Natural hazards and earth system sciences · 2019 · 36 citations · 72 references
Natural SciencesOcean EngineeringOceanographyCoastal EngineeringOcean WavesPhysical OceanographyExtreme Ocean WavesSurface Wave MethodsTropical Cyclone ForecastingTropical WavesWave ForecastingWave StatisticsExtreme Wave StatisticsGeneralized Pareto DistributionSample DistributionSignificant Wave HeightSignificant Wave Height EstimationWave Extremes AnalysisWave Height DistributionWave Heights
Abstract. Extreme significant wave heights are assessed in the South China Sea (SCS), as assessments of wave heights are crucial for coastal and offshore engineering. Two significant factors include the initial database and assessment method. The initial database is a basis for assessment, and the assessment method is used to extrapolate appropriate return-significant wave heights during a given period. In this study, a 40-year (1975–2014) hindcast of tropical cyclone waves is used to analyse the extreme significant wave height, employing the peak over threshold (POT) method with the generalized Pareto distribution (GPD) model. The peak exceedances over a sufficiently large value (i.e. threshold) are fitted; thus, the return-significant wave heights are highly dependent on the threshold. To determine a suitable threshold, the sensitivity of return-significant wave heights and the characteristics of tropical cyclone waves are studied. The sample distribution presents a separation that distinguishes the high sample from the low sample, and this separation is within the stable threshold range. Because the variation in return-significant wave heights in this range is generally small and the separation is objectively determined by the track and intensity of the tropical cyclone, the separation is selected as a suitable threshold for extracting the extreme sample in the tropical cyclone wave. The asymptotic tail approximation and estimation uncertainty show that the selection is reasonable.
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S. Uppala, P. Kållberg, A. J. Simmons et al. · Quarterly Journal of the Royal Meteorological Society · 2005 · 7.1K citations · Full text
Statistical Inference Using Extreme Order Statistics
James Pickands · The Annals of Statistics · 1975 · 3.6K citations