地球科学进展 doi: 10.11867/j.issn.1001-8166.2025.096

   

南海中尺度涡旋预报研究进展
朱学明1,王海龙2,郭绍敬1,张旭日1   
  1. (1. 南方海洋科学与工程广东省实验室(珠海) 中山大学海洋科学学院,广东 珠海 519082;2. 广东海洋大学 海洋与气象学院,广东 湛江 524088)
  • 出版日期:2025-11-01
  • 基金资助:
    国家自然科学基金面上项目(编号:42176029);南方海洋科学与工程广东省实验室(珠海)资助项目(编号:SML2023SP202,SML2024SP023)资助.

Research Progress on the Prediction of Oceanic Mesoscale Eddies in the South China Sea

ZHU Xueming1, WANG Hailong2, GUO Shaojing1, ZHANG Xuri1   

  1. (1. Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) & School of Marine Sciences, Sun Yat-sen University, Zhuhai Guangdong 519082, China; 2. School of Oceanography and Meteorology, Guangdong Ocean University, Zhanjiang Guangdong 524088, China)
  • Online:2025-11-01 Published:2025-11-01
  • About author:ZHU Xueming, research areas include marine environmental numerical simulation and forecasting. E-mail: zhuxueming@sml-zhuhai.cn
  • Supported by:
    Project supported by the National Natural Science Foundation of China (Grant No. 42176029); Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) Sponsored Project (Grant No. SML2023SP202, SML2024SP023).
海洋中尺度涡携带了海洋上层超过90% 的动能,是调控物质和能量输送的关键动力过程。南海作为西北太平洋最大的半封闭边缘海,是中尺度涡的高发区,其生消动力过程复杂,长期以来一直是物理海洋学研究的重点。通过对国内外相关文献的综合分析,发现对南海中尺度涡三维结构的认识更加清晰,生成机制主要包括局地风应力、吕宋海峡黑潮入侵、太平洋Rossby 波西传或多种因素共同作用,而其耗散主要由传播过程中的失稳或与内波发生相互作用导致;现有主流数值模式、同化和人工智能技术虽然具有重构和预报中尺度涡的能力,但准确度仍有待进一步提高,可为南海中尺度涡动力过程的深入理解与业务化预报技巧的提升提供系统性参考。建议未来中尺度涡研究应聚焦于多技术融合的协同优化路径,将中尺度涡动力理论、先进的海洋数值模式、资料同化、大数据和人工智能等技术进行有机结合,以进一步提升中尺度涡旋的预报精度。
AbstractOceanic Mesoscale Eddies (ME) carry more than 90% of the kinetic energy in the upper global ocean, playing vital roles in the material and energy transport. They are highly active in the South China Sea (SCS), with complex dynamics for their generation and dissipation, which are received an increasingly attention from physical oceanographers. Through comprehensive analysis of extensively relevant literatures, it is found that the understanding of the three-dimensional structural characteristics of ME in the SCS more clear, the mechanisms of generation mainly include local wind stress, intrusion of the Kuroshio from the Luzon Strait, the westward propagation of Rossby wave in the Pacific Ocean, and a combination of multiple factors. ME’s dissipation is mainly caused by instability during their propagation or interaction with internal waves. It is shown that there is the ability to reconstruct and predict ME for those popular numerical models, data assimilation, and artificial intelligence technologies, but their accuracy still needs to be further improved. It aims to provide a systematic reference for the comprehensive understanding of ME dynamical processes and the improvement of their operational forecasting skills in the SCS. We suggest that combining dynamics theory, advanced ocean numerical models and data assimilation, big data and artificial intelligence to optimize ME simulation, is one of the key points for eddy research and forecasting in the future.

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