Impact of Climatic Variation on Water Resources by Southern Oscillation Index Analysis

南方涛动(SO)对气候的影响是广泛的，远远超出了热带太平洋。然而，具体的影响还不是很明显，特别是在中高纬度地区，包括日本。首先，分析了南方涛动指数(SOI)的月时间序列，以检验其混沌特征。采用滑动平均、低通滤波和非线性平滑三种方法来降低噪声，增强混沌特性。无论是降噪的SOI时间序列还是原始的SOI时间序列，都没有发现明显的混沌行为的迹象。虽然SOI时间序列具有较长的周期性，但从动力系统理论的角度来看，SOI时间序列是随机的，而不是混沌的。其次，利用日本福冈市109年的资料，详细研究了SOI月值与正常标准化降水和温度的相关性。对于原始时间序列，SOI与福冈降水/气温之间没有显著的直接相关关系。然而，当使用SOI数据根据其大小分为五组时，获得了统计上显著的相关系数。特别是，对于降水和温度数据，都获得了最高的相关系数，在1%的水平上具有统计学意义。拉尼娜事件越强，降水量越少，4个月后福冈气温越低。此外，还给出了SOI的一般统计特征以及由此得出的数据(即塔希提岛和达尔文的平均海平面气压数据)，以指导使用SOI进行其他分析。这些特征包括大气气压资料的可用性、月气压资料的统计、SO强度的相关性、SOI按震级和按月(1-12月)的频率分析、SOI的持续时间特性的游程分析。

The impacts of Southern Oscillation (SO) on climate are widespread and extend far beyond the tropical Pacific. However, the concrete influence is not so clear, especially in middle to high latitudes, including Japan.First, the monthly time series of the Southern Oscillation Index (SOI) is anarysed to examine its chaotic characteristics. Three schemes, moving average, low-pass filter and nonlinear smoothing, were used to reduce noise and enhance chaotic properties. No significant signs of chaotic behavior were found for either the noise-reduced SOI time series or the raw one. Although it contains long-term periodicity, the SOI time series is considered to be stchastic rather than chaotic from the view point of dynamical systems theory.Second, the cross-correlation between monthly values of on one hand SOI and on the other hand normally standardized precipitation and temperature in Fukuoka, Japan, is investigated in detail using 109 years of data. For the original time series, no significant direct correlation between SOI and precipitation/temperature in Fukuoka is detected. However, statistically significant correlation coefficients are obtained when using SOI data categorized into five groups according to their magnitudes. In particular, the highest correlation coefficients, which are statistically significant at 1 % level, are obtained for both precipitation and temperature data. The stronger the La Nina event, the less precipitation and the lower temperature in Fukuoka 4 months later.Further, general statistical characteristics of SOI and the data from which it is derived (i.e. mean sea level pressure data at Tahiti and Darwin) are presented as guidance when using SOI for other analyses. The characteristics include the availability of the barometric pressurc data, statistics of monthly pressure data, correlation of SO intensity, frequency analysis of SOI by magnitude and by month (January-December), duration properties of SOI by run analysis.