In this study, the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5) with three-dimensional variational data assimilation (3DVAR) is utilized to investigate influences of GPS occultation refractivity on simulations of typhoons past Taiwan. Two recent cases were simulated, including Typhoon Nari in September 2001 and Typhoon Nakri in July 2002. The GPS observation data are taken from the Challenging Minisatellite Payload for Geophysical Research and Application (CHAMP) and Satélite de Aplicaciones Cieratíficas-C (SAC-C) satellites that provide several retrieved refractivity profiles in the simulated domain near the initialization time. Through 3DVAR, the observed refractivity can be quickly ingested into the model initial conditions to recover the information over the ocean. The initial moisture increments from ingested GPS refractivity soundings exhibit a maximum magnitude of about 1.5 g kg-1 associated with temperature increments of generally less than 0.2°C. The differences between the model local refractivity and the observed refractivity are less than 3% with a maximum magnitude of about 10 units. Pronounced increments from an occultation point are found within an influential radius of 500-600 km only. For the simulation without the assimilation of GPS refractivity (the no-GPS run). the simulated Typhoon Nari coherently moves southwestward toward Taiwan early in the simulation but then exhibits a westward track along the northwest of Taiwan after landfall. With GPS refractivity assimilated, the simulated westward track in the no-GPS run is closer to the west coast. During landfall, the cloud convection associated with the intense vortex core encounters the Central Mountain Range (CMR) and produces torrential rainfalls along its northwestern slope. Both the GPS run and the no-GPS run capture the observed feature of very intense rainfall over the southwestern slope base of the CMR later in the simulation, while the intensity as well as the track is improved in the GPS run. In the other case (Nakri), the simulated rainfall distributions, in general, are similar for both the GPS run and the no-GPS run; however, the GPS run exhibits a more pronounced low to the southeast of Taiwan, which results in more intense rainfall in the northeast of Taiwan as observed. Both GPS runs for Nari and Nakri show improved skills in 24-h accumulated rainfall prediction, in particular, at later stages, as supported by higher threat scores and smaller root-mean-square errors against observations over the island. This positive impact can be attributed largely to the fact that the accumulative effects from assimilation of initial GPS refractivity soundings are instrumental to model performance. A cycling 3DVAR scheme is also explored in the simulation for Nari to investigate the impact of complementary NASA Quick Scatterometer (QuikSCAT) near-surface wind observations on model prediction. When such observed near-surface wind is assimilated into reinitialization at a later integration time, the track prediction is further improved and thus the prediction for accumulated rainfall is improved as well.