Reconstruction of Interior Velocity in the Southern Pacific Ocean Using Satellite and Argo Data

• Published in: IEEE geoscience and remote sensing letters 2025, Vol.22, p.1-5
• Main Authors: Xiang, Liang, Xu, Yongsheng, Sun, Haiwei, Zhang, Qingjun, Kong, Weiya, Zhang, Lin, Zhang, Xiangguang, Huang, Chao, Zhao, Dandan
• Format: Article
• Language: English
• Subjects: Accuracy; Dynamical modes decomposition; interior ocean velocity; machine learning; Meters; Ocean temperature; Oceans; Radio frequency; remote sensing; Salinity (geophysical); Satellites; Sea surface; Surface reconstruction; Surface topography
• ISSN: 1545-598X; 1558-0571
• DOI: 10.1109/LGRS.2024.3508023

Ocean velocities are essential for understanding how the ocean influences and responds to climate dynamics, making their accurate reconstruction crucial for both climate modeling and predictions. However, reconstructing interior ocean velocities remains a significant challenge due to the sparse distribution of velocity observations and the ocean's complex dynamics. In this study, we introduce an efficient methodology for reconstructing interior ocean velocities by combining sea surface satellite data-including sea surface height (SSH), temperature, wind, and current-with Argo velocity observations, using the dynamic mode decomposition (DMD) technique. DMD offers the advantage of reducing the dimensionality of interior velocity fields, helping to address the limitations caused by sparse observations. The reconstructed velocity for the Southern Pacific Ocean (SPO) was validated against Argo and acoustic Doppler current profiler (ADCP) velocities, showing a strong correlation than GLORYS12V1 velocities. In particular, the reconstructed velocities have a mean correlation coefficient of 0.78 for the zonal component and 0.74 for the meridional component above 1000 m. Additionally, the reconstructed flow field exhibits a coherent pattern that closely aligns with the eddies observed in SSH. This research significantly contributes to the Global Ocean Monitoring and Observing Program by enhancing both the accuracy and resolution of ocean velocity measurements.