| Budget Amount *help |
¥3,100,000 (Direct Cost: ¥3,100,000)
Fiscal Year 2000: ¥700,000 (Direct Cost: ¥700,000)
Fiscal Year 1999: ¥700,000 (Direct Cost: ¥700,000)
Fiscal Year 1998: ¥1,700,000 (Direct Cost: ¥1,700,000)
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| Research Abstract |
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.
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