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AI-Based Reconstruction of Eddy-Resolved Subsurface Currents in the Indo-Pacific Convergence Zone
编号：814 访问权限：仅限参会人 更新：2026-08-31 19:55:27 浏览：6次 口头报告

报告开始：2027年01月13日 09:00（Asia/Shanghai）

报告时间：15min

所在会场：[S32] Session 32 - AI for Ocean Dynamics: advancements, discoveries and challenges [S32-2] AI for Ocean Dynamics: advancements, discoveries and challenges

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摘要
Non-equilibrium processes are prevalent in the ocean and play a dominant role in governing energy exchange, vertical transport, and turbulent mixing. However, robust characterization of these processes remains challenging due to sparse observations and uncertainties in numerical models, particularly in dynamically active regions. This study develops a deep learning–based subsurface current reconstruction (DLSCR) model for the Indo-Pacific Convergence Zone (IPCZ), a dynamically complex region with multiscale circulation. The model reconstructs eddy-resolving (1/12°) three-dimensional subsurface ocean currents down to 643 m from sea surface information—including sea surface currents, height, temperature, salinity, and wind stresses. DLSCR demonstrates robust reconstruction skill throughout the upper 400 m of the ocean, with low root mean square errors and high spatiotemporal correlations. This capability is further illustrated by the model’s representation of key upper-ocean dynamical features in the IPCZ, including the spatiotemporal evolution of subsurface mesoscale eddies and the three-dimensional structure of the subtropical gyre. Beyond reconstruction skill, a perturbation-based interpretability analysis reveals surface currents (U/V) and SSH as the two primary contributors. Surface currents (U/V) affect subsurface current reconstruction across the full depth range, with the strongest sensitivity occurring in the mixed layer (0–50 m). In contrast, SSH exerts its primary influence in the thermocline (50–150 m). These results demonstrate that DLSCR captures physically meaningful surface–subsurface relationships in the IPCZ, providing an interpretable, data-driven framework for reconstructing eddying ocean interior.
 
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报告人
Qin Duan
PhD candidate South China Sea Institute of Oceanology

稿件作者
Qin Duan South China Sea Institute of Oceanology
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重要日期

  • 会议日期

    01月12日

    2027

    至

    01月15日

    2027

  • 07月21日 2026

    初稿截稿日期

  • 01月15日 2027

    注册截止日期

主办单位
State Key Laboratory of Marine Environmental Science, Xiamen University (MEL)
Department of Earth Sciences, National Natural Science Foundation of China (NSFC)
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