High‐Resolution Convective Wet Scavenging Simulations: A Case Study of the Fukushima Daiichi Nuclear Power Plant Accident

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 137 Cs, 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 46%–48% increase in total deposition in the Tokyo Metropolitan Area. The results show that dynamic conditions critically influence wet scavenging and that replenishment of convective transport is necessary to simulate high‐resolution convective wet scavenging using offline CTMs.