Nonstationary modelling of significant wave height using time series decomposition method

Huang, Weinan; Zhu, Xiaowen; Jin, Yishuai; Shen, Xingchen

doi:10.1016/j.oceaneng.2024.118731

Ocean Engineering

2024

DOI: 10.1016/j.oceaneng.2024.118731

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Nonstationary modelling of significant wave height using time series decomposition method

Weinan Huang,

Xiaowen Zhu,

Yishuai Jin

et al.

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2024

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Assessing extreme significant wave height in China’s coastal waters under climate change

Zhu,

Huang

2024

Front. Mar. Sci.

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Accurately estimating the return values of significant wave height is essential for marine and coastal infrastructure, particularly as climate change intensifies the frequency and intensity of extreme wave events. Traditional models, which assume stationarity in wave data, often underestimate future risks by neglecting the impacts of climate change on wave dynamics. Combining time series decomposition and recurrence analysis, the research develops a nonstationary framework to predict significant wave height. The stochastic component is modelled using a stationary probability distribution, while the deterministic component is predicted based on sea surface temperature projections from CMIP6 climate scenarios. The model evaluation demonstrates strong predictive capability for both stochastic and deterministic components. Application of the model to China’s coastal waters reveals significant discrepancies between stationary and nonstationary return value estimates. Compared to conventional distribution models, the nonstationary model predicts substantial increases in extreme wave heights. These findings underscore the importance of adopting nonstationary models to more accurately assess future risks posed by extreme wave events in a changing climate.

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Assessing extreme significant wave height in China’s coastal waters under climate change

Zhu,

Huang

2024

Front. Mar. Sci.

View full text Add to dashboard Cite

show abstract

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Nonstationary modelling of significant wave height using time series decomposition method

Cited by 1 publication

References 92 publications

Assessing extreme significant wave height in China’s coastal waters under climate change

Assessing extreme significant wave height in China’s coastal waters under climate change

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