Wet deposition, including both in- and below-cloud scavenging, is critical for the atmospheric transport modeling of Cs following the Fukushima Daiichi Nuclear power plant (FDNPP) accident. Although intensively investigated, wet deposition simulation is still subject to uncertainties of meteorological inputs and wet scavenging modeling, leading to biased Cs transport prediction. To reduce the dual uncertainties, in- and below-cloud wet scavenging schemes of Cs were simultaneously integrated into Weather Research and Forecasting-Chemistry (WRF-Chem), yielding online coupled modeling of meteorology and the two wet scavenging processes. The integration was performed using 25 combinations of different in- and below-cloud schemes, covering most schemes in the literature. Two microphysics schemes were also tested to better reproduce the precipitation. The 25 models and the ensemble mean of 9 representative models were systematically compared with the below-cloud-only WRF-Chem model, using the cumulative deposition and atmospheric concentrations of Cs measurements. The results reveal that, with the Morrison's double moment cloud microphysics scheme, the developed models could better reproduce the rainfall and substantially improve the cumulative deposition simulation. The in-cloud scheme is influential to the model behaviors and those schemes considering cloud parameters also improve the atmospheric concentration simulations, whereas the others solely dependent on the rain intensity are sensitive to meteorology. The ensemble mean achieves satisfactory performance except one plume event, but still outperforms most models.

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http://dx.doi.org/10.1016/j.envint.2021.106882DOI Listing

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