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Inversion of the full-depth sound speed profile based on remote sensing data and surface sound speed
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Qianqian Li1, 2, Honglin Li1, Shoulian Cao1, Xian Yan1, Zhichuan Ma1
Haiyang Xuebao | 2022, 44(12) : 84 - 94
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Haiyang Xuebao | 2022, 44(12): 84-94
• Article •
Inversion of the full-depth sound speed profile based on remote sensing data and surface sound speed
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Qianqian Li1, 2, Honglin Li1, Shoulian Cao1, Xian Yan1, Zhichuan Ma1
Affiliations
  • 1. College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China
  • 2. College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, China
Published: 2022-12-01 doi: 10.12284/hyxb2022149
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The ocean sound speed profile (SSP) determines the underwater acoustic propagation, and it is very important to obtain SSP in near real-time for underwater acoustic communication, positioning, and fish detecting. The single Empirical Orthogonal Function regression (sEOF-r) method inverts the SSP by establishing a linear regression relationship between the empirical orthogonal coefficient of the SSP and the sea surface remote sensing data. However, the ocean is a complex dynamical system, and the SSP and the remote sensing data are not simple linear. Therefore, based on the Argo historical gridded dataset, self-organizing map (SOM) was used to establish the nonlinear mapping between sea surface data, such as sea level anomaly (SLA), sea surface temperature (SST) and surface sound speed measured by surface velocimeter, and SSP anomaly. The three-dimensional sound speed field is then inverted by the near real-time remote sensing data and the surface sound speed. The results of the SSP inversion showed that, under the advantage of multi-source information fusion, the algorithm generated a smaller inversion error than linear inversion and had better robustness. It improved the average accuracy of inversion by about 2 m/s than sEOF-r method, and improved by about 1 m/s than classical SOM method that without considering the surface sound speed.

Argo dataset  /  sea surface temperature  /  sea level anomaly  /  EOF decomposition  /  surface velocimeter  /  sEOF-r method  /  SOM method
Qianqian Li, Honglin Li, Shoulian Cao, Xian Yan, Zhichuan Ma. Inversion of the full-depth sound speed profile based on remote sensing data and surface sound speed[J]. Haiyang Xuebao, 2022 , 44 (12) : 84 -94 . DOI: 10.12284/hyxb2022149
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Year 2022 volume 44 Issue 12
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Article Info
doi: 10.12284/hyxb2022149
  • Receive Date：2022-02-17
  • Online Date：2026-02-01
  • Published：2022-12-01
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  • Received：2022-02-17
  • Revised：2022-05-23
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Affiliations
    1. College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China
    2. College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, China
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光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
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