Abstract: The performance of the Micro Rain Radar (MRR) in estimating raindrop size distribution (DSD) and integral rainfall parameters (i.e., rainfall intensity R, liquid water content W, radar reflectivity factor Z, mean mass-weighted raindrop diameter Dm and intercept parameter Nw of the normalized gamma distribution) was comprehensively evaluated using coincident data from a 2D video disdrometer (2DVD) and an X-band dual-polarization radar (XPOL) in Beijing during the warm seasons (May-September) from 2016 to 2018. A comparative analysis between the standard MRR products (“AVG” data) and the reprocessed data ("REP") derived from raw MRR spectra was conducted to assess MRR’s accuracy in both stratiform and convective precipitation. Key findings are as follows: (1) The retrieval accuracy of DSD and rainfall parameters for "REP" data outperformed "AVG" data, with superior performance in stratiform rain compared to convective rain. The reflectivity (Z) bias improved from -23.74 dB ("AVG") to 0.74 dB ("REP") in convective precipitation. (2) Compared to 2DVD measurements, "AVG" data systematically underestimated DSD and rainfall parameters, with underestimation increasing with rainfall intensity. In contrast, "REP" data exhibited higher correlation coefficients (Z: 0.96; R: 0.94; W: 0.93; Dm: 0.87; log10Nw: 0.78), lower absolute biases and reduced root mean square errors. (3) Simulations of reflectivity (Z) and differential reflectivity (ZDR) based on "REP" DSD showed better agreement with XPOL observations, with biases of -1.14 dB (vs. -3.04 dB for "AVG") and 0.02 dB (vs. 0.12 dB for "AVG"), respectively. (4) The vertical resolution of MRR significantly influenced retrieval performance. In stratiform rain, MRR-retrieved DSD and rainfall parameters at 30 m, 100 m, and 200 m resolutions shows high consistency with 2DVD measurements. But in convective rain, the optimal agreement occurred at 30 m, while the 200 m resolution performs marginally better than the 100 m resolution. In summary, these results demonstrate that applying de-aliasing and vertical wind correction to MRR raw spectra significantly enhances its capability to retrieve DSD and rainfall parameters in both stratiform and convective precipitation, providing a more reliable technical means for investigating the fine-scale vertical microphysical structure of precipitation.