The Influential Factors and Prediction of Kuroshio Extension Front on Acoustic Propagation-Tracked

The Kuroshio Extension front (KEF) considerably influences the underwater acoustic environment; however, a knowledge gap persists regarding the acoustic predictions under the ocean front environment. This study utilized the high-resolution ocean reanalysis data (JCOPE2M, 1993–2022) to assess the impact of the KEF on the underwater acoustic environment. Oceanographic factors were extracted from the database using the Douglas-Peucker algorithm, and acoustic propagation characteristics were obtained using the Bellhop raytracing model. This study employed a backpropagation neural network to predict the acoustic propagation affected by the KEF. The depth of the acoustic channel axis and the vertical gradient of the transition layer of sound speed were identified as the fundamental factors influencing the first area of convergence, with correlations between the former and the distance of the first convergence zone ranging from 0.52 to 0.82, and that for the latter ranging from −0.42 to −0.7. The proposed method demonstrated efficacy in forecasting first convergence zone distances, predicting distances with less than 3 km error in >90% of cases and less than 1 km error in 68.61% of cases. Thus, this study provides a valuable predictive tool for studying underwater acoustic propagation in ocean front environments and informs further research.