A global high-resolution temperature and salinity reconstruction by spatiotemporal multiscale correlations and dynamic height constraints

Abstract. High-resolution temperature and salinity (T & S) gridded datasets are essential for exploring large and mesoscale ocean phenomena. In this study, a global, weekly T & S gridded dataset with a horizontal resolution of 1/4° and a depth range of 0–1500 m from 2005 to 2023 is reconstructed using a four-dimensional multigrid analysis (4D-MGA) framework. With minimal prior statistical assumptions, the 4D-MGA efficiently extracts information from in-situ T & S profiles and satellite-observed sea level anomalies by integrating multiscale spatiotemporal correlation and physical constraints. The results show that the 4D-MGA product successfully delivers a credible, high-resolution analysis that combines robustness with reliable mesoscale information. Specifically, our product exhibits a lower root mean square error and excellent unbiased performance on a global scale when compared with the ARMOR3D product and the GLORYS reanalysis. http The product is then applied to investigate the linear trends of geostrophic transport within five key sections in WBCs. The 4D-MGA product is a subset of the high-resolution, objective analysis, gridded dataset for oceans, and it has the potential to advance our understanding of ocean dynamics and climate change. The weekly reconstructed dataset (4D-MGA) is freely available at https://doi.org/10.5281/zenodo.19378150.