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Coupled modeling of in- and below-cloud wet deposition for atmospheric 137Cs transport following the Fukushima Daiichi accident using WRF-Chem: A self-consistent evaluation of 25 scheme combinations
Environment International ( IF 10.3 ) Pub Date : 2021-09-22 , DOI: 10.1016/j.envint.2021.106882
Sheng Fang 1 , Shuhan Zhuang 1 , Daisuke Goto 2 , Xiaofeng Hu 3 , Li Sheng 4 , Shunxiang Huang 5
Affiliation  

Wet deposition, including both in- and below-cloud scavenging, is critical for the atmospheric transport modeling of 137Cs 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 137Cs transport prediction. To reduce the dual uncertainties, in- and below-cloud wet scavenging schemes of 137Cs 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 137Cs 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.



中文翻译:


使用 WRF-Chem 对福岛第一核电站事故后大气 137Cs 输运的云内和云下湿沉降进行耦合建模:对 25 种方案组合的自洽评估



湿沉降,包括云内和云下清除,对于福岛第一核电站 (FDNPP) 事故后137 Cs 的大气传输模型至关重要。尽管进行了深入研究,湿沉降模拟仍然受到气象输入和湿清除模型的不确定性的影响,导致137 Cs 输运预测存在偏差。为了减少双重不确定性, 137 Cs的云内和云下湿清除方案同时集成到天气研究和预报化学(WRF-Chem)中,产生气象和两个湿清除过程的在线耦合模型。使用 25 种不同云内和云下方案的组合进行集成,涵盖了文献中的大多数方案。还测试了两种微物理方案,以更好地再现降水。使用137 Cs 测量的累积沉积和大气浓度,将 25 个模型和 9 个代表性模型的集合平均值与仅云下 WRF-Chem 模型进行了系统比较。结果表明,利用莫里森的双矩云微物理方案,所开发的模型可以更好地再现降雨并显着改善累积沉积模拟。云内方案对模型行为有影响,考虑云参数的方案也改善了大气浓度模拟,而其他仅依赖于降雨强度的方案对气象敏感。除一次羽流事件外,整体均值取得了令人满意的性能,但仍优于大多数模型。

更新日期:2021-09-23
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