Emerging vortex street in the ocean from multi-source big data

Oceanic vortex streets are a representative wake phenomenon generated by the interaction between oceanic currents and bluff bodies such as islands, reefs, and offshore wind-energy infrastructures. They serve as an important vehicle for investigating coastal material transport, energy cascades, and ecological responses. This review aims to provide an integrative synthesis of recent advances in oceanic vortex street research from the perspectives of simulation data, observational data, and their related applications. We first review the fundamental role of traditional numerical simulations in producing high‑fidelity flow fields and elucidating dynamical mechanisms in oceanic vortex street simulations, as well as the extended value of AI-physics integrated approaches for rapid prediction, sparse reconstruction, and parameter inversion. Then, we review the application of various multi-source remote sensing data, including multispectral imagers and synthetic aperture radar, together with in situ observations and reanalysis products, in the identification and process‑based analysis of oceanic vortex streets, with particular emphasis on the contribution of coordinated multi-source observations to understanding their driving mechanisms and evolution. Building on a multi-source big data framework that integrates remote sensing observations and numerical simulations, we further examine recent progress and emerging applications of oceanic vortex streets in cross-disciplinary fields, including ecological, biological, and biogeochemical studies. Finally, from a data‑oriented perspective, we identify two major challenges currently facing oceanic vortex street research, namely limited observability and insufficient data-driven application, and propose corresponding solutions and recommendations.