Authors
Jiachen Yang, Qing Xie, Zhengjian Li, Desheng Chen, Changlin Chen, Jiabao Wen
Published in
Sensors (Basel, Switzerland). Volume 26. Issue 15. Aug 04, 2026. Epub Aug 04, 2026.
Abstract
Accurate daily three-dimensional (3D) ocean sound speed prediction is essential for underwater acoustic applications. Existing data-driven studies often focus on global field errors, leaving localized thermocline-related errors insufficiently addressed. Using ten years of daily GLORYS12 reanalysis data from an equatorial Pacific region, we developed a 3D ConvLSTM predictor for background spatiotemporal evolution. We then proposed the Full-Depth Dynamic Gradient-Guided Residual Correction Network (FDGRC-Net), which derives a continuous mask from the previous-day regional temperature gradient profile to guide residual learning and output gating. On the 2009 test set, FDGRC-Net reduced the overall RMSE from 0.4209 to 0.3916 m/s and the MAE from 0.2302 to 0.2180 m/s. It also demonstrated improved prediction performance in the northern South China Sea cross-region evaluation and achieved annual RMSE reductions of 5.12-7.90% in frozen 2010-2015 tests. Against 521 collocated Argo profiles, it slightly but consistently improved the observational agreement. In a controlled Bellhop diagnostic, the transmission loss MAE decreased from 2.825 to 2.489 dB and the mean arrival time error from 4.099 to 3.653 ms. These results demonstrate that FDGRC-Net provides an effective and physically interpretable approach to thermocline-aware daily 3D sound speed prediction.
PMID:
42590713
Bibliographic data and abstract were imported from PubMed on 13 Aug 2026.
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