The South Atlantic Subtropical Underwater (STUW) was identified from Argo floats between 2001 and 2019. Expressed as a vertical salinity maximum at the subsurface, the STUW spreads over the western subtropical and tropical South Atlantic. The mean salinity, conservative temperature, and potential density of the STUW are 36.66 ± 0.43 g/kg, 22.62 ± 2.27°C, and 25.14 ± 0.49 kg/m 3 , respectively. Based on the criteria derived from the STUW properties described above and the results from the Estimating the Circulation and Climate of the Ocean (ECCO) model, the production and fate of the STUW are calculated. The annual mean subduction rate is 3.26 Sv, and effective subduction occurs from September to November. Approximately 73% (2.38 Sv) of the subducted STUW is transported toward the tropical Atlantic, and 23% (0.75 Sv) of the subducted STUW is dissipated near the STUW formation region; 99% of the subducted STUW particles are dissipated within 2 years. Water particles can enter/exit the STUW along the advection route of the STUW. A total of 3.92 Sv of the STUW volume dissipates within the tropical region between 1.5°S and 1°N, implying that STUW contributes to 98% of the total transport of the subtropical cell. This analysis tracks the South Atlantic STUW from formation to dissipation and highlights the importance of the STUW in governing the subtropical cell.

The variability in sea surface salinity (SSS) on different time scales plays an important role in associated oceanic or climate processes. In this study, we compare the SSS on sub-annual, annual, and interannual time scales among ten datasets, including in situ-based and satellite-based SSS products over 2011–2018. Furthermore, the dominant mode on different time scales is compared using the empirical orthogonal function (EOF). Our results show that the largest spread of ten products occurs on the sub-annual time scale. High correlation coefficients (0.6~0.95) are found in the global mean annual and interannual SSSs between individual products and the ensemble mean. Furthermore, this study shows good agreement among the ten datasets in representing the dominant mode of SSS on the annual and interannual time scales. This analysis provides information on the consistency and discrepancy of datasets to guide future use, such as improvements to ocean data assimilation and the quality of satellite-based data.