001-8166.2017.04.0396
论文     
BCC_CSM1.1气候模式对全球海表温度年代际变化的回报能力评估
韩振宇1, 吴波2, 辛晓歌1
1.中国气象局 国家气候中心,北京 100081;
2.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
Decadal Prediction Skill of the Global Sea Surface Temperature in the BCC_CSM1.1 Climate Model
Han Zhenyu1, Wu Bo2, Xin Xiaoge1
1. National Climate Center, China Meteorological Administration, Beijing 100081, China;
2. State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics,Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
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摘要:

通过与观测资料和20世纪历史气候模拟试验结果(NoINT)的对比分析,评估了BCC_CSM1.1年代际预测试验(INT)中对全球海表温度(SST)年代际变化的回报能力。分析结果显示:①INT试验模拟的全球平均SST增暖趋势比NoINT的更加接近观测;②其在热带大西洋、热带西太平洋和热带印度洋有较高的预测技巧;③对于太平洋年代际振荡2个关键区——北太平洋和热带中东太平洋,模式的预测技巧较低,且海洋初始化的作用也很小;④在热带南印度洋,INT的预测技巧普遍高于NoINT,在提前3~6年和4~7年时技巧最高。这些结论与基于其他模式得到的已有研究结果类似,但是BCC模式对北大西洋,特别是其副极地区域的预测技巧明显低于其他模式。BCC模式无法合理模拟出北大西洋SST与热盐环流间的交替变化规律,可能是其预测技巧偏低的原因。

关键词: BCC_CSM1.1全球海表温度年代际预测热盐环流    
Abstract:

This study assesses retrospective decadal prediction skill of Sea Surface Temperature (SST) variability in initialized climate prediction experiments (INT) with the Beijing Climate Center Climate System Model (BCC_CSM1.1). Ensemble forecasts were evaluated using observations, and compared to an ensemble of uninitialized simulations (NoINT). The results show as follows: ①The warming trend of global mean SST simulated by the INT runs is closer to the observation than that in the NoINT runs.②The INT runs show high SST prediction skills over broad regions of tropical Atlantic, western tropical Pacific and tropical Indian Oceans. ③ In the North Pacific and the east-central tropical Pacific Ocean, the prediction skills are very weak, and there are few improvements coming from the initialization in the INT runs. ④ In the southern Indian Ocean, the prediction skills of the INT runs are significantly larger than that of the NoINT runs, with the maximum skill at the 3~6 and 4~7 years lead time. The above-mentioned conclusions are similar to the results of other climate models. However, the prediction skill in the North Atlantic Ocean is much lower than that of other models, especially in the subpolar region. The low skills in the Atlantic Ocean may be attributed to the misrepresentation of the lead-lag relationship between the Atlantic meridional heat transport and the SST in the BCC_CSM1.1.

Key words: Decadal prediction    Thermohaline circulation.    Global sea surface temperature    BCC_CSM1.1
收稿日期: 2016-10-17 出版日期: 2017-04-20
ZTFLH:  P467  
基金资助:

公益性行业(气象)科研专项项目“基于FGOALS-s、CMA和CESM气候系统模式的年代际集合预测系统的建立与研究”(编号:GYHY201506012); 中国气象局LCS气候研究开放课题青年基金2016年度资助项目“BCC_CSM1.1模式对中国近期气候的预测能力研究”资助

作者简介: 韩振宇(1987-),男,山西原平人,副研究员,主要从事气候模拟和季风变率研究.E-mail:hanzy@cma.gov.cn
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引用本文:

韩振宇, 吴波, 辛晓歌. BCC_CSM1.1气候模式对全球海表温度年代际变化的回报能力评估[J]. 地球科学进展, 2017, 32(4): 396-408.

Han Zhenyu, Wu Bo, Xin Xiaoge. Decadal Prediction Skill of the Global Sea Surface Temperature in the BCC_CSM1.1 Climate Model. Advances in Earth Science, 2017, 32(4): 396-408.

链接本文:

http://www.adearth.ac.cn/CN/10.11867/j.issn.1001-8166.2017.04.0396        http://www.adearth.ac.cn/CN/Y2017/V32/I4/396

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