The parameterization of raindrop size distribution (DSD) is critical for the satellite precipitation retrieval algorithms. Utilizing the multiple ground-based two-dimensional video (2DVD) and Particle Size and Velocity (Parsivel) disdrometers data from the Precipitation Validation Network (Guangdong) of the Fengyun satellites during April–September 2024, this study evaluates the uncertainty of DSD parameterization on a dual-frequency (DF) precipitation retrieval algorithm over South China. It is shown that the composite raindrop spectra generally conform to the gamma distribution, with the shape parameter μ on average of 4.5–4.8, which is higher than the fixed μ = 3 used in the Global Precipitation Measurement mission (GPM) Dual-Frequency Precipitation Radar (DPR) algorithms. By varying the μ value in the DSD gamma model, the effects on the retrieved mass-weighted mean diameter (D_m), normalized intercept parameter (N_w), and rain rate are examined. As μ increases from 1 to 6, the underestimation of D_m shifts to overestimation, while for lgN_w and rain rate, it is the opposite. The overestimation of rainfall, especially at the range of 8–32 mm h⁻¹, mainly comes from underestimated D_m and overestimated lgN_w. On the contrary, overestimation of D_m and underestimation of lgN_w mainly lead to underestimated rainfall, especially when rain rate is above 64 mm h⁻¹. Comprehensive analysis shows that the DSD gamma distribution with μ in the range of 4–5 may be more suitable for South China. These results provide valuable reference for optimizing the DSD module of the precipitation retrieval algorithm for the Fengyun-3G (FY-3G) satellite.

The accuracy of the FY-3G PMR prototype algorithm is evaluated using the data of GPM KuPR. Based on the result, the sensitivity of precipitation rate retrieval to initial relation of $R$- $D_{\mathrm{m}}$, phase, and the correction factor paramNUBF for NUBF is analyzed. Firstly, the $R$- $D_{\mathrm{m}}$ relation of stratiform and convection are adjusted and the DSD profiles, radar reflectivity factor profiles, and precipitation rate profiles are compared. Secondly, sensitivity experiments are conducted to analyze the impact of phase misjudgment on the accuracy of precipitation rate retrieval. Finally, the sensitivity of paramNUBF to precipitation rate retrieval is evaluated by setting different paramNUBF. The results indicate that the FY-3G PMR prototype algorithm is well consistent with GPM KuPR in the retrieval of precipitation structure and intensity distribution, and the relative error is less than 10% while the correlation coefficient is greater than 0.95. The retrievals of radar reflectivity factor profiles and precipitation rate profiles are not sensitive to $R$- $D_{\mathrm{m}}$, but the retrieved DSD profiles are relatively more sensitive to $R$- $D_{\mathrm{m}}$. Misjudgment of phase in the bright band layer, especially between mixed phase state and solid or between mixed phase state and liquid state, affects precipitation rate retrieval near the 0 degree layer but has little impact on ground precipitation rate retrieval. ParamNUBF is a highly sensitive factor, and the greater the difference from the true value, the greater the error of the precipitation rate profile. The sensitivity analysis on spaceborne radar precipitation rate retrieval algorithms can not only deepen our understanding of precipitation rate retrieval theories and methods and improve the accuracy of precipitation rate retrieval, but also provide design ideas for the upcoming field experiments of FY-3G PMR.

By combining the bright band model used in the GPM retrieval algorithm and Mie scattering calculation, the lookup table of scattering functions is generated for three types of precipitation, i.e., solid precipitation, liquid precipitation and mixed phase precipitation. The accuracy of the lookup table is verified by comparing with the measured data of GPM. The result shows that the maximum deviation of scattering calculation is less than 0.5 dB. Based on the lookup table, the frequency correction from spaceborne Ku band radar to S-band radar is completed. The analysis of the scattering function shows that the frequency correction from Ku band to S band depends on the phase and spectral parameter $D_{\mathrm{m}}$. Among them, the frequency correction of liquid precipitation is mainly negative, and the maximum is not more than −3 dB. The frequency correction of mixed phase precipitation varies significantly with the height of the 0℃ bright band. The frequency correction of solid precipitation is positive without a 0℃ bright band. When there is a 0℃ bright band, it changes significantly with temperature. The method proposed in this paper can be used to realize the frequency correction between satellite and ground radars in different bands, and provide effective support for consistency inspection of detection accuracy of spaceborne radar.