<b>Nowcasting of a Warm-sector Rainfall Event in Southern China with the TRAMS Model: Sensitivity to Different Radar Reflectivity Retrieval Methods and Incremental Updating Strategies</b>

To improve the radar data assimilation scheme for the high-resolution TRAMS (Tropical Regional Atmospheric Model System) model, this study investigates the sensitivity of simulating a warm-sector rainfall event in southern China to different radar reflectivity retrieval methods and incremental updating strategies. It was found that the ICR (Ice Cloud Retrieval) method provides more reasonable cloud hydrometeors. But the impact of different retrieval methods is minimal without dynamic field being adjusted correspondingly. By further assimilating the wind field, the overestimated south winds were effectively reduced and the observed low-level convergence in the north Guangdong was successfully simulated, playing a substantial role in improving the precipitation forecast. Both IAU (Incremental Analysis Update) and Nudging methods were able to adjust the forecast to better match the observations, with IAU showing slightly better adjustment effects than Nudging. These findings are beneficial for further improving the forecast accuracy of precipitation intensity. Extending the IAU relaxation time from 4 to 10 minutes has almost no impact on the actual forecasting. However, by adjusting the time-dependent distribution of IAU weighting factors to prioritize the correction of the wind field, it is possible to avoid the impact of cloud particle adjustments on the effectiveness of dynamic field adjustments. This allows for more realistic low-level wind convergence and precipitation forecasts to be obtained. As a whole, the ICR method for retrieving cloud hydrometeors, combined with the IAU method using time-dependent distribution weighting factors appears to be a more suitable option for the radar data assimilation scheme in TRAMS model.