This study investigated the effect of arctic oscillation by analyzing the cross-correlation characteristics between the arctic oscillation index (AOI) and the number of typhoons occurred in the North Pacific, the number of typhoons affected on the Korean Peninsula, total rainfall depth and number of...
This study investigated the effect of arctic oscillation by analyzing the cross-correlation characteristics between the arctic oscillation index (AOI) and the number of typhoons occurred in the North Pacific, the number of typhoons affected on the Korean Peninsula, total rainfall depth and number of rainy days during the monsoon season in Korea. Then, study evaluates the effect of mother wavelet in the wavelet analysis of white noise, white-noise-added sine function, short-memory arctic oscillation index (AOI) and long-memory southern oscillation index (SOI). Finally study performs the cross wavelet analysis with the arctic oscillation index (AOI) and the four climate factors like the number of typhoons occurred in the North Pacific, the number of typhoons affecting the Korean Peninsula, the rainfall amount, and the number of rainy days during the monsoon season in Korea. This study considers a total of four mother wavelets (i.e., Bump, Morlet, Paul, and Mexican Hat) in the evaluation. The data period for this analysis was determined to be from 1961 to 2016 by considering the data available.
Based on this analysis, it was found that the arctic oscillation has a weak but statistically significant effect on the monsoon characteristics of the Korean Peninsula. However, the level of effect was not consistent over the data period but varied significantly periodically.
Summarizing the results of mother wavelet analysis is as follows. First, the Bump mother wavelet is found to have some limitation to represent the unstationary behavior of the periodic components. Its application results are more or less the same sa the spectrum analysis. On the other hand, the Morlet and Paul mother wavelets are found to represent the unstationary behavior of the periodic components. Finally, the application results of the Mexican Hat mother wavelet are found to be too complicated to be used. Additionally, it is also found that the application result of Paul mother wavelet can be inconsistent for some specific time series. As a result, the Morlet mother wavelet seems to be the most stable one for general applications, which is also assured by the recent trend that the Morlet mother wavelt is most frequently used in the wavelet analysis research.
Then, summarizing the results of Morlet wavelet analysis is as follows. First, the winter AOI is found to have a greater influence on the climate of Korea than the other seasonal AOIs. The winter AOI and both monsoon characteristics, i.e., the total rainfall depth and the rainy days, shows a strong correlation for their long-term-period components in
the 1970s, but the short-term-period ones after the 1990s. On the other hand, in recent years, somewhat different trend is observed that the total rainfall and the winter AOI shows a strong correlation between the long-term-period components, the rainy days between the short-term-period ones. Second, this study confirms that the typhoon characteristics, rather than the monsoon characteristics, are weakly correlated with the winter AOI. However, the number of typhoons affecting the Korean peninsula showed an obvious correlation pattern changing every ten years from the long-term-period components to the short-term-period ones. As the change of correlation characteristics between AOI and monsoon (or typhoon), however, is non stationary without any obvious periodicity, it may not be used for the forecasting purpose. Therefore, this wavelet analysis has the possibility to get appropriate results about non stationary data.
This study investigated the effect of arctic oscillation by analyzing the cross-correlation characteristics between the arctic oscillation index (AOI) and the number of typhoons occurred in the North Pacific, the number of typhoons affected on the Korean Peninsula, total rainfall depth and number of rainy days during the monsoon season in Korea. Then, study evaluates the effect of mother wavelet in the wavelet analysis of white noise, white-noise-added sine function, short-memory arctic oscillation index (AOI) and long-memory southern oscillation index (SOI). Finally study performs the cross wavelet analysis with the arctic oscillation index (AOI) and the four climate factors like the number of typhoons occurred in the North Pacific, the number of typhoons affecting the Korean Peninsula, the rainfall amount, and the number of rainy days during the monsoon season in Korea. This study considers a total of four mother wavelets (i.e., Bump, Morlet, Paul, and Mexican Hat) in the evaluation. The data period for this analysis was determined to be from 1961 to 2016 by considering the data available.
Based on this analysis, it was found that the arctic oscillation has a weak but statistically significant effect on the monsoon characteristics of the Korean Peninsula. However, the level of effect was not consistent over the data period but varied significantly periodically.
Summarizing the results of mother wavelet analysis is as follows. First, the Bump mother wavelet is found to have some limitation to represent the unstationary behavior of the periodic components. Its application results are more or less the same sa the spectrum analysis. On the other hand, the Morlet and Paul mother wavelets are found to represent the unstationary behavior of the periodic components. Finally, the application results of the Mexican Hat mother wavelet are found to be too complicated to be used. Additionally, it is also found that the application result of Paul mother wavelet can be inconsistent for some specific time series. As a result, the Morlet mother wavelet seems to be the most stable one for general applications, which is also assured by the recent trend that the Morlet mother wavelt is most frequently used in the wavelet analysis research.
Then, summarizing the results of Morlet wavelet analysis is as follows. First, the winter AOI is found to have a greater influence on the climate of Korea than the other seasonal AOIs. The winter AOI and both monsoon characteristics, i.e., the total rainfall depth and the rainy days, shows a strong correlation for their long-term-period components in
the 1970s, but the short-term-period ones after the 1990s. On the other hand, in recent years, somewhat different trend is observed that the total rainfall and the winter AOI shows a strong correlation between the long-term-period components, the rainy days between the short-term-period ones. Second, this study confirms that the typhoon characteristics, rather than the monsoon characteristics, are weakly correlated with the winter AOI. However, the number of typhoons affecting the Korean peninsula showed an obvious correlation pattern changing every ten years from the long-term-period components to the short-term-period ones. As the change of correlation characteristics between AOI and monsoon (or typhoon), however, is non stationary without any obvious periodicity, it may not be used for the forecasting purpose. Therefore, this wavelet analysis has the possibility to get appropriate results about non stationary data.
주제어
#북극진동 웨이블릿 분석
※ AI-Helper는 부적절한 답변을 할 수 있습니다.