我国南方冬季异常低温和异常降水事件分析

统计分析1951年以来1月份以及1880年以来冬季．我国南方的异常低温与降水事件，结果表明1月异常低温（温度距平〈-1σ）有12次，降水异常偏多（降水距平〉＋1σ）有10次．冷湿组合有3次（1969、1993、2008）；冬季异常低温有29次．降水异常偏多有16次，冷湿组合存2次（1886／87、1904／05）．利用NCEP／NCAR再分析资料等．采用合成方法分析异常低温与异常降水事件时大气环流特征，结果表明有利于南方低温的环流特征是：西们利亚高压、东业大槽及东亚急流异常偏强。有利于降水偏多的环流特征是：东亚大槽偏弱；200hPa上中东急流异常偏强、东亚急流偏弱：东亚从对流层低层到中高层都有异常南风。当发生冷湿组合时，低温主要是受到西伯利亚冷高压异常偏强的影响．而降水主要受对流层850hPa至200hPa环流异常的作用。南方冬季水汽主要来自南支槽的西南气流和南海上空的转向气流，在降水偏多时有异常西南水汽输送距平。西伯利亚高压、欧亚遥相关型、西太平洋遥相关型、北极涛动4个环流因子能解释南方1月和冬季气温方差的47．2％和51．5％：而中东急流、东亚经向风、欧亚遥相关型则能共同解释南方1月和冬季降水方差的49．4％和48．4％。统计降水异常与ENSO的对应关系表明．当发生E1 Nifio事件时南方冬季降水偏多的概率较大，当发生LaNifia事件时，降水偏少的概率较大，而温度与ENSO没有明显的统计相关。

Anomalous Winter Temperature and Precipitation Events in Southern China

This paper analyzed the anomalous low-temperature events, and the anomalous rain-abundant events over southern China for Januaries since 1951 and for winters since 1880, there anomalous events are defined using ±1σ thresholds. And 12 cold temperature Januaries are identified where temperature anomaly is below - 1σ, and 10 wet Januaries are identified where precipitation anomaly is above +1σ.Among these events there are 3 cold-wet Januaries, namely 1969, 1993 and 2008. Using NCEP/NCAR reanalysis data, the authors checked the atmospheric circulation changes in association with the anomalous temperature and precipitation events. The results show that the strong Siberian high (SBH), East Asian Trough (EAT) and East Asian Jet Stream (EAJS) are favorable conditions for low temperature in southern China. While the anomalous south-wind at 850 hPa, the weak EAT at 500 hPa, and the strong Middle East Jet Stream (MEJS) and the weaker EAJS are found to accompany a wetter southern China. The cold-wet winters in southern China, such as January of 2008, are mainly related to a stronger Siberian High, and at the same time the circulation anomalous in middle to upper troposphere is precipitation-favorable. In wet winters, the water vapor below 500 hPa are mainly transported by the anomalous southwesterly flow and the anomalous southern flow over the Indo-China Peninsula and the South China Sea area. The correlation coefficients of MEJS, EAMW (East Asian Meridional Wind), EU (Eurasian pattern) to southern China precipitation in January are +0.65, - 0.59 and - 0.48 respectively, and the correlation for the high-pass filtered data are +0.63, - 0.55 and - 0.44, respectively, their correlations are all significant at the 99% level. MEJS, EAMW and EU together can explain 49.4% of the variance in January precipitation. Explained variance for January and winter temperature by Siberian High, EU, WP (Western Pacific pattern) and AO (Arctic Oscillation) are 47.2% and 51.5%, respectively. There are more precipitation in southern China during El Nino winters, and less precipitation during La Nina winters. And there is no clear evidence that occurrences of anomalous temperature events in winter in southern China are closely linked with ENSO events.