In this paper,we displayed one-dimensional climate signals,such as global temperature variation,Southern Oscillation Index and variation of external forcing factors,on a two- dimensional time-scale plane using compact...In this paper,we displayed one-dimensional climate signals,such as global temperature variation,Southern Oscillation Index and variation of external forcing factors,on a two- dimensional time-scale plane using compactly supported wavelet decomposition.Using the lag- correlation analysis method,and interpretative variance analysis method,and phase comparison method to the wavelet analysis result,we not only gained the variation on different scales to the global temperature and El Nino signals,the location of the jump point and intrinsic scale of these series,but also indicated the magnitude,extent and time of the effect of external forcing factors on them.We also put forward reasonable explanation to the main variation of recent 140 years.展开更多
文摘In this paper,we displayed one-dimensional climate signals,such as global temperature variation,Southern Oscillation Index and variation of external forcing factors,on a two- dimensional time-scale plane using compactly supported wavelet decomposition.Using the lag- correlation analysis method,and interpretative variance analysis method,and phase comparison method to the wavelet analysis result,we not only gained the variation on different scales to the global temperature and El Nino signals,the location of the jump point and intrinsic scale of these series,but also indicated the magnitude,extent and time of the effect of external forcing factors on them.We also put forward reasonable explanation to the main variation of recent 140 years.
