A Gaussian-surface-based approach to identifying oceanic multi-eddy structures from satellite altimeter datasets

This study presents a Gaussian-surface-based approach to identifying multi-eddy structures from the sea level anomaly (SLA) maps. The SLA signals of an eddy are modeled by a two-dimensional anisotropic Gaussian surface. An identification criterion is introduced to determine whether to retain or split a multi-eddy structure. Detection result of a three-eddy structure from the SLA in the South China Sea (SCS) demonstrates the effectiveness of the identification approach. Comparison with a merger event previously reported about a multi-eddy structure in northern SCS reveals the advantage of this approach over simple splitting strategy, which may lose the eddy-eddy interaction details conveyed by real multi-eddy structures.