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This study systematically investigates the microphysical characteristics of warm-season precipitation over northern Zhejiang Province, China, based on comprehensive observations from six laser precipitation monitors (LPMs) and two S-band dual-polarisation weather radars (HZ-SPOL and JX-SPOL) collected between March and October 2022. In addition, the performance of dual-polarisation radar retrievals of raindrop size distribution (DSD) parameters, specifically the mass-weighted mean diameter (D₀) and the normalised intercept parameter (N_w) of the gamma distribution, is quantitatively evaluated. The results reveal the following: (1) Precipitation in the northern Zhejiang region is predominantly characterised by high concentrations of small raindrops, with an average D₀ of 1.0 mm and a mean N_w of 10^4.3m^-3·mm^-1, exhibiting typical features of warm-cloud precipitation. A classification approach based on the statistical properties (mean and standard deviation) of rainfall rate effectively discriminates between stratiform and convective precipitation. Stratiform precipitation shows relatively narrow DSDs and low spatial variability across sites, with low rainfall intensity (R<10 mm·h^-1) and smaller drop sizes (D₀ <1.0 mm). In contrast, convective precipitation exhibits significantly broader spectra, with D₀ and average R values reaching up to 1.8 mm and 19 mm·h^-1, respectively, and displays much greater spatial heterogeneity. Medium-sized raindrops (1.0-2.0 mm) contribute the largest fraction (33.4%) to total rainfall accumulation, while larger drops (D₀ >2.5 mm), though relatively infrequent, still account for 10.3% of total rainfall volume. (2) Simulated polarimetric variables at S-band—reflectivity (Z), differential reflectivity (Z_DR), and specific differential phase (K_dp)—calculated using a T-matrix scattering model based on local DSDs, show good agreement with actual radar observations, validating the applicability and robustness of the scattering model in the region. Retrieval relationships for D₀ and N_w are established using the localised DSD dataset. Sensitivity analysis indicates that D₀ is primarily influenced by Z_DR, with a negligible bias of -0.005 mm, while N_w is influenced by both Z and Z_DR and exhibits larger variability, with a mean bias of 0.029 m^-3·mm^-1. (3) Validation is carried out using six precipitation events observed at Changxing in 2023, comparing retrievals from two radars: Jiaxing (JX-SPOL) and Hangzhou (HZ-SPOL). The JX-SPOL retrievals of D₀ show better agreement with LPM measurements, with a mean bias of 0.087 mm and RMSE of 0.418 mm, outperforming HZ-SPOL (bias -0.195 mm, RMSE 0.444 mm). For N_w, JX-SPOL yields a higher correlation coefficient (0.536) compared to HZ-SPOL (0.199), and the absolute deviation and RMSE (HZ-SPOL 1.046 m^-3·mm^-1 and JX-SPOL 0.819 m^-3·mm^-1) are relatively close, although systematic biases remain: JX-SPOL tends to underestimate by 0.395 m^-3·mm^-1, whereas HZ-SPOL overestimates by 0.494 m^-3·mm^-1. Overall, this study provides a scientific basis for improving dual-polarisation radar retrievals of precipitation microphysics in Zhejiang Province. The findings highlight the importance of localised DSD datasets in optimising retrieval algorithms and emphasise the need for further validation efforts using diverse precipitation events and multi-site observations to enhance the accuracy, stability, and generalisability of radar-based microphysical retrieval techniques.