Impact of GNSS Radio Occultation and Reflectometry Data Assimilation on Tropical Cyclogenesis Prediction

Accurate prediction of tropical cyclogenesis is fundamental to enhancing typhoon forecasting and disaster mitigation. This study investigates the impacts of Global Navigation Satellite System (GNSS) observations on cyclogenesis predictions by integrating a multi-case statistical evaluation with a targeted case study. Initially, the impact of GNSS Radio Occultation (RO) data assimilation (DA) was assessed by assimilating both conventional observations and RO data in ten tropical cyclone cases in the Northwestern Pacific from 2020 to 2022. Utilizing the WRF hybrid-3DEnVar system, the results demonstrate that incorporating RO data with a nonlocal excess phase operator improves the accuracy of cyclogenesis localization and timing, a finding further corroborated by ensemble forecasts.

Beyond RO, this research explores the potential of integrating GNSS Reflectometry (GNSS-R) data, which provides sea surface wind speed information to better capture the near-surface dynamical environment during the early stages of cyclogenesis. In a case study of Typhoon Gaemi (2024), RO data assimilation successfully captured the cyclogenesis signal that was missed in experiments without RO. Furthermore, jointly assimilating RO and GNSS-R observations (RO+R) refined the predicted genesis timing compared with RO-based experiments. These findings suggest the potential to use multi-source GNSS observations to improve the precision of tropical cyclogenesis forecasting.