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Temporal–spatial diversities of long-range correlation for relative humidity over China

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  • Lin, Guangxing
  • Chen, Xi
  • Fu, Zuntao

Abstract

Long-range correlations of daily relative humidity anomaly records from 191 weather stations over China during 1951–2000 are analyzed by means of fluctuation analysis (FA) and detrended fluctuation analysis (DFA). The information about trends in the relative humidity records can be obtained by comparing the FA curve with DFA curves. The daily relative humidity fluctuations are found to be power-law correlated and their average scaling exponent is higher than that of the temperature fluctuations, indicating that the relative humidity fluctuations take different statistical behavior from other meteorological quantities and there exists a stronger persistence in the relative humidity fluctuations. Furthermore, it is also found that these power-law scaling properties vary from station to station and show both spatial and temporal diversities, which may be explained by a proposed mechanism.

Suggested Citation

  • Lin, Guangxing & Chen, Xi & Fu, Zuntao, 2007. "Temporal–spatial diversities of long-range correlation for relative humidity over China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(2), pages 585-594.
    • Handle: RePEc:eee:phsmap:v:383:y:2007:i:2:p:585-594
    DOI: 10.1016/j.physa.2007.04.059
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    Citations

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    Cited by:

    1. 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.
    2. Mohti, Wahbeeah & Dionísio, Andreia & Vieira, Isabel & Ferreira, Paulo, 2019. "Financial contagion analysis in frontier markets: Evidence from the US subprime and the Eurozone debt crises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1388-1398.
    3. Siqueira, Erinaldo Leite & Stošić, Tatijana & Bejan, Lucian & Stošić, Borko, 2010. "Correlations and cross-correlations in the Brazilian agrarian commodities and stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(14), pages 2739-2743.
    4. 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.
    5. Wang, Lihong, 2009. "Memory parameter estimation for long range dependent random fields," Statistics & Probability Letters, Elsevier, vol. 79(21), pages 2297-2306, November.
    6. 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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