Key Laboratory of Meteorological Disaster/KLME / ILCEC / CIC-FEMD, Nanjing University of Information Science & Technology
本文利用中国气象台站观测降水、英国Hadley中心海温和NCEP/NCAR再分析数据集等资料，研究了2016年秋季中国南方降水异常偏多的环流特征及其海温影响。结果表明，2016年秋季东亚副热带西风急流偏强，我国南方地区位于急流入口区的右侧，有利于产生上升运动；同时西太平洋副热带高压强度偏强、面积偏大、位置偏北偏西，对应副高西南侧的东南风将热带太平洋的暖湿气流向我国南方输送，有利于降水偏多。另外，2016年秋季登陆我国的台风异常偏多，频繁活动的台风给我国南方带来了大量降水，也是导致我国南方降水异常偏多的原因之一。进一步研究表明，2016年秋季南方降水异常偏多主要与同期赤道西太平洋和东南太平洋海温异常偏高有关，上述海区的海温异常通过激发向下游传播的遥相关波列或通过Gill响应对东亚环流产生影响，进而有利于中国南方降水增多。通过CAM5.3（Community Atmosphere Model Version 5.3）一系列的敏感性试验，验证了上述的结果。
Based on the precipitation data from weather stations in China, UK Hadley Centre SST (Sea Surface Temperature) and NCEP/NCAR reanalysis datasets, this paper studies the atmospheric circulation characteristics of the abnormally heavy precipitation events over the southern China in the fall of 2016 and impact of SST. Results show that the subtropical westerly jet in East Asia was much stronger in the fall of 2016, and the southern China was just located to the right of the jet stream entrance, which was conducive to an ascending motion. The western Pacific subtropical high also was much stronger than its normal, with a larger area and more northwestward shifted location. The anomalous southeasterly winds on the southwest side of the western Pacific subtropical high transported warm and moist air from the tropical Pacific to the southern China, leading to heavy precipitation there. In addition, more landing typhoons along the coast of the Southeast China also contributed to the heavy precipitation. Further analysis shows that the heavy rainfall event was mainly related to the abnormally higher SST over the equatorial western and southeastern Pacific simultaneously on inter-annual time scales, and anomalous warming over the North Atlantic on inter-decadal time scales. These aforementioned SST anomalies could affect the East Asian atmospheric circulation through exciting downstream-propagating teleconnection wave trains or Gill-type atmospheric responses. The above results are further confirmed by a series of numerical model simulations using CAM5.3 (Community Atmosphere Model Version 5.3).