澜沧江流域暴雨干旱灾害与海温异常波动规律的相关性

基于中国气象局国家气象信息中心提供的澜沧江区域1961—2011年50年气象资料,采用EMD(Empirical Mode Decomposition)分解、均生函数逐步回归模型、相关分析等方法,探讨了澜沧江流域极端天气灾害的变化特征,及其区域极端灾害变化和全球海温异常ENSO(El Nio/La Nia-Southern Oscillation)之间的联系。结果表明:(1)该区域降水和暴雨频次存在多尺度特征,降水量存在2a、7a、15a的变化周期,且主周期为准2 a。(2)降水量和暴雨频度序列的IMF1和IMF2周期在2—7 a之间,与ENSO在年际变化上的信号相吻合,NINO(El Nio)指数无论春夏秋冬或年际都与暴雨和干旱灾害频次呈现负相关,而SOI(Southern Oscillation Index)指数则呈现正相关,其中,NINO指数与干旱相关性指数在秋冬和年际接近-0.3。(3)澜沧江流域暴雨和干旱灾害与ENSO有重要联系,且随着气温升高干旱灾害频次明显增加。研究结果显示区域极端气温灾害的变化与全球气候变暖有某种关联,是全球气候变化的区域响应表现形式之一。

Correlation between the regularity of abnormal fluctuation of sea surface temperature and rain and drought disasters in the Lancang River Basin

Extreme weather events occur frequently under conditions of global climate change. These extreme events are considered by many scholars to be due to climate warming. However, the mechanisms governing extreme weather events as regional responses to global climate change are unclear, as is the attribution of such extreme disasters to particular sources. Globally, the oceans are one of the most important sources of power, heat, and water vapor transmission, and significant variations of the sea surface temperature (SST) will lead to global climate change. Based on 50 years of'' meteorological data (1961-2011) for the Lancang region, obtained from the National Meteorological Information Center, the techniques of wavelet analysis, empirical mode decomposition (EMD), mean generating function stepwise regression model, and correlation analysis were used to investigate the link between regional extreme weather disasters in the Lancang River Basin and global climate change from the latter half of the 20th century to the early 21st century. The results showed that various multi-scale features exist in the regional precipitation and storm frequency data with periods of 2, 7, and 15 years, with the 2-year cycle being the most important. The EMD method was considered more suitable than wavelet analysis for determining the main cycles because it was better able to deal with non-stationary nonlinear signals. The IMF1 and IMF2 cycles of precipitation and frequent rainstorms were 2-7 years, which coincided with the ENSO inter-annual variability of the signal. The NINO index, regardless of the frequency of winter or annual heavy rain or drought disasters, showed negative correlation, while the SOI showed positive correlation. The coefficient of correlation between the NINO index and winter and annual drought was close to -0.3.The frequency of drought and extreme temperature events increased significantly with increase in temperature. Thus, climate change and global warming were found to have some connection to one manifestations of the regional response to global climate change. The ENSO index, regardless of the frequency of seasonal or annual heavy rain and drought disasters, showed negative correlation, while the SOI showed positive correlation. The correlation coefficient between the ENSO index, and autumn and winter and annual drought, was close to -0.3. The NINO index showed correlation with heavy rain, and the SOI showed significant negative correlation with heavy rain and obvious correlation with drought. Therefore, it can be concluded that regional heavy rain might be affected by ENSO, whereas the SOI is one of the more important factors determining the occurrence of drought. The influence of SST on drought and floods is actually transmitted via the response of atmospheric circulation. Various statistical, diagnostic, and numerical experiments have proven that SST thermal anomalies influence mid- and high-latitude atmospheric circulation anomalies, which is important evidence supporting the above conclusion. It has been demonstrated that an important link exists between the occurrence of heavy rain and drought disasters in the Lancang River Basin and ENSO.