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A study of Saudi climatic parameters using climatic predictability indices

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  • Rehman, Shafiqur
  • El-Gebeily, Mohamed

Abstract

In this paper, the persistency of individual meteorological parameters and the dependency of precipitation on barometric pressure and temperature is studied using climate predictability index. For the accomplishment of the set objective, daily average values of barometric pressure, temperature and total precipitation data for a period of 17 years from eleven locations was used. The Hurst exponents (H) for each of these parameters were calculated using wavelet and rescaled range analysis (R/S) methods. The Hurst exponent was used in turn to calculate the fractal dimension D for corresponding parameter. Finally, these fractal dimensions were used to calculate the climate predictability index PIC in-terms of the barometric pressure predictability index (PIP), temperature predictability index (PIT) and precipitation predictability index (PIR). The calculated Hurst exponents using wavelet methods were all less than 0.5 for all stations which is indicative of an anti-persistence behavior of the parameters in time. The same values calculated using the R/S method was less than 0.5 for barometric pressure and temperature but greater than 0.5 for precipitation data. The climate predictability index showed that in most of the cases the precipitation was dependent on both barometric pressure and temperature predictability indices. In some cases it was more dependent on the barometric pressure index than the temperature and in some cases otherwise. In Saudi Arabia there is no prevalent or established rainy season and the present analysis could not result into concrete results. It is therefore recommended to analyze the data by breaking the entire data set into seasons and further into different years.

Suggested Citation

  • Rehman, Shafiqur & El-Gebeily, Mohamed, 2009. "A study of Saudi climatic parameters using climatic predictability indices," Chaos, Solitons & Fractals, Elsevier, vol. 41(3), pages 1055-1069.
    • Handle: RePEc:eee:chsofr:v:41:y:2009:i:3:p:1055-1069
    DOI: 10.1016/j.chaos.2008.04.032
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    1. Carbone, A. & Castelli, G. & Stanley, H.E., 2004. "Time-dependent Hurst exponent in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 267-271.
    2. Pavlov, A.N. & Ziganshin, A.R. & Klimova, O.A., 2005. "Multifractal characterization of blood pressure dynamics: stress-induced phenomena," Chaos, Solitons & Fractals, Elsevier, vol. 24(1), pages 57-63.
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    1. Kalamaras, N. & Philippopoulos, K. & Deligiorgi, D. & Tzanis, C.G. & Karvounis, G., 2017. "Multifractal scaling properties of daily air temperature time series," Chaos, Solitons & Fractals, Elsevier, vol. 98(C), pages 38-43.

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