as MPAS, provides a beneficial application. Use of this MPAS model with multiple 60-15 or 60-15-3 km resolution has demonstrated fairly good performance for predicting the local track and intensity variations of typhoons passing by the Taiwan area (e.g., [2; 3]). Improving the initial conditions for forecasts of tropical cyclones is a key point for enhancing the predictive skill. Data assimilation (DA) is one of the vital tools that can improve the initial conditions for forecasts of tropical cyclones. Among DA, the Gridpoint Statistical Interpolation (GSI) DA system has been developed by the National Centers for Environmental Prediction (NCEP), which can assimilate multiple observations including conventional and non-conventional observations. More details about NCEP GSI are provided by [PERSON] et al. [4] and [PERSON] et al. [5]. Through GSI with a built-in Ensemble Kalman Filter (EnKF), ensemble members with assimilation of various observations can be used to provide better and representative background errors that are flow dependent. A hybrid DA system then may be constructed with such background errors in combination with the static/climatological background errors set by a three-dimensional variational (3 DVAR) system [6]. Such a 3 DVAR/EnKF hybrid system is a versatile tool of model initialization for tropical cyclone forecasts in the academic community and operational centers including the Central Weather Bureau (CWB) in Taiwan [7]. The robustness of DA for improving the initial conditions for model forecasting essentially depends on the availability of the observations fit to the forecast regime, in particular, in the vicinity of tropical cyclones for investigation. There are few sounding observations (both conventional and non-conventional) near tropical cyclones over the ocean available for global model assimilation, and it turns out that tropical cyclones provided by global analysis, e.g., the NCEP Global Forecast System (GFS) Final Analysis (FNL), are often relatively weaker than the best track intensity. In order to remedy this shortcoming, implanting a vortex with consistently observed intensity is still required for improving the initial intensity and structure of tropical cyclones. The satellite radiance observations may often encompass the typhoon circulation to provide retrieved information that, however, is much coarser horizontally and vertically to resolve the typhoon vortex. To improve the vortex analysis limited by the observations, the original vortex in a tropical cyclone (TC) is removed in the initial guess from the global analysis, and then a bogus vortex is implanted through some procedures that were described in detail by [PERSON] [8]. The dynamical vortex initialization (DVI) method is one of the efficient vortex initializations that utilizes a dynamic forecast model in short-term cycling integration (e.g., one hour) and then relocates the spin-up vortex (after a few cycle runs) to the observed TC position as well as matches with the observed intensity [9; 10; 11; 12]. With the improved TC condition by DVI, the track and intensity forecasts of typhoons over the western North Pacific have been improved for regional models (e.g., [9; 10; 11; 12]) as well as for global models (e.g., [13]). Global Navigation Satellite System (GNSS) radio occultation (RO) has been an important source of observations over the ocean. The RO technique uses the radio waves transmitted by Global Positioning System (GPS) satellites that pass through the atmosphere and then reach the low-earth orbit satellites (LEO) with some refraction because of varying atmospheric refractive index along the raypath. The signals received by LEOs can provide vertical sounding profiles with high accuracy and vertical resolution (e.g., [14; 15]). Formosa Satellite-3 and Constellation Observing System for Meteorology, Ionosphere, and Climate (FORMOSAT-3/COSMIC, hereafter FS3/C) is one of the pioneer GPS RO missions with six LEOs to construct a global coverage through the constellation.