Seasonal and interannual variations in material transport in the Korea Strait originating from the Taiwan Strait
Abstract Understanding the variability in material transport from the Taiwan Strait (TS) to the Korean Strait (KS) is crucial for predicting ecological changes and the spread of marine debris in the East Asian Marginal Seas (EAMS). However, the dynamic variability of this transport remains poorly un...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-08-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-13861-z |
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| Summary: | Abstract Understanding the variability in material transport from the Taiwan Strait (TS) to the Korean Strait (KS) is crucial for predicting ecological changes and the spread of marine debris in the East Asian Marginal Seas (EAMS). However, the dynamic variability of this transport remains poorly understood. In this study, we investigated the dynamic variability of material transport from the TS to the KS, using a Lagrangian particle-tracking system coupled with a three-dimensional numerical model. The model results showed that particles originating from the TS most frequently passed through the KS in August, with distinct interannual variability. Our findings indicate that southerly winds enhance the sea surface height (SSH) gradient in the southwestern East China Sea (ECS) shelf region through surface Ekman transport, weakening cross-shelf offshore currents and preventing particles from being transported offshore. The interannual variability of southerly winds is associated with variations in SSH in the southwestern shelf region, thereby modulating material transport from the TS to the KS. Furthermore, southerly winds over the EAMS are found to strengthen during negative phases of the Pacific Decadal Oscillation, suggesting a potential linkage between material connectivity in the EAMS and large-scale climate indices. These findings reveal how physical processes govern material transport in the EAMS, offering valuable insights into the prediction of nutrient fluxes and pollutant dispersion. |
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| ISSN: | 2045-2322 |