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中国农学通报 ›› 2016, Vol. 32 ›› Issue (2): 149-154.doi: 10.11924/j.issn.1000-6850.casb15040110

所属专题: 农业气象

• 资源 环境 生态 土壤 气象 • 上一篇    下一篇

华北冬季大雪频次变化特征及对海温的响应

陈凯奇1,房一禾2,张 蕊3,祝新宇4,赵连伟2,张海娜2,吴 琼2   

  1. (1兰州大学大气科学学院,兰州 730000;2沈阳区域气候中心,沈阳 110166;3东陵区气象局,沈阳 110016;4辽宁省防雷技术服务中心,沈阳 110166)
  • 收稿日期:2015-04-14 修回日期:2015-12-27 接受日期:2015-05-20 出版日期:2016-01-28 发布日期:2016-01-28
  • 通讯作者: 赵连伟
  • 基金资助:
    辽宁省气象局科学技术研究项目(201502);辽宁省科技厅农业攻关及产业化项目(2015103038);公益性行业(气象)科研专项 (GYHY201306049) 和公益性行业(气象)科研专项(GYHY201306050)。

Variation Characteristics of Heavy Snow Frequency in North China and Its Response to Sea Surface Temperature

Chen Kaiqi1, Fang Yihe2, Zhang Rui3, Zhu Xinyu4, Zhao Lianwei2, Zhang Haina2, Wu Qiong2   

  1. (1College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000; 2Regional Climate Center of Shenyang, Shenyang 110016; 3Meteorological Bureau of Dongling District, Shenyang 110016; 4Liaoning Lightning Protection Technique Service Center, Shenyang 110016)
  • Received:2015-04-14 Revised:2015-12-27 Accepted:2015-05-20 Online:2016-01-28 Published:2016-01-28

摘要: 为了解华北冬季大雪频次变化特征及与前期海温的关系,达到为冬季设施农业等服务的目的,采用华北区282站逐日降水量资料、NCEP再分析资料,计算了华北冬季的大雪频次,分析了近51年来华北冬季大雪频次的时空特征及与前期海温的关系。结果表明:近51年来,华北冬季大雪强度呈上升趋势,有明显的年代际变化特征;华北冬季大雪频次EOF第1模态呈全区一致的特征,第2模态由北向南依次呈“+-+”的特征。年际尺度上,影响第1模态的海温关键区为:前夏(秋)热带印度洋和北大西洋;第2模态关键区为:前夏(秋)赤道东太平洋海温,即与厄尔尼诺关系密切。年代际尺度上,影响第1模态的海温关键区为:前夏亲潮区、热带印度洋和北大西洋,第2模态与PDO关系密切。

关键词: 花生, 花生, 亲缘关系, 共祖先度, 主要性状, 遗传改良

Abstract: The study aims to gain a comprehensive understanding of the variation characteristics of the winter heavy snow frequency in north China and the relationship between the winter heavy snow frequency in north China and sea surface temperature, thus to serve winter agricultural facilities. Based on the daily precipitation data of 282 observational stations in north China and NCEP reanalysis data, the winter heavy snow frequency in north China was calculated, the spatial and temporal features of the winter heavy snow frequency were analyzed. Results showed that: during the recent 51 years, the winter heavy snow frequency in north China was descending, and presented an obvious inter-decadal variation characteristic. The first EOF mode of heavy snow frequency presented a consistent variation characteristic in the entire region, the second EOF mode presented “ - ” pattern, the first time coefficients appeared an obvious inter-decadal variation characteristic. The key SST regions of the first EOF mode were respectively the tropical Indian Ocean and the North Atlantic Ocean. There was a close relationship between the second EOF mode and El Nino. The key SST regions of the inter-decadal component of the first EOF mode were respectively Oyashio, the tropical Indian Ocean and the North Atlantic Ocean. There was a close relationship between the inter-decadal component of the second EOF mode and PDO.

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