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High frequency intrinsic modes in El Niño/Southern Oscillation Index

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  • Petroni, Filippo
  • Ausloos, Marcel

Abstract

Recent daily data of the Southern Oscillation Index have been analyzed. The power spectrum indicates major intrinsic geophysical short periods. We find interesting “high frequency” oscillations at 24, 27, 37, 76, 100 and 365 days. In particular the 24 days peaks may correspond to the Branstator–Kushnir wave, the 27 days may be due to the moon effect rotation, the 37 days peaks are most probably related to the Madden and Julian Oscillation. It is not yet clear the explanations for the 76 days which may be associated with interseasonal oscillation in the tropical atmosphere; the 100 days could be resulting from a mere beat between the 37 and 27 periods, or the 76 and 365 days. We use these periods to reconstruct the signal and to produce a forecast for the next 9 months, at the time of writing. After cleansing the signal of those periodicities a detrended fluctuation analysis is performed to reveal the nature of the stochastic structures in the signal and whether specific correlation can be found. We study the evolution of the distribution of first return times, in particular between extreme events. A markedly significant difference from the expected distribution for uncorrelated events is found.

Suggested Citation

  • Petroni, Filippo & Ausloos, Marcel, 2008. "High frequency intrinsic modes in El Niño/Southern Oscillation Index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5246-5254.
    • Handle: RePEc:eee:phsmap:v:387:y:2008:i:21:p:5246-5254
    DOI: 10.1016/j.physa.2008.05.021
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    References listed on IDEAS

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    1. Ausloos, M. & Petroni, F., 2007. "Tsallis non-extensive statistical mechanics of El Niño southern oscillation index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 721-736.
    2. Vandewalle, N. & Ausloos, M., 1997. "Coherent and random sequences in financial fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 246(3), pages 454-459.
    3. Ausloos, M, 2002. "Empirical Analysis of Time Series," MPRA Paper 28700, University Library of Munich, Germany.
    4. Ivanova, K & Ausloos, M, 1999. "Application of the detrended fluctuation analysis (DFA) method for describing cloud breaking," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 274(1), pages 349-354.
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