Explicit storm prediction necessitates detailed knowledge of the severe storm environment for input as initial conditions into an NWP model. Fortunately, the dataset provided by the United States ’Weather Surveillance Radar 88D network provides high spatial and temporal observations of severe storms. Therefore, the assimilation of radar data assimilation presents itself as an integral part of the development of a warn-on-forecast framework. Warn-on-forecast is the term given to the transforming of the severe weather prediction community from a mode of “warn-on detection” to a framework of issuing severe weather warnings based upon a short range forecast. This talk will focus on the assimilation of radar data for the improvement of short-term forecasts (1hr), of severe storms using the NCEP GSI hybrid ensemble-3DVar data assimilation system and the NMMB. In particular, the addition of a radar reflectivity forward model will be discussed along with preliminary results from a case study.