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Study of Saudi Arabian climatic conditions using Hurst exponent and climatic predictability index

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  • Rehman, Shafiqur

Abstract

This paper utilizes Hurst exponent to study the persistency of meteorological parameters individually and dependency of rainfall/precipitation on pressure and temperature using climate predictability index. For the purpose, daily averages of surface pressure and temperature and daily total rainfall data for a period of 7 years for three locations and 14 years for seven locations has been utilized. The Hurst exponents (H) for above mentioned meteorological parameters were calculated using rescaled range analysis (R/S) and absolute moments methods. These H values were used to calculate the fractal dimension D for pressure, temperature and rainfall data. Finally, these D’s were used to calculate the climate predictability index PIC in terms of pressure predictability index (PIP), temperature predictability index (PIT) and rainfall predictability index (PIR). The Hurst exponent analysis showed that H values for rainfall, relative humidity and wind speed time series data for all the stations were >0.5 which is indicative of persistence behavior of the parameters on the previous values while for pressure and temperature H values were <0.5 means anti-persistence behavior. The climate predictability index showed that in most of the cases the rainfall was dependent on both pressure and temperature predictability indices. In some cases it was more dependent on 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, 2009. "Study of Saudi Arabian climatic conditions using Hurst exponent and climatic predictability index," Chaos, Solitons & Fractals, Elsevier, vol. 39(2), pages 499-509.
    • Handle: RePEc:eee:chsofr:v:39:y:2009:i:2:p:499-509
    DOI: 10.1016/j.chaos.2007.01.079
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    References listed on IDEAS

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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.
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    2. Zhang, Baoqing & Wu, Pute & Zhao, Xining & Wang, Yubao & Wang, Jiawen & Shi, Yinguang, 2012. "Drought variation trends in different subregions of the Chinese Loess Plateau over the past four decades," Agricultural Water Management, Elsevier, vol. 115(C), pages 167-177.
    3. Pakrashi, Vikram & Kelly, Joe & Harkin, Julie & Farrell, Aidan, 2013. "Hurst exponent footprints from activities on a large structural system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1803-1817.
    4. Kristoufek, Ladislav, 2012. "How are rescaled range analyses affected by different memory and distributional properties? A Monte Carlo study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(17), pages 4252-4260.
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    6. Mulligan, Robert F., 2014. "Multifractality of sectoral price indices: Hurst signature analysis of Cantillon effects in disequilibrium factor markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 403(C), pages 252-264.

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