摘要:本文基于中国地面气温日值网格数据集（V2.0），采用滑动相关和相关分析等方法，揭示了冬季北大西洋涛动（NAO）对中国北方极端低温影响的事实，进一步证实了东北后冬（1、2月）冷日（夜）与同期NAO相关性的年代际变化。研究发现：在20世纪80年代中期前，东北后冬冷日（夜）频发，与NAO的相关性较好，而在80年代中期后东北后冬冷日（夜）少发，与NAO的相关性减弱。其中，1月在1969~1988阶段，东北冷日（夜）与NAO的相关性最好，相关区域显著，相关系数可达-0.68（-0.66），而在1989~2009阶段二者相关性最弱，相关区域不显著。进一步分析发现，在不同年代际背景下，NAO引起的大气环流异常是导致东北1月冷日（夜）与1月NAO相关性年代际变化的重要原因。相关性较好的年代，NAO引起的环流异常有利于冷涡等天气系统维持在贝加尔湖到东北一带，使东北地区气温偏低，冷日（夜）频发；相关性较弱的年代，不利于冷空气南下，使东北地区气温偏高，冷日（夜）少发。
关键词:极端温度/
北大西洋涛动/
相关分析/
年代际变化
Abstract:Based on the gridded daily surface air temperature database (V2.0) of China, the influences of wintertime North Atlantic Oscillation (NAO) on extreme low temperature over northern China are investigated. The interdecadal variation in the relationship between NAO and cold days (nights) during the same period over Northeast China (NEC) in late winter is revealed based on sliding correlation analysis and correlation analysis. The results show that cold days (nights) are more frequent in late winter over NEC and have a better correlation with NAO before the middle 1980s compared to that after the middle 1980s. Additionally, the correlation was most significant over NEC in January during the period of 1969-1988, which could reach ?0.68 (?0.66), but became weak during the period of 1989-2009. Furthermore, it is found that the interdecadal variation in the relationship between NAO and cold days (nights) over NEC in January is largely attributed to the NAO-related atmospheric circulation anomalies under different interdecadal backgrounds. The weather systems such as cold vortex caused by the NAO-related atmospheric circulation anomalies can maintain over a large area from Lake Baikal to NEC, leading to lower than normal temperature and more frequent cold days (nights) over NEC in the years when significant correlation exists between NAO and cold days (nights). The opposite is true when there is no significant correlation between NAO and cold days (nights) in NEC.
Key words:Extreme temperature/
NAO (North Atlantic Oscillation)/
Correlation analysis/
Interdecadal variation
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