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A universal model to characterize different multi-fractal behaviors of daily temperature records over China

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  • Lin, Guangxing
  • Fu, Zuntao

Abstract

The multi-fractal properties of surface air temperature over China are studied through Multi-fractal detrended fluctuation analysis (MF-DFA). It is shown that there indeed exists the multi-fractal phenomenon in daily surface air temperature time series, reflecting a great deal of fluctuations at various time scales. The multi-fractal properties can be characterized very well by a universal generalized binomial multiplicative cascade model with only two parameters a and b. For different stations, the width of singularity spectrum f(α) is different, indicating different strengths of temperature multi-fractal behavior from station to station.

Suggested Citation

  • Lin, Guangxing & Fu, Zuntao, 2008. "A universal model to characterize different multi-fractal behaviors of daily temperature records over China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 573-579.
    • Handle: RePEc:eee:phsmap:v:387:y:2008:i:2:p:573-579
    DOI: 10.1016/j.physa.2007.10.011
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    1. Telesca, Luciano & Lapenna, Vincenzo & Macchiato, Maria, 2005. "Multifractal fluctuations in seismic interspike series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 354(C), pages 629-640.
    2. Vitanov, Nikolay K. & Yankulova, Elka D., 2006. "Multifractal analysis of the long-range correlations in the cardiac dynamics of Drosophila melanogaster," Chaos, Solitons & Fractals, Elsevier, vol. 28(3), pages 768-775.
    3. Stanley, H.E. & Amaral, L.A.N. & Goldberger, A.L. & Havlin, S. & Ivanov, P.Ch. & Peng, C.-K., 1999. "Statistical physics and physiology: Monofractal and multifractal approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 270(1), pages 309-324.
    4. Kantelhardt, Jan W. & Zschiegner, Stephan A. & Koscielny-Bunde, Eva & Havlin, Shlomo & Bunde, Armin & Stanley, H.Eugene, 2002. "Multifractal detrended fluctuation analysis of nonstationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 87-114.
    5. Bunde, Armin & Havlin, Shlomo, 2002. "Power-law persistence in the atmosphere and in the oceans," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 314(1), pages 15-24.
    6. Kantelhardt, Jan W. & Rybski, Diego & Zschiegner, Stephan A. & Braun, Peter & Koscielny-Bunde, Eva & Livina, Valerie & Havlin, Shlomo & Bunde, Armin, 2003. "Multifractality of river runoff and precipitation: comparison of fluctuation analysis and wavelet methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 330(1), pages 240-245.
    7. Kaushik Matia & Yosef Ashkenazy & H. Eugene Stanley, 2003. "Multifractal Properties of Price Fluctuations of Stocks and Commodities," Papers cond-mat/0308012, arXiv.org.
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    Citations

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    Cited by:

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    2. Jiang, Lei & Zhang, Jiping & Liu, Xinwei & Li, Fei, 2016. "Multi-fractal scaling comparison of the Air Temperature and the Surface Temperature over China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 783-792.
    3. Wang, Jian & Huang, Menghao & Wu, Xinpei & Kim, Junseok, 2023. "A local fitting based multifractal detrend fluctuation analysis method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).
    4. Zunino, Luciano & Figliola, Alejandra & Tabak, Benjamin M. & Pérez, Darío G. & Garavaglia, Mario & Rosso, Osvaldo A., 2009. "Multifractal structure in Latin-American market indices," Chaos, Solitons & Fractals, Elsevier, vol. 41(5), pages 2331-2340.
    5. Zunino, L. & Tabak, B.M. & Figliola, A. & Pérez, D.G. & Garavaglia, M. & Rosso, O.A., 2008. "A multifractal approach for stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(26), pages 6558-6566.
    6. Jiang, Lei, 2018. "Mean wind speed persistence over China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 211-217.
    7. Gong, Huanhuan & Fu, Zuntao, 2022. "Beyond linear correlation: Strong nonlinear structures in diurnal temperature range variability over southern China," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    8. Lu, Feiyu & Yuan, Naiming & Fu, Zuntao & Mao, Jiangyu, 2012. "Universal scaling behaviors of meteorological variables’ volatility and relations with original records," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4953-4962.

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