High-resolution temperature and salinity (<em>T </em>&<em> S</em>) gridded datasets are essential for exploring large and mesoscale ocean phenomena.<span> </span>In this study, a global, weekly <em>T </em>&<em> S</em> 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-dimensio<span>nal multigrid analysis (4D-MGA) framework</span>.<span> With minimal prior statistical assumptions, the 4D-MGA efficiently extracts information from in-situ </span><em>T </em>&<em> S</em><span> profiles and satellite</span>-<span>observed </span>sea level anomalies<span> by integrating multiscale spatiotemporal</span> correlation<span> and physical constraints.</span><span> The results show that the </span>4D-MGA <span>product successfully delivers a credible, high-resolution analysis that combines robustness with reliable mesoscale information.</span><span> Specifically,</span> <span>our product exhibits a lower </span>root mean square error <span>and excellent unbiased performance on a global scale when compared with the ARMOR3D product and the GLORYS reanalysis. </span>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<span>.</span> <span>The weekly reconstructed dataset (4D-MGA) is freely available </span>at <a href="https://doi.org/10.5281/zenodo.19378150" target="_blank" rel="noopener"><span>https://doi.org/10.5281/zenodo.19378150</span></a>.