Abstract: The strong cold pool is pivotal in the genesis of severe gales associated with squall lines, and its intensity simulation is closely related to parameter settings of cloud microphysical and boundary layer processes in the model. Despite parameter uncertainties, it remains challenging to apply reasonable parameter perturbations to squall line systems. To improve the performance of convective-scale numerical models in the forecast of squall line systems, based on the WRF (The Weather Research and Forecasting Model) model, five key parameters are selected from the cloud microphysical process and the boundary layer process to carry out sensitivity tests for the weak simulation of the cold pool associated with squall lines. Subsequently, the joint perturbation of the sensitive parameters is carried out, and the influence of this method on the simulation of a squall line process in Jiangsu is discussed. The results indicate that adjusting parameters that influence evaporation can significantly affect the estimation of the cold pool. Specifically, the parameter CONSTB, which reflects the impact of raindrop size on its terminal velocity, and the parameter VF1R, which accounts for the influence of surrounding airflow on raindrop behavior, exhibit the highest sensitivity to the cold pool dynamics. In the single-parameter and multi-parameter combined perturbation experiments, the simulated 2 m temperature in the cold zone of the squall line is 1—2℃ lower than that of the control experiment, which effectively overcomes the problem of weak simulation of the cold pool. In addition, the joint perturbation of CONSTB and VF1R parameters has a notable positive impact on forecast accuracy, with the simulated 10 m maximum wind speed being the most accurate in comparison to actual observations. Results show that the multi-parameter joint perturbation method for squall line cold pools effectively captures the uncertainty of parameters within physical parameterization schemes and improves cold pool simulation, thereby enhancing the accuracy of squall line gale predictions.