The focus of this study is the latter. In particular, a series of observing system simulation experiments (OSSEs) is conducted to gauge the impact of NIS data on tropical cyclone simulations performed with the University of Wisconsin Nonhydrostatic Modeling System (UW-NMS). Previous work by the authors has demonstrated the power of the Ensemble Kalman Filter (EnKF) in convective-scale data assimilation, and so the EnKF is the assimilation framework of choice. It is demonstrated that the type, density and frequency of observations anticipated to be provided by NIS can indeed be expected to result in significant improvement in tropical cyclone prediction. In particular, significant reduction in track, intensity and precipitation forecast errors are demonstrated.