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Statistical analyses of sea state conditions in South China Sea

Abstract

The statistical characterization of sea conditions in the South China Sea (SCS) was investigated by analyzing a 30-year (1976–2005) numerically simulated daily wave height and wind speed data. The monthly variation of these parameters shows that wave height and wind speed have minimum values of 0.54 m and 4.15 m s−1, respectively in May and peak values of 2.04 m and 8.12 m s−1, respectively in December. Statistical analysis of the daily wave height and wind speed and the subsequent characterization of the annual, seasonal and monthly mean sea state based on these parameters were also done. Results showed that, in general, the slight sea state prevails in the SCS and has nearly the highest occurrence in all seasons and months. The moderate sea condition prevails in the winter months of December and January while the smooth (wavelets) sea state prevails in May. Furthermore, spatial variation of sea states showed that calm and smooth sea conditions have high occurrences (25%–80%) in the southern SCS. The slight sea condition shows the largest occurrence (25%–55%) over most parts of the SCS. High occurrences (8%–17%) of the rough and very rough seas distribute over some regions in the central SCS. Sea states from high to phenomenal conditions show rare occurrence (<12%) in the northern SCS. The calm (glassy) sea condition shows no occurrence in the SCS.

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References

  • Bitner-Gregersen, E., 2015. Joint met-ocean description for design and operations of marine structures. Applied Ocean Research, 51: 279–292.

    Article  Google Scholar 

  • Callahan, P. S., Morris, C. S., and Hsiao, S. V., 1994. Comparison of TOPEX/POSEIDON and significant wave height distributions to Geosat. Journal of Geophysical Research, 99 (C12): 25015–25024.

    Article  Google Scholar 

  • Dobson, E., Monaldo, F., and Goldhirsh, J., 1987. Validation of Geosat altimeter-derived wind speeds and significant wave heights using buoy data. Journal of Geophysical Research, 92 (C10): 10719–10731.

    Article  Google Scholar 

  • Ewans, K. C., 2015. A wavelet-based test for swell stationarity. Applied Ocean Research, 51: 255–267.

    Article  Google Scholar 

  • Forristall, G. Z., 1978. On the statistical distribution of wave heights in a storm. Journal of Geophysical Research Atmospheres, 83 (C5): 2553–2558.

    Article  Google Scholar 

  • Fu, L. L., Christensen, E. J., Yamaone Jr., C. A., Lefebvre, M., Menard, Y., Dorrer, M., and Escudier, P., 1994. TOPEX/POSEIDON mission overview. Journal of Geophysical Research, 99 (C12): 24369–24381.

    Article  Google Scholar 

  • Jahns, H. O., and Wheeler, J. D., 1973. Long-term wave probabilities based on hindcasting of severe storms. Journal of Petoleum Technology, 25 (4): 473–486.

    Article  Google Scholar 

  • Lucas, C., and Guedes, S. C., 2015a. On the spectral modelling of swell spectra. Ocean Engineering, 108: 749–759.

    Article  Google Scholar 

  • Lucas, C., and Guedes, S. C., 2015b. Bivariate distributions of significant wave height and mean wave period of combined sea states. Ocean Engineering, 106: 341–353.

    Article  Google Scholar 

  • Lucas, C., Muraleedharan, G., and Guedes, S. C., 2014. Outliers identification in a wave hindcast dataset used for regional frequency analysis. In: Maritime Technology and Engineering. Guedes, S. C., and Santos, T. A., eds., Taylor and Francis Group, London, 1317–1327.

    Google Scholar 

  • Rodriguez, G., and Soares, C. G., 2000. Wave period distribution in mixed sea states. Proceedings of the 19th International Conference on Offshore Mechanics and Arctic Engineering. ASME, New York Paper, OMAE/S&R-6132.

    Google Scholar 

  • Santoro, A., Guedes, S. C., and Arena, F., 2013. Analysis of experimental results on the space-time evolution of wave groups in crossing seas. In: Proceedings of the 32nd International Conference on Ocean, Offshore and Arctic Engineering. Nantes, France, Paper OMAE2013-11533.

    Google Scholar 

  • Schneggenburger, C., Gunther, H., and Rosenthal, W., 2000. Spectral wave modeling with non-linear dissipation: Validation and applications in a coastal tidal environment. Coastal Engineering, 41 (1–3): 201–235.

    Article  Google Scholar 

  • Silva, D., Rusu, E., and Guedes, S. C., 2013. Evaluation of various technologies for wave energy conversion in the Portuguese nearshore. Energies, 6: 1344–1364.

    Article  Google Scholar 

  • Soares, C. S., and Guedes, S. C., 2007. Comparison of bivariate models of distributions of significant wave height and wave period. In: Proceedings of the 26th International Conference on Offshore Mechanics and Arctic Engineering (OMAE 2007). ASME, NY, USA, paper OMAE 2007-29740.

    Google Scholar 

  • Sundar, V., and Ananth, P. N., 1988. Wind climate for Madras harbor, India. Journal of Wind Engineering & Industrial Aerodynamics, 31 (2): 323–333.

    Article  Google Scholar 

  • Thompson, E. F., 1980. Energy Spectra in Shallow U.S. Coastal Waters. Tech. Paper 80-2, U.S. Army, Corps of Engineers, Coastal Engineering Research Centre.

    Google Scholar 

  • Titov, L. F., 1969. Wind-Driven Waves. Israel Program for Scientific Translations, Jerusalem.

    Google Scholar 

  • Tolman, H. L., 2009. User Manual and System Documentation of WAVEWATCH-III Version 3.14. NOAA/NWS/NCEP/MMAB Technical Note, Washington, 1–194.

    Google Scholar 

Download references

Acknowledgements

This work is financially supported by the National Natural Science Foundation of China (NSFC) (41276015), the Public Science and Technology Research Funds Projects of Ocean (201505007), the Joint Project for the National Oceanographic Center by the NSFC and Shandong Government (U1406401), and the Doctoral Fund of Ministry of Education of China (20120132110004).

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Correspondence to Xiaopei Lin.

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Osinowo, A., Lin, X., Zhao, D. et al. Statistical analyses of sea state conditions in South China Sea. J. Ocean Univ. China 16, 357–369 (2017). https://doi.org/10.1007/s11802-017-3188-9

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  • DOI: https://doi.org/10.1007/s11802-017-3188-9

Key words

  • wave height
  • wind speed
  • sea state
  • occurrence