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A Method for Forecasting Cloud Condensation Nuclei Using Predictions of Aerosol Physical and Chemical Properties from WRF/Chem

机译:WRF / Chem预测气溶胶理化性质的云凝结核预报方法

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Model investigations of aerosol-cloud interactions across spatial scales are necessary to advance basic understanding of aerosol impacts on climate and the hydrological cycle. Yet these interactions are complex, involving numerous physical and chemical processes. Models capable of combining aerosol dynamics and chemistry with detailed cloud microphysics are recent developments. In this study, predictions of aerosol characteristics from the Weather Research and Forecasting Model with Chemistry (WRF/Chem) are integrated into the Regional Atmospheric Modeling System microphysics package to form the basis of a coupled model that is capable of predicting the evolution of atmospheric aerosols from gas-phase emissions to droplet activation. The new integrated system is evaluated against measurements of cloud condensation nuclei (CCN) from a land-based field campaign and an aircraft-based field campaign in Colorado. The model results show the ability to capture vertical variations in CCN number concentration within an anthropogenic pollution plume. In a remote continental location the model-forecast CCN number concentration exhibits a positive bias that is attributable in part to an overprediction of the aerosol hygroscopicity that results from an underprediction in the organic aerosol mass fraction. In general, the new system for predicting CCN from forecast aerosol fields improves on the existing scheme in which aerosol quantities were user prescribed.
机译:为了进一步了解气溶胶对气候和水文循环的影响,有必要进行跨空间尺度的气溶胶-云相互作用的模型研究。然而,这些相互作用是复杂的,涉及许多物理和化学过程。能够将气溶胶动力学和化学与详细的云微观物理学相结合的模型是最近的发展。在这项研究中,将来自天气研究和化学预测模型(WRF / Chem)的气溶胶特征预测集成到区域大气建模系统微物理学软件包中,以形成能够预测大气气溶胶演变的耦合模型的基础。从气相排放到液滴活化。根据科罗拉多州陆上野战和飞机野战的云凝结核(CCN)测量结果对新的集成系统进行了评估。模型结果表明,能够捕获人为污染羽流中CCN数浓度的垂直变化。在偏远的大陆位置,模型预测的CCN数浓度表现出正偏差,这部分归因于对有机气溶胶质量分数预测不足而导致的对气溶胶吸湿性的过高预测。总的来说,用于从预测的气溶胶场中预测CCN的新系统对用户指定气溶胶量的现有方案进行了改进。

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