Abstract: Currently, the impact of environmental field errors on the simulation effect is hardly considered in seeding models, and uncertain conclusions are often drawn. Therefore, in this study, the ensemble forecast model by initial field perturbation is one-way coupled with the columnar cloud model and AgI seeding scheme. The cloud model is driven in real time using multiple sets of thermal and microphysical profiles provided by the mesoscale model, which comprise the environmental field disturbance error. The multimember, single grid/multigrid AgI seeding numerical experiments are conducted to simulate the precipitation process of convective-stratiform mixed clouds in Zhejiang Province on January 23, 2022, to establish the optimal seeding scheme and the probability distribution of the seeding effect. Results revealed that, from the simulation effect of a single station (Hangzhou station), all members of ensemble forecast can realize positive precipitation enhancement when the amounts of AgI used at a height of 3.6 km (−5.2°C) are 1.2×10⁻⁷ to 1.2×10⁻⁴ g kg⁻¹ at 1500 UTC on January 23, in which the precipitation enhancement is the largest at an amount of AgI of 1.2×10⁻⁵g kg⁻¹, with a mean value of 4.67% and the 99% quantile of 7.77%. In the single point simulation, the initial field disturbance has a great effect on concluding whether excessive seeding leads to precipitation reduction, e.g., when the amount of AgI is increased to 1.2×10⁻² g kg⁻¹, more than 50% of the ensemble members exhibit the effect of precipitation reduction, but some members still display the effect of enhancement. Multiple grid sensitive experiments indicate that it should be seeded in the northwest and north of Zhejiang, particularly in the northeast of Jiaxing and near the Lin’an area from the perspective of the optimal probability of the seeding effect. Moreover, these regions correspond to relatively high average supercooled water content and low average ice crystal number concentration.