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Diagnosis of an underestimation of summertime sulfate using the Community Multiscale Air Quality model

机译:使用社区多尺度空气质量模型诊断夏季硫酸盐偏低

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We evaluate the simulations of SO_2 and sulfate using the Community Multiscale Air Quality model (CMAQ) version 4.6 with the observations over the United States in 2002. MM5 was used for meteorological simulations. While the general seasonal cycles of SO_2 and sulfate are simulated well by the model, we find significant systematic biases in the summer. The model low bias in sulfate is considerably more severe than the model bias in SO_2. Both ACM and RADM schemes are used in the model to test the sensitivities of simulated sulfate to cloud processing. We carry out detailed modeling analysis and diagnostics for July 2002. Compared to satellite observations of cloud liquid water path, CMAQ cloud modules greatly overestimates convective (sub-grid) precipitating clouds, leading to large over-estimation of sulfate wet scavenging. Limiting convective precipitating cloud fraction in the cloud modules to <10% and hence significantly reducing wet scavenging lead to much improved agreement between simulated and observed sulfate. The average lifetime of sulfate in the model increases from 1 -2 days to 3-4 days for July. We show that a potential model problem of excessive wet scavenging of sulfate does not necessarily lead to apparent problems in model simulations of sulfate wet deposition rate compared to surface observations. In general, there is still a lack of direct observational constraints from air quality monitoring measurements on model simulated cloud processing of SO_2 and sulfate.
机译:我们使用社区多尺度空气质量模型(CMAQ)4.6版评估了SO_2和硫酸盐的模拟,并于2002年在美国进行了观测。MM5用于气象模拟。虽然该模型很好地模拟了SO_2和硫酸盐的一般季节周期,但我们发现夏季存在明显的系统偏差。硫酸盐的模型低偏差比SO_2中的模型偏差严重得多。模型中同时使用了ACM和RADM方案,以测试模拟硫酸盐对云处理的敏感性。我们对2002年7月进行了详细的建模分析和诊断。与卫星对云水路径的观测相比,CMAQ云模块极大地高估了对流(子网格)降水云,从而导致对硫酸盐湿扫除的大量高估。将对流降水云模块中的对流降水云比例限制为<10%,从而显着减少湿气清除率,可以大大改善模拟硫酸盐和观察到的硫酸盐之间的一致性。模型中硫酸盐的平均寿命从7月的1 -2天增加到3-4天。我们表明,与表面观测相比,过度湿清除硫酸盐的潜在模型问题并不一定会导致硫酸盐湿沉积速率模型模拟中的明显问题。通常,在对SO_2和硫酸盐的模拟云计算进行空气质量监测测量时,仍然缺乏直接的观测约束。

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