首页> 外文期刊>Autonomic neuroscience: basic & clinical >Improved method of visibility parameterization focusing on high humidity and aerosol concentrations during fog-haze events: Application in the GRAPES_CAUCE model in Jing-Jin-Ji, China
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Improved method of visibility parameterization focusing on high humidity and aerosol concentrations during fog-haze events: Application in the GRAPES_CAUCE model in Jing-Jin-Ji, China

机译:雾霾事件高湿度和气溶胶浓度的可见性参数化的改进方法:在京津冀的葡萄_cauce模型中的应用

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摘要

Atmospheric visibility affects people's everyday lives and its simulation accuracy is therefore important, especially in low visibility conditions. Two fog haze pollution episodes (episode 1, 16-21 December 2016 and episode 2, 30 December 2016-7 January 2017) in the Beijing-Tianjin-Hebei (Jing-Jin-Ji) region of China are simulated using the GRAPES_CUACE atmospheric chemistry model. The simulation of low visibility is significantly overestimated by the model. The observational data show that a decrease in visibility is closely related to the increase of the mass concentration of aerosol particles and the increase of the relative humidity. However, the contribution of aerosol particles to extremely low visibility is less than that of the relative humidity. When visibility is 80% or near saturation. High humidity promotes the hygroscopic growth of aerosols, and it also favors the formation of fog droplets. Besides the strongly enhanced aerosol extinction coefficient due to hygroscopic growth at high relative humidity conditions that may be underestimated by the IMPROVE scheme, the further degradation of visibility may also depend on extinction from fog droplets which is absent in the IMPROVE scheme. An improved visibility parameterization focusing on low visibility is proposed based on the IMPROVE equation by including the direct extinction coefficient b(f) of fog droplets in the original parameterization. Focusing on the two fog haze episodes, the simulation results with the improved parameterization show an overall improvement in the simulation of low visibility over the whole Jing-Jin-Ji region. The errors in the simulation of visibility by the improved parameterization averaged over the Jing-Jin-Ji region are reduced by 65%-88% relative to the original parameterization. In addition, the improved parameterization greatly improves the visibility simulation accuracies (VSAs) of 5 km, especially 3 km.
机译:大气的知名度影响人们的日常生活,因此其模拟精度是重要的,特别是在低可见性条件下。两次雾霾污染集(2016年12月16日至2016年12月2日2017年12月30日2017年12月30日)在中国的京津冀(京锦吉)地区正在使用葡萄_案大气化学模拟模型。低可视性的模拟被模型显着高估。观察数据表明,可见性的降低与气溶胶颗粒的质量浓度的增加和相对湿度的增加密切相关。然而,气溶胶颗粒对极低的可视性的贡献小于相对湿度的贡献。当可见性为80%或近饱和时。高湿度促进气溶胶的吸湿生长,并且还有利于雾滴的形成。除了由于改善方案可能低估的高相对湿度条件下的高相对湿度条件下具有吸湿性生长的强烈增强的气雾消光系数,可视性的进一步降低也可能取决于改善方案中不存在的雾滴的灭火。基于通过在原始参数化中的雾滴的直接消光系数B(F)包括改进方程,提出了一种改进的可见性参数化。专注于两个雾霾剧集,具有改进的参数化的仿真结果表明,整体改善了整个景金吉地区的低可视性模拟。通过Jing-Jin-ji区域的改进参数化的可见性模拟的错误,相对于原始参数化减少了65%-88%。此外,改进的参数化大大提高了5公里,尤其是3公里的可见性仿真精度(VSA)。

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