This Special Issue showcases innovative methods, including advanced signal processing and machine learning, to enhance ocean data quality and integration, fostering a deeper understanding of ocean-climate interactions. Despite their significance, many aspects of ocean science remain underexplored due to the complex interplay of physical, chemical, biological, and human factors. This Special Issue's papers cover a diverse range of topics, including improving sonar mosaics with curvelet transform, refining BGC-Argo radiometry, mapping bathymetry using Sentinel-2 and HPC, estimating Arctic water transport, the use of UAV-based LiDAR, optimizing wind sensing, analyzing heat flux at the sea-air interface, modeling float resistance, studying ocean turbulence, and leveraging AI for whale call analysis.
