Wavelet Analysis of Nonstationary and Chaotic Time Series with an Application to the Climate Change Problem

2000 ◽  
pp. 653-677 ◽  
Author(s):  
D. M. Sonechkin ◽  
N. M. Datsenko
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Wavelet Analysis ◽  
Chaotic Time Series ◽  
Change Problem

scholarly journals Variability of Rainfall in the Semi-Arid Region of Brazil

10.29007/srn9 ◽  
2018 ◽  
Author(s):  
Celso Santos ◽  
Carlos Galvão ◽  
Reginaldo Brasil Neto ◽  
Isabel Meneses
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Wavelet Analysis ◽  
Arid Region ◽  
Rainfall Regime ◽  
Space And Time ◽  
Semi Arid Region ◽  
Semi Arid

The Brazilian semi-arid region presents a highly variable rainfall regime in space and time. Although the mechanisms of rainfall have been well described and numerically modelled, reliable forecasts for more than six months in advance cannot be produced yet, as well as projections of climate change in the long term. This paper contributes to the understanding of the variability examining a more than 100-year time series of a rainfall gauge in this region, using three techniques: wavelet analysis, Mann- Kendall and Sen tests. The techniques allow the description of the patterns of variability of rainfall and suggest that there is not still a clear evidence of climate change.

Characteristics Identification of Runoff and Sediment Flux Based on Wavelet Analysis Approach in Lower Yellow River

2014 ◽  
Vol 700 ◽  
pp. 506-510
Author(s):  
Yu Zhi Shi ◽  
Ming Yuan Fan ◽  
Yu Yan Zhang ◽  
Hai Jiao Liu ◽  
Xiao Feng Yang
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Wavelet Analysis ◽  
Yellow River ◽  
Sediment Flux ◽  
The Yellow River ◽  
Lower Yellow River ◽  
Multi Scale ◽  
Flood Season ◽  
Water And Sediment

Due to the influences of climate change and human activities, the water and sediment flux of the Yellow River are certainly changing. This paper selects monthly time series of runoff and sediment flux from 1950 to 2009 for study at Lijin station, in lower Yellow River. A widely used identification method, wavelet analysis, is applied for recognizing changing point and cycle of the runoff and sediment respectively in multi-scale of annual, flood season and non-flood season. The results indicate that there are two significant changing points in 1985, 2002 year, and cycle recognized results are different in multi-scale as well as with different hydrology factors.

scholarly journals THE SPECTRUM OF CHAOTIC TIME SERIES (II): WAVELET ANALYSIS

2011 ◽  
Vol 21 (05) ◽  
pp. 1457-1467 ◽  
Author(s):  
GOONG CHEN ◽  
SZE-BI HSU ◽  
YU HUANG ◽  
MARCO A. ROQUE-SOL
Keyword(s):  
Time Series ◽  
Wavelet Analysis ◽  
Fourier Analysis ◽  
Multiresolution Analysis ◽  
Exponential Growth ◽  
Sufficient Conditions ◽  
Chaotic Time Series ◽  
Wavelet Coefficients ◽  
Necessary And Sufficient ◽  
Number Of Iterations

This paper is a continuation of Part I where the authors treated the Fourier analysis of chaotic time series generated by a chaotic interval map. Here, we perform multiresolution analysis by using wavelet coefficients and characterize some necessary and sufficient conditions for the occurrence of chaos by the exponential growth with respect to the number of iterations n of certain sums of the wavelet coefficients.

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