| 一种新的El Niño海气耦合指数 |
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| 引用本文： | 陈圣劼,何金海,吴志伟.一种新的El Niño海气耦合指数[J].大气科学,2013,37(4):815-828. |
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| 作者姓名： | 陈圣劼 何金海 吴志伟 |
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| 作者单位： | 南京信息工程大学大气科学学院/气象灾害省部共建教育部重点实验室,南京210044 |
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| 基金项目： | 国家重点基础研究发展计划(973 计划)项目2012CB417403,江苏高校优势学科建设工程资助项目PAPD,国家自然科学基金项目41205066 |
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| 摘 要： | 利用1980～2010 年月平均Hadley中心海表温度、美国全球海洋资料同化系统(GODAS)海洋温度和NCEP/NCAR 大气环流再分析资料,通过对2 个海洋要素(海表温度SST、上层热含量HC)和5 个大气要素(海平面气压SLP、850 hPa 风场、200 hPa 速度势和对外长波辐射OLR)的多变量经验正交函数展开(multivariate EOF,简称MV-EOF)探讨了热带太平洋的主要海气耦合特征。结果表明,MV-EOF 分析的前两个耦合模态分别很好地对应了传统型El Ni?o 和El Ni?o Modoki 的海气耦合特征:传统型El Ni?o 期间,伴随着赤道中东太平洋SST 的异常增温,HC、SLP、200 hPa 速度势等要素总体呈东西反相的“跷跷板”变化,低层850 hPa 赤道中太平洋出现较强西风距平,西北太平洋上空为反气旋性异常环流;El Ni?o Modoki 期间,SST 持续增温和HC 正异常中心均显著西移至中太平洋,低层SLP 和高空200 hPa 速度势均呈现纬向三极型异常分布,低层异常强西风向西移至暖池东部,西北太平洋上空呈现气旋性异常环流。两类El Ni?o 的海气耦合特征存在显著差异,较优的El Ni?o 指数应不仅可以客观描述和区分El Ni?o 现象本身,更要紧密联系两类事件所产生的大气响应。以往定量表征El Ni?o 年际变化的指标大多立足于SST 或SLP,本文选取HC 作为研究指标,定义了一组新的El Ni?o 指数HCEI 和HCEMI。较以往基于SST 的El Ni?o 指数,HCEI 和HCEMI 不仅能更清楚地表征和区分两类El Ni?o(如1993 年的传统型El Ni?o 和2006 年的El Ni?o Modoki),而且能更好地反映和区分两类El Ni?o 与大气间的海气耦合特征,为El Ni?o的监测和短期气候预测工作提供了一个新工具。
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| 关 键 词： | ElNiño ElNiño Modoki 海气耦合特征 热含量指数 MV-EOF |
| 收稿时间： | 2012/3/14 0:00:00 |
| 修稿时间： | 9/8/2012 12:00:00 AM |
New Ocean—Atmosphere Coupling Indices for El Ni?o |
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| CHEN Shengjie,HE Jinhai and WU Zhiwei.New Ocean—Atmosphere Coupling Indices for El Ni?o[J].Chinese Journal of Atmospheric Sciences,2013,37(4):815-828. |
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| Authors: | CHEN Shengjie HE Jinhai and WU Zhiwei |
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| Institution: | Key Laboratory of Meteorological Disaster of Ministry of Education/School of Atmospheric Science, Nanjing University of Information Science & Technology, Nanjing 210044 |
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| Abstract: | Using the monthly mean Met Office Hadley Center sea surface temperature (SST) analyses data, Global Ocean Data Assimilation System ocean temperature data, and NCEP circulation reanalysis datasets for the period 1980-2010, the main ocean?atmosphere coupled processes over the tropical Pacific Ocean were investigated through the multivariate empirical orthogonal functions (MV-EOFs) of two thermal ocean parameters —SST and upper-ocean heat content (HC) — and five meteorological elements — sea level pressure (SLP), 850-hPa u wind, 850-hPa v wind, 200-hPa velocity potential, and outgoing longwave radiation (OLR). Our results show that the temporal and spatial distribution of the first and second MV-EOF modes of the ocean-atmosphere elements capture the ocean?atmosphere couplings of the canonical El Ni?o and El Ni?o Modoki events, respectively. Associated with the warming center in the central and eastern tropical Pacific, the canonical El Ni?o phenomenon is also characterized by the “seesaw” pattern of east?west anti-phase changes in ocean?atmosphere elements such as HC, SLP, and 200-hPa velocity potential. Meanwhile, there are strong westerly anomalies in the central equatorial Pacific and anticyclonic circulation anomalies over the western North Pacific at low atmospheric levels. On the other hand, during the El Ni?o Modoki events, the centers of the positive anomalies of SST and HC moved west to the central equatorial Pacific, and the anomalies of SLP and 200-hPa velocity potential were characterized by a three-polar pattern. Moreover, the low-level strong westerly anomalies moved west to the east of the warm pool, and cyclonic circulation anomalies occurred over the western North Pacific. The ocean?atmosphere couplings of the two types of El Ni?o episodes were significantly different, which suggests that more sophisticated indices for El Ni?o are required to represent and separate the two events more effectively and to better identify their different atmospheric response. Here, in contrast to previously reported El Ni?o indices based on SST or SLP, the El Ni?o signal is represented by HC, and new indices based on HC are defined for the two types of events, which not only capture and characterize the two types more distinctly, for example, the 1993 El Ni?o and 2006 El Ni?o Modoki event, but better identify their ocean?atmosphere coupled process, providing a new approach to monitoring and short-term climate prediction of El Ni?o episodes. |
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