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Statistical analysis on extreme wave height

Author

Listed:
  • N. Teena
  • V. Sanil Kumar
  • K. Sudheesh
  • R. Sajeev

Abstract

The classical extreme value theory based on generalized extreme value (GEV) distribution and generalized Pareto distribution (GPD) is applied to the wave height estimate based on wave hindcast data covering a period of 31 years for a location in the eastern Arabian Sea. Practical concern such as the threshold selection and model validation is discussed. Estimates of wave height having different return periods are compared with estimates obtained from different distributions. On comparing the distributions fitted to the GEV with annual maximum approach and GPD with peaks over threshold approach have indicated that both GEV and GPD models gave similar or comparable wave height for the study area since there is no multiple storm event in a year. Influence of seasonality on wave height having different return period is also studied. Copyright Springer Science+Business Media B.V. 2012

Suggested Citation

  • N. Teena & V. Sanil Kumar & K. Sudheesh & R. Sajeev, 2012. "Statistical analysis on extreme wave height," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 64(1), pages 223-236, October.
    • Handle: RePEc:spr:nathaz:v:64:y:2012:i:1:p:223-236
    DOI: 10.1007/s11069-012-0229-y
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    Citations

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    Cited by:

    1. T. Muhammed Naseef & V. Sanil Kumar & Jossia Joseph & B. K. Jena, 2019. "Uncertainties of the 50-year wave height estimation using generalized extreme value and generalized Pareto distributions in the Indian Shelf seas," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 97(3), pages 1231-1251, July.
    2. Draycott, S. & Sellar, B. & Davey, T. & Noble, D.R. & Venugopal, V. & Ingram, D.M., 2019. "Capture and simulation of the ocean environment for offshore renewable energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 15-29.
    3. Gaidai, Oleg & Xu, Xiaosen & Wang, Junlei & Ye, Renchuan & Cheng, Yong & Karpa, Oleh, 2020. "SEM-REV offshore energy site wind-wave bivariate statistics by hindcast," Renewable Energy, Elsevier, vol. 156(C), pages 689-695.
    4. Gaidai, Oleg & Ji, Chunyan & Kalogeri, Christina & Gao, Junliang, 2017. "SEM-REV energy site extreme wave prediction," Renewable Energy, Elsevier, vol. 101(C), pages 894-899.
    5. Samuel Draycott & Thomas Davey & David M. Ingram, 2017. "Simulating Extreme Directional Wave Conditions," Energies, MDPI, vol. 10(11), pages 1-21, October.

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