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Visibility graph approach to the analysis of ocean tidal records

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  • Telesca, Luciano
  • Lovallo, Michele
  • Pierini, Jorge O.

Abstract

By using the recent method of the visibility graph, three time series of oceanic tide level in central Argentina were investigated. The degree distributions show a rich structure; in particular the maximum is due to the main periodic oscillations at 24hours and 12hours and higher harmonics. The degree distributions of the residuals (obtained removing from the original signals the cyclic components) suggest that the local effects, linked with the particular coastal conditions of the sites, are discernible for the degree k<20, while the global effects, linked with linked with the more general and common atmospheric forcing and ocean current conditions, are visible for k>100. Although a relationship between the spectral exponent α and the exponent of the degree distribution γ of tidal signals can be recognized, this cannot be simply stated due to the very rich and complex structure of time dynamics of tides. The present study, even if still preliminary, show the importance of the visibility graph method in investigating the complex time dynamics of observational and experimental signals.

Suggested Citation

  • Telesca, Luciano & Lovallo, Michele & Pierini, Jorge O., 2012. "Visibility graph approach to the analysis of ocean tidal records," Chaos, Solitons & Fractals, Elsevier, vol. 45(9), pages 1086-1091.
    • Handle: RePEc:eee:chsofr:v:45:y:2012:i:9:p:1086-1091
    DOI: 10.1016/j.chaos.2012.06.003
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    Cited by:

    1. Luciano Telesca & Zbigniew Czechowski, 2024. "Information–Theoretic Analysis of Visibility Graph Properties of Extremes in Time Series Generated by a Nonlinear Langevin Equation," Mathematics, MDPI, vol. 12(20), pages 1-15, October.
    2. Serinaldi, Francesco & Kilsby, Chris G., 2016. "Irreversibility and complex network behavior of stream flow fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 585-600.
    3. Zhang, Yali & Wang, Jun, 2017. "Nonlinear complexity of random visibility graph and Lempel-Ziv on multitype range-intensity interacting financial dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 741-756.
    4. Zhang, Bo & Wang, Jun & Fang, Wen, 2015. "Volatility behavior of visibility graph EMD financial time series from Ising interacting system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 301-314.
    5. Telesca, Luciano & Lovallo, Michele & Ramirez-Rojas, Alejandro & Flores-Marquez, Leticia, 2013. "Investigating the time dynamics of seismicity by using the visibility graph approach: Application to seismicity of Mexican subduction zone," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6571-6577.
    6. Shengli, Liu & Yongtu, Liang, 2019. "Exploring the temporal structure of time series data for hazardous liquid pipeline incidents based on complex network theory," International Journal of Critical Infrastructure Protection, Elsevier, vol. 26(C).
    7. Liu, Jin-Long & Yu, Zu-Guo & Zhou, Yu, 2024. "A cross horizontal visibility graph algorithm to explore associations between two time series," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    8. Gao, Meng & Ge, Ruijun, 2024. "Mapping time series into signed networks via horizontal visibility graph," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).

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