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<p>The regional sea level budget in the South China Sea, which remains poorly assessed and understood, is critical for evaluating coastal risks to densely populated cities. This study quantifies the sea level budget and assesses different time-scale climate modes (i.e., El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Pacific Decadal Oscillation (PDO)) on the modulation of sea level variability during 2003–2023. The altimetric-observed sea level trend is 4.29±0.51 mm/yr, with approximately 49% explained by Steric Sea Level (SSL; ~15%) and Mass Sea Level (MSL, ~34%) components, leaving an unexplained residual of 2.22±0.75 mm/yr (51%). This residual primarily reflects inadequate Argo-derived thermohaline data constraints and cumulative errors across observational platforms. Using an AutoRegressive Distributed Lag (ARDL) model and Multiple Linear Regression (MLR), we assessed the influence of different time-scale climate modes on sea level trends. We found that ENSO and PDO lead to the rising sea level trends and amplify its budget residual, while IOD has a weak influence on the residual. After removing ENSO or PDO signals via the two methods, a decrease in sea level trends is exhibited, with a pronounced impact on SSL. Notably, the MLR method revealed a greater decrease in the sea level trend than the ARDL model, suggesting that sea level anomalies at adjacent times significantly contribute to the intrinsic long-term trend. The findings of this study will contribute to the regional sea level budget research and potentially provide climatic guidance on coastal adaptation strategies to sea level changes.</p>

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Regional sea level budget and its response to multi-timescale climate modes in the South China Sea

  • 期刊论文

  • 发表日期：

    2025年8月11日

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  • Pengfei Yang,
  • Hok Sum Fok

摘要

The regional sea level budget in the South China Sea, which remains poorly assessed and understood, is critical for evaluating coastal risks to densely populated cities. This study quantifies the sea level budget and assesses different time-scale climate modes (i.e., El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Pacific Decadal Oscillation (PDO)) on the modulation of sea level variability during 2003–2023. The altimetric-observed sea level trend is 4.29±0.51 mm/yr, with approximately 49% explained by Steric Sea Level (SSL; ~15%) and Mass Sea Level (MSL, ~34%) components, leaving an unexplained residual of 2.22±0.75 mm/yr (51%). This residual primarily reflects inadequate Argo-derived thermohaline data constraints and cumulative errors across observational platforms. Using an AutoRegressive Distributed Lag (ARDL) model and Multiple Linear Regression (MLR), we assessed the influence of different time-scale climate modes on sea level trends. We found that ENSO and PDO lead to the rising sea level trends and amplify its budget residual, while IOD has a weak influence on the residual. After removing ENSO or PDO signals via the two methods, a decrease in sea level trends is exhibited, with a pronounced impact on SSL. Notably, the MLR method revealed a greater decrease in the sea level trend than the ARDL model, suggesting that sea level anomalies at adjacent times significantly contribute to the intrinsic long-term trend. The findings of this study will contribute to the regional sea level budget research and potentially provide climatic guidance on coastal adaptation strategies to sea level changes.