The Naval Research Laboratory at Stennis Space Center, MS, has implemented a near-real-time automated processing and quality control system for selected ocean surface parameters derived from remote sensing. The initial atmospheric parameter selected for development was specific humidity derived from the DMSP SSM/I and POES AMSU sensors, based on a recent set of specific humidity algorithms of Jackson, et al. (2006). The single-instrument algorithms were implemented for daily data feeds from NOAA's Comprehensive Large Array-data Stewardship System (CLASS). The derived specific humidity values are processed through an automated data quality control routine that assigns a probability of error to each observation based on climatological or model-based background fields and variabilities. A 42-month dataset of matchups with real-time in situ measurements was developed using ship and buoy observations obtained from NOAA's National Centers for Environmental Prediction. The matchups are used to assess the bias and error characteristics of the remote sensing-derived specific humidity in comparison with global atmospheric model fields.