Impact of TRITON GNSS-R wind speed assimilation on convective rainfall prediction: a case study of a nearshore rainfall event on April 23, 2024

Abstract

The TRITON satellite, developed by the Taiwan Space Agency (TASA) and launched in October 2023, is equipped with a global navigation satellite system (GNSS) reflectometry receiver and operates in a high-inclination orbit. The ocean surface wind speed (OSW) is retrieved from GNSS signals reflected off the ocean surface. This study examines the impact of assimilating TRITON OSW in addition to radar observations on convective-scale precipitation forecasts, focusing on a nearshore heavy rainfall event on 23 April 2024 characterized by high position uncertainty. Given the track-based sampling of GNSS-R, the TRITON OSW data available for this event fortuitously cover two critical areas, including weak southwesterly flow over the Taiwan Strait and the Meiyu front, northeast of Taiwan. The TRITON OSW assimilation is conducted using a Weather Research and Forecasting (WRF)-based Radar Ensemble Data Assimilation framework on a 4-km analysis grid with a rapid update cycle of 15 min. Despite the limited temporal availability of OSW data, a positive impact on the wind analysis and very short-term forecast is identified. The assimilation of TRITON OSW data effectively corrects low-level wind, successfully complementing ground-based radar data where near-surface observations are unavailable. Consequently, the weak winds over the Taiwan Strait and offshore southwestern Taiwan, as well as the strong, front-associated winds northeast of Taiwan can be better represented. The OSW assimilation also enhances moisture in the southwestern offshore region. These adjustments yield more accurate prediction for the intensity and location of linear-type nearshore heavy rainfall systems. The improvement stems from enhanced convergence within and above the planetary boundary layer, as well as greater convective instability. Furthermore, the incremental assimilation of TRITON OSW observations with successive cycles provides the possibility of increasing the value of the TRITON OSW, given its dense distribution along a sequence of specular points. This study serves as an initial case-specific evaluation exploring the dynamic mechanisms through which TRITON OSW data can complement the radar assimilation framework and improve nearshore convective representation.