Abstract Recently, a new approach to remote sensing of water vapor based on the Global Positioning System (GPS) has been proposed. Specifically, the bending of radio signals propagating from GPS satellites to a receiver on a low earth-orbiting satellite can be used to derive vertical profiles of atmospheric refractivity. Vertical profiles of temperature and water vapor can then be retrieved from the refractivity measurements. This is potentially a valuable data source for the meteorological community. However, before such measurements are used for operational numerical weather prediction, we need to assess the accuracy of the retrieved temperature and moisture fields and properly assimilate these observations into a numerical model. A 4D data assimilation system based on the adiabatic version of the Penn State-NCAR Mesoscale Model and its adjoint was developed. A series of observing system simulation experiments was then conducted to assess the impact of GPS-derived atmospheric refractivity data. Specific...