The dispersion of cloud droplet spectral dispersion is an important parameter that cannot be ignored in the parameterization of autoconversion, and has an important influence on surface precipitation. In this study, the weather research and forecast coupled with chemistry (WRF-Chem) model was used to simulate a precipitation process in the middle and lower reaches of the Yangtze River from January 3, 2019, to January 6, 2019. Different values of cloud droplet spectral dispersion (0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0) were set to study the microphysical changes of cloud and precipitation under the clean and polluted backgrounds. The results show that the precipitation in this case mainly comes from the autoconversion from cloud droplets to rain and the accretion of cloud droplets by rain. The accumulated precipitation under the clean condition is greater than that under the polluted condition because the concentration of cloud droplets is smaller under the clean condition, which is beneficial to autoconversion and accretion. Although the autoconversion and accretion are dominant during precipitation processes, the main reasons leading to the increase of accumulated precipitation with the increase of cloud droplet spectral dispersion are as follows: With the increase of cloud droplet spectral dispersion, the mass concentration of ice particles increases, which leads to the enhancement of melting process and more raindrops, thus enhancing surface precipitation. The results will improve the theoretical understanding of the response of cloud and precipitation process to aerosol and cloud droplet spectral dispersion.