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

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 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.