Quantitative Precipitation Estimation Based on S-Band Dual-Polarized Radar Observations over Coastal Eastern China during the Meiyu Season

This study established an S-band dual-polarization radar quantitative precipitation estimation system (NDRQPES) using raindrop size distribution (DSD) data observed during the Meiyu seasons of 2021–2023 in Ningbo, eastern coastal China. The NDRQPES was evaluated by comparing its quantitative precipitation estimation (QPE) accuracy with the national radar mosaic operational product (CHN_QPE) during the Meiyu periods of 2023 and 2024. The results show that NDRQPES, incorporating linear rainfall relationships from localized DSD data, significantly improved hourly precipitation estimate accuracy, with a correlation coefficient (CC) > 0.90 and relative bias (RB) within ±10%. Furthermore, it outperformed CHN_QPE in categorical scores (CSI) across various rainfall rates. However, it exhibited biases in accumulated rainfall estimates, overestimating by 8.89% in 2023 and underestimating by 13.87% in 2024. NDRQPES is also less effective than CHN_QPE in detecting extreme heavy rainfall (> 64 mm h^-1). These discrepancies may be attributed to the microphysical complexity of Meiyu rainfall, including variability in hydrometeor morphology and noise interference in weak rainfall, as well as the limited representativeness of single-point DSD data. While CHN_QPE effectively captures intense precipitation events, it exhibits significant systematic overestimation, with an RB of 161.77% in 2024. This study provides valuable insights for refining and localizing dual-polarization radar precipitation algorithms for regional applications.