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Long-term memory dynamics of continental and oceanic monthly temperatures in the recent 125 years

Author

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  • Alvarez-Ramirez, Jose
  • Alvarez, Jesus
  • Dagdug, Leonardo
  • Rodriguez, Eduardo
  • Carlos Echeverria, Juan

Abstract

For both Northern and Southern hemispheres, the long-term memory dynamics for continent and ocean temperature records in the recent 125 years is studied in this paper. It is found that the records exhibit long-range memory and multifractality characteristics where large temperature anomalies display a more random behavior than the overall time series. A 256-month moving window was used to compute the time evolution of the fractal scaling exponent, giving the following results: (i) Ocean temperatures are more persistent than land temperatures, a result already reported in recent publications, (ii) All records show multifractality features, reflecting the nonlinear behavior of the temperature dynamics. Continent temperatures present sharper multifractal spectra than ocean temperatures, (iii) The persistency, as revealed by the scaling exponent, for ocean temperatures displays a cyclic behavior around a nearly constant average value of 22 years, (iv) The persistency for the Northern Hemisphere land temperature is also cyclical but with an increasing trend, and (v) The time at which the Northern Hemisphere continent temperature persistency will converge into the Northern Hemisphere ocean behavior was estimated with linear and exponential extrapolation functions, showing hitting dates around 2050±20 A.D. Potential implications of these results concerning the nature of climate change are also discussed.

Suggested Citation

  • Alvarez-Ramirez, Jose & Alvarez, Jesus & Dagdug, Leonardo & Rodriguez, Eduardo & Carlos Echeverria, Juan, 2008. "Long-term memory dynamics of continental and oceanic monthly temperatures in the recent 125 years," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(14), pages 3629-3640.
  • Handle: RePEc:eee:phsmap:v:387:y:2008:i:14:p:3629-3640
    DOI: 10.1016/j.physa.2008.02.051
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    Citations

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    Cited by:

    1. Charakopoulos, A.K. & Katsouli, G.A. & Karakasidis, T.E., 2018. "Dynamics and causalities of atmospheric and oceanic data identified by complex networks and Granger causality analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 436-453.
    2. Hernandez-Martinez, Eliseo & Velasco-Hernandez, Jorge X. & Perez-Muñoz, Teresa & Alvarez-Ramirez, Jose, 2013. "A DFA approach in well-logs for the identification of facies associations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 6015-6024.
    3. Tsekouras, Georgios & Koutsoyiannis, Demetris, 2014. "Stochastic analysis and simulation of hydrometeorological processes associated with wind and solar energy," Renewable Energy, Elsevier, vol. 63(C), pages 624-633.
    4. Erjia Ge & Yee Leung, 2013. "Detection of crossover time scales in multifractal detrended fluctuation analysis," Journal of Geographical Systems, Springer, vol. 15(2), pages 115-147, April.

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