Abstract
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.
Highlights
Reasonable assessments of extreme significant wave heights are highly important for the security and expense of coastal defence and offshore structures (Ojeda and Guillén, 2006, 2008; Ojeda et al, 2010, 2011; Mortlock and Goodwin, 2015, 2016; Mortlock et al, 2017)
A sample is extracted from an accurate initial database, the extreme sample is identified by a reliable sampling method and an appropriate probability distribution model is fitted
Considering that the extreme significant wave height should be extrapolated based on an independent and identically distributed database required for the extreme value theory (EVT) (Coles, 2001; Sobradelo et al, 2011), these time series buoy measurements and numerical hindcasts should be processed
Summary
Reasonable assessments of extreme significant wave heights are highly important for the security and expense of coastal defence and offshore structures (Ojeda and Guillén, 2006, 2008; Ojeda et al, 2010, 2011; Mortlock and Goodwin, 2015, 2016; Mortlock et al, 2017). The generalized Pareto distribution (GPD) model (Coles, 2001) is widely used to extrapolate extreme significant wave heights (Martucci et al, 2010; Blanchet et al, 2015; Kapelonis et al, 2015; Boessenkool et al, 2017; Muhammed Naseef and Sanil Kumar, 2017) This method (i.e. the POT-GPD method) makes the most of the samples, extends the return period when the threshold is suitable (Alves and Young, 2003; You, 2011; Vanem, 2015a; Samayam et al, 2017; Shao et al, 2017) and, due to this method, extracts all high samples.
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