长江流域梅雨的多尺度特征及其与全球海温的关系

Multiple Scale Characteristics for Precipitation over the Yangtze River Valley during the Meiyu Period and Their Relationships with the Global Sea Surface Temperature

利用EOF和小波变换方法讨论了长江流域梅雨期降水的多时空尺度特征.长江流域梅雨期降水空间分布主要存在3种类型:(1)江南北部多雨、黄淮少雨型;(2)长江中下游多雨、江南南部少雨型;(3)江淮流域、华南东南部多雨及江南北部、华北地区少雨型.时间尺度主要周期为:准2年、3～5年、准10年振荡和线性增加趋势.长江流域梅雨期降水的各主要周期与前期(秋、冬和春季)全球海温相关分析表明,前期各季海温相关以冬季相关最好.年际、准2年及3～5年振荡周期对应的海温关键区,主要在热带和副热带地区;年代际及准10年振荡周期对应的海温关键区,主要在温带海洋;线性增加趋势的海温关键区,则遍布全球海洋.选取显著性水平达到0.05的相关区域海温距平的平均值作预报因子,利用逐步回归方法对梅雨期降水距平进行回报和预报试验的结果表明,综合考虑不同时间尺度的海温因子共同作用后建立的预测模型,对预测我国梅雨期降水距平的分布,有一定的预报能力.

The multiple temporal and spatial scale characteristics of rainfall over the Yangtze River valley during the Meiyu period is studied by EOF and wavelet analysis.There are three main spatial patterns for the precipitation over the Yangtze River and Huaihe River valleys: The first case is that the rainfall was more than normal in the north of southern china, and was less than normal over the regions of Yellow River and Huaihe River valleys; The second case is that the positive anomalous precipitation appeared in the Yangtze River valley, and the negative anomalous precipitation appeared in south of southern China; The third case is that the precipitation increased in the region between the Yangtze River and Huaihe River valleys, and the decreased in the north of southern China as well as northern China.The quasi biennial oscillation (QBO), 3—5-year oscillation, quasi decadal oscillation and linear tendency are the basic periods for the rainfall in the Yangtze River and Huaihe River valleys:The correlation coefficients between the temporal series of the four scale for rainfall and the global sea surface temperature anomalies (SSTA) in autumn, winter and spring showed that the closed relationship appeared in winter, and the largest correlation coefficients occurred at the tropic-subtropical ocean area for annual variation. The regression equation of forecasting precipitation over the Yangtze River and Huaihe River valleys during the Meiyu period was setup using the stepwise regression, and which showed there is the better improved for forecasting results.