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<p>Ocean reanalysis data, compared to traditional observational data, possess stronger continuity and higher data accuracy. The globally high-resolution ice-ocean coupled reanalysis product China Ocean ReAnalysis, Version 2.0 (CORA v2.0), independently developed by the National Marine Information Center, has attracted considerable attention since its release in 2020. This study selected six representative points of sound velocity profiles in different global ocean regions and conducted comparative analysis between the 2014 momentary data from CORA v2.0 and Argo data. Additionally, the monthly average data of CORA v2.0 in 2013 were compared and studied against General Digital Environmental Model (GDEM) and World Ocean Atlas (WOA) data. Metrics such as Root Mean Square Error (RMSE) and Mean Error (ME) were introduced to evaluate the differences between datasets. The result reveals that, in a comparison of single moment data, the sound velocity profiles of CORA v2.0 data and Argo data exhibit high consistency, with ME generally within 2 m/s. Regarding a comparison of monthly average data, the consistency between CORA v2.0 data and WOA data is higher, while the error relative to GDEM data is relatively larger, but their RMSE and ME exhibit high similarity in temporal trends. Based on the 2014 data of CORA v2.0, the temporal and spatial evolutionary laws of global seawater sound velocity profiles and sound speed fields were analyzed. On the time scale, the variation of seawater sound speed is mainly influenced by seasons, with significant differences between winter and summer seasons. On the daily scale, there are certain differences in sound velocity profiles mainly in the early morning and afternoon. On the spatial scale, analysis was conducted from both horizontal and vertical perspectives. The distribution of sound speed exhibits evident regularity with latitude, with shallow seawater sound speed being greatly influenced by external factors while deep seawater is relatively stable. Using the Range-dependent Acoustic Model for Geoacoustics (RAMgeo) model to solve the underwater acoustic field at three specific points, the characteristic changes of sound velocity profiles at different times of the day and their impact on under water sound propagation losses were obtained. This paper provides valuable information for the application of CORA v2.0 data products.</p>

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Analysis of the distribution of sound velocity profiles and sound propagation laws based on a global high-resolution ocean reanalysis product

  • 期刊论文

  • 发表日期：

    2025年5月1日

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  • Shiyuan Tao,
  • Yi Yu,
  • Wenbin Xiao,
  • Weimin Zhang,
  • Yanlai Zhao

摘要

Ocean reanalysis data, compared to traditional observational data, possess stronger continuity and higher data accuracy. The globally high-resolution ice-ocean coupled reanalysis product China Ocean ReAnalysis, Version 2.0 (CORA v2.0), independently developed by the National Marine Information Center, has attracted considerable attention since its release in 2020. This study selected six representative points of sound velocity profiles in different global ocean regions and conducted comparative analysis between the 2014 momentary data from CORA v2.0 and Argo data. Additionally, the monthly average data of CORA v2.0 in 2013 were compared and studied against General Digital Environmental Model (GDEM) and World Ocean Atlas (WOA) data. Metrics such as Root Mean Square Error (RMSE) and Mean Error (ME) were introduced to evaluate the differences between datasets. The result reveals that, in a comparison of single moment data, the sound velocity profiles of CORA v2.0 data and Argo data exhibit high consistency, with ME generally within 2 m/s. Regarding a comparison of monthly average data, the consistency between CORA v2.0 data and WOA data is higher, while the error relative to GDEM data is relatively larger, but their RMSE and ME exhibit high similarity in temporal trends. Based on the 2014 data of CORA v2.0, the temporal and spatial evolutionary laws of global seawater sound velocity profiles and sound speed fields were analyzed. On the time scale, the variation of seawater sound speed is mainly influenced by seasons, with significant differences between winter and summer seasons. On the daily scale, there are certain differences in sound velocity profiles mainly in the early morning and afternoon. On the spatial scale, analysis was conducted from both horizontal and vertical perspectives. The distribution of sound speed exhibits evident regularity with latitude, with shallow seawater sound speed being greatly influenced by external factors while deep seawater is relatively stable. Using the Range-dependent Acoustic Model for Geoacoustics (RAMgeo) model to solve the underwater acoustic field at three specific points, the characteristic changes of sound velocity profiles at different times of the day and their impact on under water sound propagation losses were obtained. This paper provides valuable information for the application of CORA v2.0 data products.