Abstract Convective precipitation is a key factor for diagnosing convective clouds and the subsequent modeling of the wet scavenging of air pollutants in offline chemical transport models (CTMs). However, a discrepancy exists between the Weather Research and Forecasting model, which uses resolved convection, and CTMs, which rely on a diagnostic convective cloud scheme, in handling high-resolution convective wet scavenging simulations. To explore the uncertainties arising from this disparity, this study focuses on 137Cs, released during the Fukushima Daiichi Nuclear Power Plant accident, as a species with numerous observations compared to other radionuclides and minimal interference from other factors using the NAQPMS model incorporating a physically-based wet deposition module. A diagnostic convective cloud scheme was applied, using a radar composite reflectivity factor (RCRF) of 35 dBZ to identify convective precipitation. Implementing the RCRF diagnosis scheme significantly improved model performance by increasing in-cloud deposition. This enhancement led to a 4648resolution convective wet scavenging using offline CTMs.