Reconstruction Method of Ocean Front Model Based on Fuzzy Cluster Analysis of Sound Speed Profile

Ocean fronts are mostly determined according to the horizontal temperature gradient, and various selection criteria may lead to different frontal zones. This study proposes a frontal zone delineation method based on sound speed profile. In this paper, the sound speed profile of the Kuroshio intrusion front in the Luzon Strait is classified via fuzzy cluster analysis based on transitive closure and fuzzy C-means algorithm. At the same time, considering that ocean fronts affect sound propagation, we verify the effectiveness of the two algorithms in terms of sound transmission loss. The results show that in different depth ranges, the effectiveness of the two algorithms differs in identifying the frontal zone. At depth below 300 m, the sound speed profile changes drastically, and fuzzy cluster analysis based on the transitive closure is more effective. At 300-700 m depth where the sound speed profile tends to be stable, the fuzzy C-means algorithm is more effective. At 700-1000 m depth near the SOFAR axis (the depth of the minimum sound speed), fuzzy cluster analysis based on the transitive closure is more effective. Finally, based on the sound speed profile, we combine both algorithms for the first time to obtain a three-layer geometric optimized structure of the Kuroshio intrusion front in the Luzon Strait. The classification of sound speed profiles via the two fuzzy cluster algorithms provides a new way to judge the frontal zone in different depth ranges and reconstruct geometric models of ocean fronts.

Automated summary

This study proposes a method for delineating ocean fronts based on sound speed profiles, classifying them in different depth ranges using fuzzy cluster algorithms. The effectiveness of the algorithms in identifying frontal zones varies at different depths, with a combination of both algorithms resulting in a three-layer geometric optimized structure of the ocean front.