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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - High-Resolution Convective Wet Scavenging Simulations
T2 - A Case Study of the Fukushima Daiichi Nuclear Power Plant Accident
AU - Liu, Nuohang
AU - Ge, Baozhu
AU - Su, Xingtao
AU - Chen, Xueshun
AU - Wild, Oliver
AU - Zhang, Yuanchun
AU - Wang, Zhe
AU - Wang, Zifa
N1 - e2024JD043202 2024JD043202
PY - 2025/8/20
Y1 - 2025/8/20
N2 - 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.
AB - 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.
KW - Convection
KW - Wet deposition
KW - wet scavenging
KW - Caesium 137
KW - Fukushima
KW - Atmospheric modelling
KW - Numerical modelling
U2 - 10.1029/2024JD043202
DO - 10.1029/2024JD043202
M3 - Journal article
VL - 130
JO - Journal of Geophysical Research: Atmospheres
JF - Journal of Geophysical Research: Atmospheres
SN - 0747-7309
IS - 16
M1 - e2024JD043202
ER -