Estimation of mean and extreme waves in the East China Seas

Li, Jiangxia; Chen, Yongping; Pan, Shunqi; Pan, Yi; Fang, Jiayu; Sowa, Derrick M.A.

doi:10.1016/j.apor.2016.01.005

Cited by 40 publications

(14 citation statements)

References 13 publications

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“…The log-Pearson type III distribution curve method is recommended by the Water Resources Council of the United States, and it was fitted to the sample hydrological data by using the mean, standard deviation, and skewness coefficient of the logarithms [27,28]. This method is also widely used in the frequency analysis of extreme hydrology events in China [29,30]. In this study, we chose the Pearson type III (P-III) distribution curve to model the marginal distribution of rainstorms and typhoon surges, using Simpson's Rule to reduce the error.…”

Section: Marginal Distributionmentioning

confidence: 99%

Copula-Based Joint Probability Analysis of Compound Floods from Rainstorm and Typhoon Surge: A Case Study of Jiangsu Coastal Areas, China

Yuan

Xiong

2018

Sustainability

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Coastal areas are vulnerable to floods caused by rainstorms and typhoons. It is necessary to ascertain the risk of floods caused by both of these extreme weather events. A conceptual risk model is proposed to evaluate the rainstorm risk, typhoon surge risk, and the compound risk in the coastal areas of Jiangsu Province during the period of 1960-2012. The results of the model show that the typhoon surge risk in the study region is greater than the rainstorm risk. Three Archimedean copulas were used to fit the joint probability distributions of the compound events. The Frank copula and the Gumbel copula proved to be the best-fitting joint distribution function for the Huaibei plain district and the Lixiahe district, respectively. The probability of the extreme compound events not happening is less than 90% in the study region. This means that the flood risk is mainly subject to the encounter of a low-level rainstorm and a low-level typhoon surge. The study shows that the northern region of Jiangsu Province is more vulnerable to the compound risk, and that we should pay more attention to the floods caused by the compound events of rainstorm and typhoon surge.

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Section: Marginal Distributionmentioning

confidence: 99%

Copula-Based Joint Probability Analysis of Compound Floods from Rainstorm and Typhoon Surge: A Case Study of Jiangsu Coastal Areas, China

Yuan

Xiong

2018

Sustainability

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“…Therefore, there is a need to project future regional wave climate and assess the impacts of its change. Progress on this topic has been reported for regions like northeast Atlantic Ocean (Izaguirre et al, ; Aarnes et al, ), northwest Mediterranean Sea (Casas‐Prat and Sierra, ), North Sea (Groll et al, ), northeast Atlantic Ocean and the Mediterranean (Perez et al, ), West European Seas (Zacharioudaki et al, ), East China Sea (Li et al, ), among others, and all have noted strong regional deviations from projected global trends. In this study, we use general circulation model (GCM) wind output to simulate surface ocean waves along the Indian coast and present the mean wave climate at selected locations for a better understanding of the wave parameters for effective coastal zone management.…”

Section: Introductionmentioning

confidence: 99%

Wave climate projections along the Indian coast

Chowdhury

Behera

Reeve

2019

Intl Journal of Climatology

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Future changes in wave climate will influence the marine ecosystem, coastal erosion, design of coastal defences, operation of near-and off-shore structures, and coastal zone management policies and may further add to the potential vulnerabilities of coastal regions to projected sea level rise. Many studies have reported changes in the global wave characteristics under climate change scenarios, but it is important to project future changes in local/regional wave climate for smooth implementation of policies and preventing severe coastal erosion and flooding. In this study the regional wave climate along the Indian coast for two time slices, 2011-2040 and 2041-2070, is reported using an ensemble of near-surface winds generated by four different CMIP5 general circulation models (GCMs), under RCP4.5 scenario. Comparison of the wave climate for the two time slices shows an increase in wave heights and periods along much of the Indian coast, with the maximum wave heights increasing by more than 30% in some locations. An important finding is that at most locations along the east coast, wave periods are expected to increase by almost 20%, whereas along the west coast an increase of around 10% is expected. This will alter the distribution of wave energy at the shoreline through changes in wave refraction and diffraction, with potential implications for the performance and design of coastal structures and swash-aligned beaches. Furthermore, the computations show material changes in the directional distribution of waves. This is particularly important in determining the longshore transport of sediments and can lead to realignment of drift-aligned beaches, manifesting itself as erosion and/or siltation problems. This study is a preliminary contribution towards regional climate projections for the Indian Ocean region which are needed to plan and mitigate the impacts of future climate change. K E Y W O R D S climate change, coastal vulnerability, dynamical projections, Indian coast, surface ocean waves, wave climate variability

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“…A comprehensive understanding of the ocean surface waves arising from extreme weather conditions is of great interest to coastal and ocean engineers and oceanographers. Many studies about predicting, simulating, or hindcasting typhoon-generated storm waves and storm surges have been carried out through numerical models because wave buoys cannot be deployed throughout an entire marine area [10][11][12][13][14]. A third-generation spectral wind wave model is mainly driven by wind fields and has been widely used to predict, simulate, and hindcast wave heights.…”

Section: Introductionmentioning

confidence: 99%

Numerical Simulation of Large Wave Heights from Super Typhoon Nepartak (2016) in the Eastern Waters of Taiwan

Hsiao

Chen

et al. 2020

JMSE

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Super Typhoon Nepartak (2016) was used for this case study because it is the most intense typhoon that made landfall in Taiwan in the past decade. Winds extracted from the Climate Forecast System version 2 (CFSV2) and ERA5 datasets and merged with a parametric typhoon model using two hybrid techniques served as the meteorological conditions for driving a coupled wave-circulation model. The computed significant wave heights were compared with the observations recorded at three wave buoys in the eastern waters of Taiwan. Model performance in terms of significant wave height was also investigated by employing the CFSV2 winds under varying spatial and temporal resolutions. The results of the numerical experiments reveal that the simulated storm wave heights tended to decrease significantly due to the lower spatial resolution of the hourly winds from the CFSV2 dataset; however, the variations in the storm wave height simulations were less sensitive to the temporal resolution of the wind field. Introducing the combination of the CFSV2 and the parametric typhoon winds greatly improved the storm wave simulations, and similar phenomena can be found in the exploitation of the ERA5 dataset blended into the parametric wind field. The overall performance of the hybrid winds derived from ERA5 was better than that from the CFSV2, especially in the outer region of Super Typhoon Nepartak (2016).

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Estimation of mean and extreme waves in the East China Seas

Cited by 40 publications

References 13 publications

Copula-Based Joint Probability Analysis of Compound Floods from Rainstorm and Typhoon Surge: A Case Study of Jiangsu Coastal Areas, China

Copula-Based Joint Probability Analysis of Compound Floods from Rainstorm and Typhoon Surge: A Case Study of Jiangsu Coastal Areas, China

Wave climate projections along the Indian coast

Numerical Simulation of Large Wave Heights from Super Typhoon Nepartak (2016) in the Eastern Waters of Taiwan

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