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Inter-decadal Variability of the Relationship Between Winter Temperature in China and Its Impact Factors
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摘要: 利用1951—2012年冬季全国160个站月平均气温以及NCEP/NACR再分析资料和海温、北极海冰等资料，分析了我国冬季气温及其关键影响因子的年代际变化特征，重点研究了关键影响因子对我国冬季气温影响关系的年代际变化。研究表明:我国冬季气温在1985年之前处于冷期，之后为暖期; 我国冬季气温异常与影响因子的关系发生了显著的年代际变化，而且影响因子之间的关系也发生了显著的年代际变化。针对这种年代际变化的基本事实，提出针对冷期和暖期中不同影响因子与冬季气温的关系分时段建立冬季气温的多因子回归预测模型，可以反映冬季气温及其影响因子关系的年代际变化特征。正确的预测策略是利用相同年代际背景下预测对象与预测因子的时间序列资料建立预测模型，以确保预测模型中反映的预测对象与预测因子关系的稳定性，进而保持较高的拟合及预测水平。Abstract: The inter-decadal variation characteristics of winter temperature in China and its key impact factors are analyzed by using monthly temperature data of 160 stations in China, NCEP/NACR reanalysis data, extended reconstructed sea surface temperatures data, and Arctic sea ice extent data from 1951 to 2012, focusing on the inter-decadal changes of the relationship between key influencing factors and winter temperature in China. Results show that the winter temperature in China before 1985 is in a cold period, and then a warm period follows. A significant inter-decadal variability has occurred for winter temperature anomalies. The scope and intensity of warming tendency has weakened significantly from 2004 to 2011.The main diagnostic analysis conclusions are summarized as follows. The majority of impact factors of winter temperature anomalies in China shows significant inter-decadal shift from 1970s to 1980s, most of which changes ahead of that of winter temperatures in China, such as Arctic Oscillation (AO), the East Asian winter monsoon (EAWM), Western Pacific subtropical high (WPSN), Arctic sea ice cover in September, and Niño3 SST index. But the inter-decadal variability of Siberian High (SH) and the basin-wide SSTA variation in the tropical Indian Ocean (IOBW) has the same pace with that of the winter temperature. The inter-decadal variability of relationship between winter temperature and its impact factors have changed on temporal and spatial scales. On temporal scale, the relationship between the winter temperature and IOBW index has weakened significantly from cold to warm period. But the influences of EAWM index, SH index and the WPSH area index on winter temperature have strengthened. On spatial scales, distributions of correlations between winter temperatures and affecting factors have changed from cold to warm period. The high correlation coefficient regions between EAWM and winter temperature have enlarged significantly. The correlation coefficient between AO index and winter temperature is negative in central-southern China in warm period. The inter-decadal variability of relationship between the impact factors has changed, the relationship between EAWM index and tropical SSTA in winter are significantly weakened from cold to warm period.Based on the basic facts of inter-decadal variations, a multi-factor regression prediction model of winter temperature can be established respectively in cold and warm period. This regression prediction model can reflect inter-decadal characteristics of relationship between the winter temperature and its impact factors. Such strategy may keep the stability and effectiveness of the prediction skill for winter temperature in China.
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图 1 1951—2011年全国冬季月平均气温距平演变
(断线为气温距平滑动t统计量，横点线为滑动t检验量0.01显著性水平临界值)
Fig. 1 Anomalies of the winter temperature in China from 1951 to 2011
(dashed line: moving t-test statistic value; straight dotted line: 0.01 significant level critical value)
图 2 1951—2012年全国平均冬季12月 (a)、1月 (b)、2月 (c)气温距平演变
Fig. 2 Anomalies of the temperature in December (a), January (b) and February (c) over China
图 3 冷期 (a) 和暖期 (b) 冬季500 hPa位势高度场距平
Fig. 3 Average anomalies of geo-potential height at 500 hPa during cold episodes (a) and warm episodes (b) in winter
图 4 1951—2011年冬季60°—70°E区域平均500 hPa位势高度距平的时间-纬度剖面图 (单位：dagpm)
Fig. 4 Latitude-time section of 60°—70°E average anomalies at 500 hPa in winter from 1951 to 2011 (unit:dagpm)
图 5 我国冬季气温的关键影响因子累积距平曲线
Fig. 5 Cumulative anomalies of the key affecting factors of winter temperature in China
图 6 我国冬季气温与关键影响因子相关分布
(阴影表示达到0.05显著性水平区域)
Fig. 6 The correlation coefficients between winter temperature and key affecting factors
(shaded areas denote passing the test of 0.05 level)
图 7 冷期 (a) 和暖期 (b) 冬季风指数与同期海温相关图
(阴影区相关系数达到0.05显著性水平)
Fig. 7 The correlation coefficients between winter monsoon index and simultaneous SSTs in cold episodes (a) and warm episodes (b)
(shaded areas denote passing the test of 0.05 level)
图 8 试验1模型拟合、试验2模型拟合、试验3模型拟合和观测的冬季气温标准化时间序列
Fig. 8 The hindcast winter temperature by Test 1， Test 2, Test 3 and the time series of standardized observed temperature
表 1 大气外强迫因子和环流因子与我国冬季气温的相关系数
Table 1 The correlation coefficients of winter temperature to external forcing and circulation factors
因子 时间 秋季 冬季 黑潮海温 全时段 0.10 0.36* 冷期 0.20 0.53* 暖期 0.04 0.12 IOBW 全时段 0.10 0.28* 冷期 0.15 0.33* 暖期 0.20 0.18 北极海冰 全时段 0.33*(9月) 0.20 冷期 0.03(9月) 0.06 暖期 0.61*(9月) 0.38* 冬季风 全时段 -0.30* -0.58* 冷期 -0.15 -0.52* 暖期 0.08 -0.67* 西伯利亚高压 全时段 -0.07 -0.59* 冷期 -0.24 -0.50* 暖期 0.20 -0.76* 副高面积 全时段 0.21 0.34* 冷期 0.29 0.31* 暖期 0.10 0.40* 高原高度场 全时段 0.15 0.49* 冷期 0.19 0.55* 暖期 0.07 0.37 AO 全时段 -0.04 0.19 冷期 -0.03 0.16 暖期 -0.07 0.19 注：*表示相关系数达到0.05显著性水平。 
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