Presented at the 2014 Ocean Sciences MeetingThe Aquarius/SAC-D satellite provides an opportunity to observe near-global sea surface salinity (SSS) with unprecedented space and time resolution not available from other components of the Global Ocean Observing System. In order to evaluate and quantify the potential utility of the SSS data for global and regional studies of SSS variability, our research group has been using the Level-2, three-beam swath data and Argo data to characterize and quantify random errors and systematic biases on a global grid. Analyses address: spectral characterization; ascending/descending biases; inter-beam biases; time-varying regional biases; comparison with in-situ Argo data; quantification of the large-scale space and time variations of biases; and potential methodologies for algorithm and product improvement. Despite continuing Level-2 product improvement, significant biases persist. Annual averaging can separate errors with large seasonal variability from stationary error patterns. Ascending/descending and inter-beam biases exhibit large-scale spatial structure and seasonal variability; such biases can be remedied using a combination of optimal interpolation and Empirical Orthogonal Functions. In addition to a global perspective, regional SSS variability and relevant error issues include examples from the Pacific and Indian Oceans.