地理科学 ›› 2013, Vol. 33 ›› Issue (8): 986-992.doi: 10.13249/j.cnki.sgs.2013.08.986

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西太平洋暖池区热含量和海表温度与江南春雨的相关性对比研究

尚可1,2(), 何金海1,3, 朱志伟1, 詹丰兴1,4   

  1. 1.南京信息工程大学,气象灾害省部共建教育部重点实验室,江苏 南京 210044
    2.河北省气象台,河北 石家庄 050021
    3.中高纬度环流系统与东亚季风研究开放实验室,吉林 长春 130062
    4.江西省气象局, 江西 南昌 330046
  • 收稿日期:2013-01-05 修回日期:2013-03-20 出版日期:2013-08-20 发布日期:2013-08-20
  • 作者简介:

    作者简介:尚 可(1989-),女,河北石家庄人,硕士,助理工程师。主要研究方向为季风与海气相互作用。E-mail:shangkedd@163.com

  • 基金资助:
    国家重点基础研究发展计划(973计划)项目(2012CB417403)、国家自然科学基金项目(41175083,41275096)、长江学者和创新团队发展计划(PCSIRT)和江苏高校优势学科建设工程资助项目(PAPD)资助

Comparison Between Correlations of Heat Content and Sea Surface Temperature over Western Pacific Warm Pool with Spring Persistent Rains

Ke SHANG1,2(), Jin-hai HE1,3, Zhi-wei ZHU1, Feng-xing ZHAN1,4   

  1. 1.Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science & Technology, Nanjing ,Jiangsu 210044,China
    2.Hebei Meteorological Observatory, Shijiazhuang, Hebei 050021,China
    3. Laboratory of Research for Middle-High Latitude Circulation and East Asian Monsoon, Changchun, Jilin 130062,China
    4.Jiangxi Provincial Meteorological Bureau, Nanchang ,Jiangxi 330046, China
  • Received:2013-01-05 Revised:2013-03-20 Online:2013-08-20 Published:2013-08-20

摘要:

利用Scripps和GODAS(Global Ocean Data Assimilation System)月平均海温资料,NOAA(National Oceanic and Atmospheric Administration)提供的逐月扩展重建海表温度资料以及中国气象局气象信息中心提供的中国753站逐日降水资料,分析了江南春雨的时空分布特征,通过SVD(Singular Value Decomposition)、时滞相关方法从预报的角度对西太平洋暖池区海表温度和热含量与江南春雨的关系进行对比分析。结果表明:近50 a江南春雨空间分布的主要模态为全区一致型分布,其次为南北反向型,第三模态表现为东西反向型;西太平洋暖池区热含量与江南春雨强度的关系比海表温度更为密切,从相关区域的集中性、稳定性及相关显著性和预报超前性等方面综合考虑,推荐将热含量作为预报江南春雨的首要因子。热含量影响江南春雨的敏感海区位于4°N ~16°N,130°E~170°E,预报关键时段为前一年7~12月。

关键词: 西太平洋暖池, 热含量, 海表温度, 江南春雨

Abstract:

:In this article, the spatial and temporal distribution of SPR (Spring Persistent Rains) are analyzed first. Then, the correlations of heat content and sea surface temperature over the west pacific warm pool with SPR are discussed comparatively through methods of SVD (Singular Value Decomposition) and lag correlation from the predicting point of view. Data used in this work comes from Scripps and GODAS (Global Ocean Data Assimilation System) monthly mean sea temperature, the NOAA (National Oceanic and Atmospheric Administration) ERSST (Extended Reconstructed Sea Surface Temperature) V3b, and precipitation from 753 Chinese meteorological stations. The results indicate that the typical pattern of annual SPR varies according to three principal modes in the last 50 years: the first mode changes in dry-wet consistency, the second with an opposite phase meridionally and the third with an opposite phase zonally. SPR and heat content are more correlated compared to sea surface temperature. It is suggested then, that heat content over western pacific warm pool can be selected as the chief factor predicting SPR when taking the centrality, stability, significance and predictability of the key regions into consideration comprehensively. The Key region(4°N~16°N,130°E~170°E) of heat content and the key period of time(July to December in the former year) which influences the intensity of SPR have been obtained respectively.

Key words: western pacific warm pool, heat content, sea surface temperature, Spring Persistent Rains

中图分类号: 

  • P732.6