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Availability of accurate remotely-sensed sea surface salinity (SSS) measurements is crucial to investigating fundamental aspects of the global hydrological cycle, ocean dynamics and marine biogeochemistry. The European Space Agency (ESA) Soil Moisture Ocean Salinity (SMOS) mission has been specifically designed for this aim. However, SMOS data display a high level of noise with respect to the signal they have to detect. Space–time averaging over relatively large sampling periods/areas is thus generally carried out to increase SSS accuracy, and further interpolation is required to fill in data gaps resulting from both mission geometry and other instrumental/physical limitations. Here, a daily, 1/4° nominal resolution, mesoscale-resolving SSS field product is obtained by using a multidimensional optimal interpolation (OI) algorithm combining SMOS salinity retrievals and satellite sea surface temperature data …