The Impact of Assimilating X‐Band Phased Array and S‐Band Radar Data on the Forecast of Tropical Cyclone Saola (2023)

Abstract X‐band phased array radar (XPAR), a promising new instrument to detect fine structure of severe weather conditions, has recently been deployed at numerous locations across China. However, the impacts of assimilating its observations on tropical cyclones (TCs) remain unclear. This study investigates these effects of assimilating XPAR radial wind velocity observations, both alone and in combination with S‐band Doppler radar radial winds, for TC Saola (2023). Compared with experiments assimilating only S‐band Doppler radar data, assimilating data from a single XPAR significantly reduces TC intensity errors by up to 6.4 m/s and improves structural representation in the inner‐core region, as well as demonstrates optimal enhancement in forecast skill for 9‐hr accumulated rainfall exceeding 100 mm threshold. Furthermore, higher‐frequency XPAR data assimilation yields additional improvements in intensity and inner‐core structure forecasting skills, albeit with increased computational demands. Joint assimilation of S‐band Doppler radar and XPAR data demonstrates superior performance over solely assimilating XPAR observations, achieving maximum intensity error reduction of 8.0 m/s, more realistic structural representation of both inner‐core features and outer rainbands, and optimal improvement for 50–100 mm rainfall forecasts. These improvements stem from XPAR's enhanced observational capacity of the TC's lower‐layer inner‐core, which strengthens lower‐layer inflow, and further demonstrates its potential to improve forecast accuracy of TCs.