【摘要】 基于历史海温数据和台风路径数据,研究了厄尔尼诺/拉尼娜(El Nio/La Nia)背景下7月份中国近海海温变化特征。结果表明:7月黄、东海海温异常与El Nio/La Nia有显著相关关系,OISST和GODAS海温数据与Nio3指数同步相关系数分别为-0.32和-0.45。El Nio年7月,黄、东海海表温度异常低于-0.5℃的概率超过60%;La Nia年7月,黄海海温异常高于0.5℃的概率约有60%;正常年7月,海温异常的空间分布与El Nio年相反,但量值偏低。El Nio年7月,中国近海及邻近区域大气异常能够给局地带来更多降水;同时,受El Nio背景场的影响,入侵黄、东海的台风强度更强、影响时间更长。大尺度的降水和台风活动的影响是导致黄、东海海温异常降低的重要原因。因此,分析和预测7月份中国近海海温异常,在充分考虑El Nio/La Nia背景场的基础上,需要结合局地的大尺度降水和台风的影响同时分析,这为特定背景下结合不同时间尺度上的因素共同分析中国近海海温变化提供了一种思路。更多还原

【Abstract】 Historical sea temperature and typhoon track datasets are used to study the SST variations of the Yellow Sea and East China Sea influenced by ENSO in the July.The results show that SST anomalies of the Yellow Sea and the East China Sea correlate well with the Nio 3 index,the correlation coefficient between the OISST dataset and Nio3 index is-0.32 in July,while it’s-0.45 when we use the GODAS dataset.There are more than 60% probability that SST anomalies would below-0.5℃ of the Yellow Sea and the East China Sea in July in the El Nio years.While in La Nia years,most part of the Yellow Sea has almost 60% probability the SST anomalies would surpass 0.5℃in July.Spatial distributions of SST anomalies in normal years are opposite to that in El Nio years in July,but with low magnitudes.The atmospheric circulation anomalies on the China adjacent seas could bring more precipitation to local area in the July of El Nio years.Meanwhile,the typhoon intensities tend to be stronger,the duration time tends to be longer and the typhoon tracks tend to pass the Yellow Sea and East China Sea in July in the El Nio years.Large-scale precipitation and the typhoon activities are the reasons that result in the negative SSTA of the Yellow Sea and East China Sea.Therefore,based on the El Nio/La Nia background analysis,the effect of large-scale precipitation and typhoon activities should also be taken into consideration when we analyze and forecast the SST anomalies of China adjacent seas in July.This proves us a new mind to analyze the SST anomalies of China adjacent seas by considering different factors with different time-scales under certain background.更多还原