<p>In this study, the spatiotemporal characteristics and influencing mechanisms of eddy–eddy interactions in the Agulhas leakage region (ALR) from 1993 to 2023 are investigated. We use satellite observations and drifter data, applying the angular momentum eddy detection and tracking algorithm (AMEDA) for eddy identification and tracking. Temporally, the analysis reveals a declining trend in both the number of eddy–eddy interactions and the eddy number over the study period. This trend contrasts with the increasing interannual trends observed for eddy kinetic energy (EKE) and enstrophy. Seasonally, periods characterized by higher EKE, enstrophy, and eddy intensity correspond to a lower eddy Rossby number and more stable eddies, during which both eddy number and the number of eddy–eddy interactions are relatively low. Spatially, these interactions are predominantly concentrated in the area between the western Agulhas Plateau and the eastern Agulhas Ridge. The region is characterized by short eddy lifespans, concentrated eddy generation and dissipation, large topographic gradients, and intense current shear. The synergy of these conditions—particularly the influence of topography on eddies and the current shear between the Agulhas Current and the Antarctic Circumpolar Current—is responsible for the high number of eddy–eddy interactions observed here. By elucidating the spatiotemporal patterns and underlying dynamics of eddy–eddy interactions in the ALR, this study contributes to a deeper understanding of mesoscale eddy life cycles and their implications for ocean energy variability.</p>

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Spatiotemporal characteristics of eddy–eddy interactions in the agulhas leakage region

  • Wang Zhu,
  • Guoqing Han,
  • Xiayan Lin,
  • Yu Liu,
  • Bo Li

摘要

In this study, the spatiotemporal characteristics and influencing mechanisms of eddy–eddy interactions in the Agulhas leakage region (ALR) from 1993 to 2023 are investigated. We use satellite observations and drifter data, applying the angular momentum eddy detection and tracking algorithm (AMEDA) for eddy identification and tracking. Temporally, the analysis reveals a declining trend in both the number of eddy–eddy interactions and the eddy number over the study period. This trend contrasts with the increasing interannual trends observed for eddy kinetic energy (EKE) and enstrophy. Seasonally, periods characterized by higher EKE, enstrophy, and eddy intensity correspond to a lower eddy Rossby number and more stable eddies, during which both eddy number and the number of eddy–eddy interactions are relatively low. Spatially, these interactions are predominantly concentrated in the area between the western Agulhas Plateau and the eastern Agulhas Ridge. The region is characterized by short eddy lifespans, concentrated eddy generation and dissipation, large topographic gradients, and intense current shear. The synergy of these conditions—particularly the influence of topography on eddies and the current shear between the Agulhas Current and the Antarctic Circumpolar Current—is responsible for the high number of eddy–eddy interactions observed here. By elucidating the spatiotemporal patterns and underlying dynamics of eddy–eddy interactions in the ALR, this study contributes to a deeper understanding of mesoscale eddy life cycles and their implications for ocean energy variability.