Presented at the 2016 Ocean Sciences MeetingSatellite sea-surface salinity (SSS) observations provide a new means for constraining an important state parameter in numerical ocean models. The benefits of assimilating satellite SSS observations include improved model surface density, near-surface convection, and thermohaline circulation. NOAA's Real Time Ocean Forecast System (RTOFS)-Global employs an eddy-resolving 1/12th-degree (approximately 9 km horizontal resolution) Hybrid Coordinate Ocean Model (HYCOM). In the current operational configuration, the RTOFS-Global sea-surface salinity is relaxed to PHC3 (Polar Science Center Hydrographic Climatology) climatological SSS fields. Experiments that separately use satellite SSS data and the PHC3 SSS climatology have been conducted to assess the impact of remotely-sensed surface salinity measurements on simulated upper-ocean salinity, temperature, and sea-surface height fields. The first phase of experiments employs a lower-resolution (1/4th-degree horizontal resolution) HYCOM model, a potential successor to the Modular Ocean Model as the oceanic component of a future version of NOAA's seasonal-interannual coupled Climate Forecast System (CFS). Results from when using satellite data are compared to results from NOAA's operational configuration, which uses an annual cycle of climatological monthly-mean SSS values. The model's sensitivity to constraining SSS to satellite measurements is explored in terms of relaxation strength and satellite data update interval using monthly-mean and nine-day-running-mean satellite SSS data from the European Space Agency's Soil Moisture - Ocean Salinity (SMOS) mission.