Forward calculations based on observational data from horizontally towed platforms verify a high morphological consistency between the Diapycnal Spice Curvature (DSC) and synthetic seismic sections. As a classic parameter for characterizing the distribution and intensity of oceanic interleaved layers, DSC values correlate well with the amplitude magnitude and polarity of seismic signals, whose variations are approximately linearly related to contrasts of multiple oceanic physical parameters including temperature, salinity, density, and buoyancy frequency. Combined with inversion results of high-resolution temperature-salinity sections from multiple sea areas, seismic oceanography data confirm that oceanic interleaved layers are predominantly developed at the fronts and the lower edges of oceanic vortices. Different from the traditional understanding of vortex edge structures dominated by thermohaline staircases and intrusion structures, the seismic evidence indicates that thermohaline staircases are destroyed by vortex shear with their regional distribution controlled by vertical superimposed water mass structures, and interleaved layers act as the primary structural feature of vortex edges,
Seismic reflection sections can effectively identify the spatial distribution and intensity of oceanic interleaved layers, which provides new insights for the wide application of seismic oceanography data and opens up multiple research avenues. Subsequent studies can further explore the coupling relationships between interleaved layers and multi-scale ocean dynamic processes such as mesoscale/submesoscale eddies, fronts, internal waves, turbulence and double diffusion, as well as their dynamic evolution characteristics. Since the stirring process is critical to the formation of interleaved layers, these layers can also serve as effective indicators for evaluating ocean stirring and mixing. In addition, the combination of field towed section data and deep learning algorithms to directly retrieve DSC distribution from seismic data is a promising innovative direction for future related research.
 

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