Previous assimilation studies of Global Positioning System (GPS) Radio Occultation (RO) data using the observing system simulation experiments (OSSEs) have shown very promising results (Zou et al. 1995, Kuo et al. 1997, Kuo et al. 2000, Kuo et al. 2002). Since then, significant efforts on the assimilation of GPS RO data have been made. As a result, world-wide operational centers have turned on the assimilation of GPS RO data in real-time applications. However, positive impacts have mostly shown in forecasts for global applications. The assimilation of real GPS RO has some difficulties in showing a meaningful positive impact in regional applications, including tropical storm predictions. This can be attributed to the low data density in time and space. It can be also attributed to ineffectiveness of assimilation methods/techniques. Therefore, a thorough study of the GPS data assimilation in an operational system is necessary to identify and solve the issues in real time forecasts and, eventually, improve the tropical storm forecasts. This paper will describe the ongoing efforts on assimilating Constellation Observing System for Meteorology Ionosphere & Climate (COSMIC) GPS RO observations using the Hurricane Weather Research and Forecast system (HWRF) and Gridpoint Statistical Interpolation (GSI) system in a near operational environment. Cycling schemes and background errors will be tuned for this study and their impact on the data assimilation will be discussed. The latest GSI based hybrid variational-ensemble capability will also be used in this work to test the impact of data assimilation methods in such a study. Preliminary results from these studies will be presented in this paper.