基于 Copula 函数的宜昌水文干旱特征分析

基于宜昌站1951～2014年的实测月径流资料,选用标准化径流指数(SSI),运用游程理论识别干旱,应用Copula函数构建干旱特征变量间的多维联合概率分布,进而对宜昌站的干旱特征进行分析。结果表明:(1)宜昌在1950～1980年代,干旱次数呈现交替变化,自1990年代以来,特别是进入21世纪后,宜昌干旱事件增多、持续时间增大、干旱烈度和峰值增高,干旱情势有加重的趋势;(2)Copula函数可很好地描述宜昌地区干旱特征变量间的联合概率分布,多变量的联合重现期和同现重现期可分别作为实际单变量重现期区间估计的下限和上限,用以评估宜昌地区不同干旱变量值所代表的干旱事件发生的频率;(3)宜昌站近60年出现两次严重的干旱事件,一次发生于1978年9月～1979年7月,该事件的干旱历时和干旱烈度均达到了历史极值,这两个变量的联合重现期约为32a,同现重现期约为110a;该事件的干旱历时、干旱烈度和烈度峰值三个变量的联合重现期为9a,同现重现期约为115a。另一次干旱事件发生于2006年6月～12月,其烈度峰值达到了历史极值,其重现期接近90a;该次事件的干旱历时、干旱烈度和烈度峰值三者的联合重现期只有13a左右,同现重现期则超过了231a。     

A New Index About the Walker Circulation

The Walker circulation (WC) has always been an important issue in atmospheric science research due to the association between the WC and tropical Pacific sea surface temperature (SST), and between the WC and ENSO events. In this paper, a new index-Omega index (OMGI) - is constructed for WC characterization based on the NCEP / NCAR reanalysis data of monthly mean vertical velocity in recent 70 years (1948-2017). Results show that the OMGI can accurately depict the variation characteristics of WC on seasonal, annual and decadal time-scales. There is a significant inverse correlation between the OMGI and equatorial eastern and central Pacific SST. Meanwhile, the peak of the OMGI appears ahead of the ENSO peak, and therefore is able to reflect the SST in the equatorial Pacific. Especially, in 35 ENSO events, the peak of the OMGI appears earlier than Ni?o 3.4 index for 19 times with 2.6 months ahead on average. In 16 El Ni?o events, the peak of the OMGI occurs ahead of the El Ni?o for 9 times with 4 months ahead on average. In 19 La Ni?a events, the OMGI peak arises 10 times earlier than the La Ni?a peak, with an average of 1.4 months ahead. OMGI shows obvious leading effect and stability over ENSO events with different strengths and types of single peak and multi peaks: the peak of the OMGI keeps about 2-3 months ahead of the ENSO. Compared with other WC indexes such as UWI and SPLI, OMGI has some advantages in the ability to describe WC changes and present the probability and thetime of prediction of ENSO event peaks.