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Fractal characteristics in wind speed time series (WSTS) observed at Nalohou (Northern Benin)

Author Affiliations

  • 1Laboratory of Physics of Radiation (LPR), Abomey-Calavi University, BP: 526 UAC, Bénin
  • 2International Chair in Physics Mathematics and Applications (CIPMA-Chair Unesco), Abomey-Calavi University, BP: 526 UAC, Bénin
  • 3Laboratory of Physics of Radiation (LPR), Abomey-Calavi University, BP: 526 UAC, Bénin and Institute of Mathematics and Physical Science (IMSP), Abomey-Calavi University, BP: 526 UAC, Bénin
  • 4Laboratory of Applied Hydrology (LHA), Abomey-Calavi University, BP: 526 UAC, Bénin
  • 5Laboratory of Physics of Radiation (LPR), Abomey-Calavi University, BP: 526 UAC, Bénin
  • 6Laboratory of Applied Hydrology (LHA), Abomey-Calavi University, BP: 526 UAC, Bénin

Res. J. Physical Sci., Volume 7, Issue (1), Pages 1-7, January,4 (2019)

Abstract

Five-years series of thirty minutes average wind speed obtained from AMMA-CATCH stations at Nalohou (Northern Benin), have been analyzed using fractal approach to determine the scaling behavior in wind speed. Wind Speed Time Series (WSTS) have been transferred into an appropriate data form: the fractal-Dimension (Df), and the Critical temporal Scale (Cts) are plotted as function of threshold (Th). Two invariance regimes are obtained in the WSTS. The first regime is defined from 30 min to 32h and the second is from 32 h to 43 days. The fractal Dimensions of these regimes are respectively in [0.2, 1] and [0.6, 1]. The critical temporal scale increases with the increased values of the threshold. Thus, the higher wind intensity can be observed necessary with a larger time scale. The fractal Dimension decreases when the threshold wind speed level increases indicating the presence of multifractal characteristics in the WSTS. This result is confirmed by the K(q)-q plots function analysis.

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