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Different scaling behaviors in daily temperature records over China

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  • Yuan, Naiming
  • Fu, Zuntao
  • Mao, Jiangyu

Abstract

Long-range correlations of five kinds of daily temperature records (i.e. daily average temperature records, daily maximum temperature records, daily minimum temperature records, diurnal temperature range and the sum of daily maximum and minimum temperature records) from 164 weather stations over China during 1951–2004 are analyzed by means of detrended fluctuation analysis (DFA). These five kinds of fluctuation series are found to be power-law correlated with scaling exponents larger than 0.5. Local changes of scaling exponents are examined and the spatial distributions of these different kinds of temperature records are similar except the diurnal temperature range (DTR for short) records. Furthermore, the differences of the scaling behavior among diurnal temperature records and other kinds of temperature records are discussed.

Suggested Citation

  • Yuan, Naiming & Fu, Zuntao & Mao, Jiangyu, 2010. "Different scaling behaviors in daily temperature records over China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(19), pages 4087-4095.
    • Handle: RePEc:eee:phsmap:v:389:y:2010:i:19:p:4087-4095
    DOI: 10.1016/j.physa.2010.05.026
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    Cited by:

    1. Garg, Teevrat & Gibson, Matthew & Sun, Fanglin, 2020. "Extreme temperatures and time use in China," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 309-324.
    2. Fu, Shu & Huang, Yu & Feng, Tao & Nian, Da & Fu, Zuntao, 2019. "Regional contrasting DTR’s predictability over China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 282-292.
    3. Zhang, Boer & Xie, Fenghua & Fu, Zunhai & Fu, Zuntao, 2019. "Comparative study of multiple measures on temporal irreversibility of daily air temperature anomaly variations over China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1387-1399.
    4. 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.
    5. Jiang, Lei, 2018. "Mean wind speed persistence over China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 211-217.
    6. 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.
    7. Yuan, Naiming & Fu, Zuntao, 2014. "Different spatial cross-correlation patterns of temperature records over China: A DCCA study on different time scales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 400(C), pages 71-79.
    8. 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).
    9. 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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