Improvement of wave predictions in marginal seas around Korea through correction of simulated sea winds

Son, Donghwi; Jun, Ki-Cheon; Kwon, Jungkee; Yoo, Jeseon; Park, Sung-Hwan

doi:10.1016/j.apor.2022.103433

Cited by 7 publications

(3 citation statements)

References 39 publications

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“…Figure 3 illustrates the interannual variations in the errors of three wind field products: ERA5, FNL, and CCMP. Analysis of the Slope values reveals a consistent underestimation of actual wind fields by ERA5 over 2017 −2021, corroborating findings from previous studies (Shi et al, 2021;Son et al, 2023;Zhai et al, 2023). Furthermore, in 2019 and 2020, all three wind field products exhibited varying degrees of underestimation.…”

Section: The Errors In the Wind Fieldssupporting

confidence: 87%

A general method to determine the optimal whitecapping dissipation coefficient in the SWAN model

Lei,

Wu,

et al. 2023

Front. Mar. Sci.

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Whitecapping dissipation is a critical term in affecting the accuracy of wave height modeling. However, the whitecapping dissipation coefficient (Cds), as a primary factor influencing whitecapping, is commonly determined through trial and error in various studies. In this study, we present a general method for calibrating the Simulating Waves Nearshore (SWAN) wave model using the whitecapping dissipation term, demonstrated through a detailed study in the South China Sea (SCS). Theoretical analysis reveals that the optimal Cds value shows a one-to-one correspondence with the applied wind field. Expectedly, under high-quality wind field conditions, the optimal Cds values tend to fall within a narrow range, regardless of the model domain or time span. Numerical experiments executed in the SCS further consolidated this inference, encompassing two common wind input schemes (ST6 and YAN) and three distinct whitecapping dissipation schemes (KOMEN, JANSSEN, and WST). Based on the experimental results, we have identified an optimal Cds range for each whitecapping dissipation scheme. Cds values within the optimal range consistently outperformed the default Cds in the SWAN model. Subsequent experiments verified the method’s applicability to the Gulf of Mexico and the Mediterranean Sea. The findings suggest that this research holds substantial promise for practical applications on a global scale.

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Section: The Errors In the Wind Fieldssupporting

confidence: 87%

A general method to determine the optimal whitecapping dissipation coefficient in the SWAN model

Lei,

Wu,

et al. 2023

Front. Mar. Sci.

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show abstract

“…The projected changes in sea surface winds also have broader significant implications for the occurrence and intensity of extreme events across the region. Stronger winds may escalate the severity of storms, consequently inducing extreme wave heights and leading to related hazards such as coastal flooding [8,9]. Changes in wind patterns can also influence regional climate dynamics, affecting precipitation and evaporation, which in turn can contribute to the onset or exacerbation of drought conditions [10,11].…”

Section: Introductionmentioning

confidence: 99%

Near-Future Projection of Sea Surface Winds in Northwest Pacific Ocean Based on a CMIP6 Multi-Model Ensemble

Bayhaqi,

Yoo,

Jang

et al. 2024

Atmosphere

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Information about wind variations and future wind conditions is essential for a monsoon domain such as the Northwest Pacific (NWP) region. This study utilizes 10 Generalized Circulation Models (GCM) from CMIP6 to evaluate near-future wind changes in the NWP under various climate warming scenarios. Evaluation against the ERA5 reanalysis dataset for the historical period 1985–2014 reveals a relatively small error with an average of no more than 1 m/s, particularly in the East Asian Marginal Seas (EAMS). Future projections (2026–2050) indicate intensified winds, with a 5–8% increase in the summer season in the EAMS, such as the Yellow Sea, East Sea, and East China Sea, while slight decreases are observed in the winter period. Climate mode influences show that winter El Niño tends to decrease wind speeds in the southern study domain, while intensifying winds are observed in the northern part, particularly under SSP5-8.5. Conversely, summer El Niño induces higher positive anomalous wind speeds in the EAMS, observed in SSP2-4.5. These conditions are likely linked to El Niño-induced SST anomalies. For the application of CMIP6 surface winds, the findings are essential for further investigations focusing on the oceanic consequences of anticipated wind changes such as the ocean wave climate, which can be studied through model simulations.

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“…The increasing rate of extreme ocean waves in northern latitudes, which also cover East Asian (EA) waters such as the East Sea (ES), the Yellow Sea (YS) and the East China Sea (ECS), is higher than that of the mean condition (Young et al, 2011) and is predicted to become more extreme in the future (Meucci et al, 2020). While extreme ocean surface waves are generally induced by storms and are associated with increasing surface wind speeds (Chun and Ahn, 2017;Heo et al, 2020), the EA region is notably sensitive to seasonal atmospheric phenomena, such as monsoonal systems (Chen et al, 2019;Son et al, 2023). Several wave climate studies conducted on a seasonal basis have shown that extreme wave heights in the EA seas have been increasing during the summer season (Liang et al, 2016;.…”

Section: Introductionmentioning

confidence: 99%

Effect of El Niño on Summer Extreme Ocean Waves over East Asian Regions

Bayhaqi,

Yoo

2023

Preprint

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Extreme wave events with devastating impacts on East Asian (EA) coastal regions have recently been more variable. However, despite being a prominent extreme spot due to the influence of anomalous seasonal atmospheric and remote climate variability, the investigation of EA extreme wave attributes, such as duration and intensity, and their relation to the climate events remains unclear. By applying the peaks-over-threshold (POT) method with a fixed threshold set at the 99th percentile, this study aimed to quantify the duration and intensity of EA extreme wave events in boreal summer from 1980–2021 and investigate the influence of El Niño and Pacific Decadal Oscillation (PDO) as the main climate mode in the Pacific Ocean. Spatially, the findings demonstrated that extreme waves have occurred with an intensity up to 1.5 m, persisting in a range from 8 to 35 hours over the study and revealing the prominent spot in the southern part of the study area, impacting the southern coast of Korea. Based on the area-averaged over the prominent spot, the appearance of El Niño induces longer (with an average of 85 h) and more intense summer extreme waves (with 2 m of max intensity). The results suggest that the eastward shifting of tropical storms (TS) due to the El Niño-induced anomalous westerlies at 5°N–10°N contributes to this condition. Furthermore, a positive PDO strengthens the El Niño effect, with the almost doubled in duration, through strong anomalous anticyclonic formation in the Philippine Sea. The study findings enhance our understanding of the link between ENSO and TS activity with respect to extreme wave duration and intensity; these factors can be relevant in formulating plans for mitigating the impact of extreme wave events on coastal environments.

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Improvement of wave predictions in marginal seas around Korea through correction of simulated sea winds

Cited by 7 publications

References 39 publications

A general method to determine the optimal whitecapping dissipation coefficient in the SWAN model

A general method to determine the optimal whitecapping dissipation coefficient in the SWAN model

Near-Future Projection of Sea Surface Winds in Northwest Pacific Ocean Based on a CMIP6 Multi-Model Ensemble

Effect of El Niño on Summer Extreme Ocean Waves over East Asian Regions

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