## 5 Discussion
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Title** & **NWP Model and DA System** & **Assimilation Method** & **Impact** \\ \hline Potential Impacts of Radio Occultation Data Assimilation on Forecast Skill of Tropical Cyclone Formation in the Western North Pacific [74] & WRF, 3 DVAR & Using nonlocal excess phase operator of GNSS RO data & RO data had an impact on moisture forecasts, and increased low-level vorticity for developing cases. \\ Evaluating the Impacts of COSMIC-2 GNSS RO Bending Angle Assimilation on Atlantic Hurricane Forecast Using the HWFER Model [76] & HWRF, 3 DEnvVAR & With local forward operator & RO data assimilation were NCEP Bending Angle Model (NBAM) & more effective in correcting water vapor bias. \\ Impact of Refractivity Profiles from a Proposed GNSS-RO Constellation on Tropical Cyclone Forecasts in a Global Modeling System [77] & GDAS/GFS, 3 DEnvVAR & Using simulated RO refractivity from nature run & RO data had more effects on wind speed and IKE forecasts than global track forecasts. \\ Impact of Assimilation of GPS Radio Occultation Refractivity on the Forecast of Typhoon Usagi in 2007 [78] & JMA, 4 DVAR & Using RO refractivity & RO data had a positive impact on the forecast of a TC at the formative and developing stages and improved the dynamic fields. \\ An Impact Study of GNSS RO Data on the Prediction of Typhoon Neptune (2016) Using a Multiresolution Global Model with 3D-Hybrid Data Assimilation [79] & MPAS, 3 DVAR/EnKF & With local RO refractivity and bending angle operators & Assimilation with bending angle had better performance than refractivity, in particular for the wind forecast. \\ Understanding the impact of assimilating FORMOSAT-7/COSMIC-2 radio occultation refractionity on tropical cyclone genesis: Observing system simulation experiments using Hurricane Gordon (2006) as a case study [93] & WRF, 3 DVAR & Refractivity profiles & Assimilating RO data helped to capture the genesis and development in TC’s core region with abundant moisture and vorticity. \\ Impacts of Radio Occultation Data on Typhoon Forecasts as Explored by the Global MPAS-GSI System [94] & MPAS, 3 DVAR/EnKF & Local bending angle and refractivity & Assimilation RO data helped to capture the genesis and development in TC’s core region with abundant moisture and vorticity. \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Summary of studies assimilating GNSS RO data. Utilizing various methods to assimilate RO data leads to different impacts. The assimilation of bending angles performs better than refractivity and atmospheric profiles; it retains more information and needs more complicated observation operators. Assimilating refractivity or atmospheric profiles loses information inevitably due to the assumptions during the retrieval, but the operators used are concise. The assimilation of bending angles is significant for the global forecasts because the long propagation path can carry a cumulative effect, and the assimilation of refractivity or atmospheric profiles is more suitable for regional models and low layers. For the assimilation of GSNSS-R wind data, there are differences between assimilating GNSS-R wind speeds directly and VAM wind vectors. The TC structures are better described by VAM wind vectors. The assimilation involving wind directions makes the TC structure more organized than only assimilating wind speeds. The assimilation of VAM vectors also has a more positive impact on improving the accuracy of track and intensity forecasts. Wind data thinning also plays an important role in assimilation, and it helps reduce the risk of overfitting, although some information