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Long term persistence in the atmosphere: global laws and tests of climate models

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  • Bunde, Armin
  • Havlin, Shlomo
  • Koscielny-Bunde, Eva
  • Schellnhuber, Hans-Joachim

Abstract

The persistence of short term weather states is a well known phenomenon: A warm day is more likely to be followed by a warm day than by a cold one and vice versa. Using advanced methods from statistical physics that are able to distinguish between trends and persistence we have shown recently that this rule may well extend to months, years and decades, and on these scales the decay of the persistence seems to follow a universal power law. Here we review these studies and discuss, how the law can be used as an (uncomfortable) test bed for the state-of-the-art climate models. It turns out that the models considered display wide performance differences and actually fail to reproduce the universal power law behavior of the persistence. It seems that the models tend to underestimate persistence while overestimating trends, and this fact may imply that the models exaggerate the expected global warming of the atmosphere.

Suggested Citation

  • Bunde, Armin & Havlin, Shlomo & Koscielny-Bunde, Eva & Schellnhuber, Hans-Joachim, 2001. "Long term persistence in the atmosphere: global laws and tests of climate models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 302(1), pages 255-267.
    • Handle: RePEc:eee:phsmap:v:302:y:2001:i:1:p:255-267
    DOI: 10.1016/S0378-4371(01)00469-1
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    Cited by:

    1. Luis A. Gil-Alana & Laura Sauci, 2019. "Temperatures across Europe: evidence of time trends," Climatic Change, Springer, vol. 157(3), pages 355-364, December.
    2. Fernández, Isabel & Hernández, Carmen N. & Pacheco, José M., 2003. "Is the North Atlantic Oscillation just a pink noise?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 323(C), pages 705-714.
    3. 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.
    4. Fernández, Isabel & Pacheco, José M. & Quintana, María P., 2010. "Pinkness of the North Atlantic Oscillation signal revisited," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5801-5807.
    5. Mante, Claude, 2007. "Application of resampling and linear spline methods to spectral and dispersional analyses of long-memory processes," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4308-4323, May.
    6. Koçak, Kasım, 2009. "Examination of persistence properties of wind speed records using detrended fluctuation analysis," Energy, Elsevier, vol. 34(11), pages 1980-1985.

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