Presented at the 2014 Ocean Sciences MeetingA new gridded high-resolution sea surface salinity (SSS) dataset has been developed at the University of Hawaii using Aquarius Level-2 data. The primary product is a weekly analysis on a nearly-global 0.5-degree grid for the period September 2011-present. The analysis is based on optimum interpolation (OI) that takes into account analyzed errors on the observations and, particularly, correlated errors, referred to here as inter-beam biases that appear to correlate over long distances along the satellite tracks. The method also includes a large-scale correction for satellite biases using Empirical Orthogonal Functions, filtering of along-track SSS data prior to OI, and the use of realistic correlation scales of mesoscale SSS anomalies. All these features are shown to result in more accurate SSS maps, free from spurious structures. A statistical description, based on the comparison between SSS maps and concurrent in-situ data, is used to demonstrate the utility of the OI analysis and the potential of Aquarius SSS products to document salinity structure at ~150 km and weekly scales. Applications of the product are exemplified by the derived patterns of regional SSS variability.