The advent of under-ice profiling float and biologging techniques has enabled year-round observation of the Southern Ocean and its Antarctic margin. These under-ice data are often overlooked in widely used oceanographic datasets, despite their importance in understanding the seasonality and its role in sea ice changes, bottom water formation, and glacial melt. We develop a four-dimensional climatology of the Southern Ocean (south of 40°S and above 2,000 m) using Data Interpolating Variational Analysis, which excels in multi-dimensional interpolation and consistent handling of topography and advection. The climatology captures thermohaline variability under sea ice, previously hard to obtain, and outperforms other products in data fidelity with smaller root-mean-square errors and biases. Our dataset will be instrumental for investigating seasonality and for improving ocean models. This work further highlights the quantitative significance of under-ice data in reproducing ocean conditions, advocating for their increased use to achieve a better Southern Ocean observing system.