scholarly journals Multifractal Detrended Cross-Correlation Analysis of sunspot numbers and river flow fluctuations

2010 ◽  
Vol 389 (21) ◽  
pp. 4942-4957 ◽  
Author(s):  
S. Hajian ◽  
M. Sadegh Movahed
BIBECHANA ◽  
2021 ◽  
Vol 18 (2) ◽  
pp. 105-116
Author(s):  
Babu Ram Tiwari ◽  
Jiyao Xu ◽  
Binod Adhikari ◽  
Narayan Prasad Chapagain

This study has been performed to understand the relationship between sunspot numbers (SSN) with climatology related parameters like temperature and rainfall from 1901 to 2016. The spectral characteristics of sunspot numbers, temperature and rainfall have been observed using continuous wavelet transform. Cross-correlation analyses were also performed to find any relation among temperature, rainfall, and sunspot numbers. The 9–11 year periodicity of sunspot numbers confirmed by wavelet transform in annual scale. The periodicity of high-frequency signals is identified between 4 to 11 years whereas the low frequencies signal is found throughout the periods of observation for temperature. Similarly, it is clear that there is more concentration of power between 8–16 years for rainfall. Cross-correlation analysis shows that the sunspot numbers is highly correlated with rainfall and temperature (correlation coefficient ~ 0.8054). The time lag relationship resulted in the almost simultaneous linear relationship between the temperature, rainfall, and the SSN tendency. The development of convective motions over the subtropics might be affected by the time rate of change of SSN combined with the surface temperature changes of diverse time scales. The convective motions were mostly controlled by the available amount of water vapor and the stability of the atmosphere that had a strong connection with the heat capacity of the concerned region. To produce more authentic findings for policy implications, further comprehensive and appropriate research can be undertaken and implemented in this very important field. BIBECHANA 18 (2) (2021) 105-115


2019 ◽  
Vol 11 (1) ◽  
pp. 01025-1-01025-5 ◽  
Author(s):  
N. A. Borodulya ◽  
◽  
R. O. Rezaev ◽  
S. G. Chistyakov ◽  
E. I. Smirnova ◽  
...  

Sensors ◽  
2018 ◽  
Vol 18 (5) ◽  
pp. 1571 ◽  
Author(s):  
Jhonatan Camacho Navarro ◽  
Magda Ruiz ◽  
Rodolfo Villamizar ◽  
Luis Mujica ◽  
Jabid Quiroga

2010 ◽  
Vol 09 (02) ◽  
pp. 203-217 ◽  
Author(s):  
XIAOJUN ZHAO ◽  
PENGJIAN SHANG ◽  
YULEI PANG

This paper reports the statistics of extreme values and positions of extreme events in Chinese stock markets. An extreme event is defined as the event exceeding a certain threshold of normalized logarithmic return. Extreme values follow a piecewise function or a power law distribution determined by the threshold due to a crossover. Extreme positions are studied by return intervals of extreme events, and it is found that return intervals yield a stretched exponential function. According to correlation analysis, extreme values and return intervals are weakly correlated and the correlation decreases with increasing threshold. No long-term cross-correlation exists by using the detrended cross-correlation analysis (DCCA) method. We successfully introduce a modification specific to the correlation and derive the joint cumulative distribution of extreme values and return intervals at 95% confidence level.


2021 ◽  
Vol 27 (S1) ◽  
pp. 1540-1541
Author(s):  
Tristan O'Neill ◽  
B. C. Regan ◽  
Matthew Mecklenburg

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