In this study, the effects of different nesting methods on simulating a flash‐flood‐producing severe convective event over Cheongju, South Korea on July 16, 2017 was examined. This event developed as part of a mesoscale convective system (MCS) accompanied by frontal forcing. Numerical experiments were conducted using the Weather Research and Forecasting model (WRF) employing one‐way concurrent (OWC), one‐way sequential (OWS), and two‐way (TW) nesting approaches with advanced physics options from Korean Integrated Model (KIM). Analysis of model simulations against Tropical Rainfall Measuring Mission (TRMM) and Automatic Weather Station (AWS) observations suggests that the TW nesting method performs better than both OW nesting methods in simulating rainfall. Large‐scale features, moisture, instability in the boundary layer, and the vertical distribution of meteorological parameters favorable for convection are better represented by TW nesting. Probability distribution Function (PDF) analysis from AWS/WRF reveals that the local‐scale distribution of surface meteorological parameters which affect storm intensity were well captured using TW. Further assessment of Equitable Threat score (ETS) also showed better precipitation forecast skill over different thresholds in TW. Vertical velocity in the innermost domain simulated using TW nesting is more consistent with ERA5 reanalysis. An additional MCS (11–13 July 2006) simulated using a similar numerical setup also benefited from TW nesting, increasing confidence in the initial findings. Along with frequent lateral boundary conditions, TW nesting allows multi‐scale interactions between parent and nested domains and improves the representation of both synoptic and local‐scale features, enhanced cloud hydrometeor, vertical velocity distributions, and subsequent rainfall.