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Relative Contributions of Aerosol Properties to Cloud Droplet Number: Adjoint Sensitivity Approach in a GCM

机译:气溶胶属性对云液滴数的相对贡献:GCM中的伴随敏感性方法

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In this work we study the sensitivity of cloud droplet number concentration to aerosol characteristics in the framework of a Global Circulation Model (GCM) by using the newly developed adjoints of a number of physically based droplet activation parameterizations. The adjoint sensitivities of these activation parameterizations were implemented in the Community Atmospheric Model version 5, which includes interactive aerosols and detailed cloud microphysics. These simulations exhibit clear patterns of high-sensitivity areas to aerosol number concentration coinciding with relatively clean environments, as well as continental and relatively polluted areas showing saturation with respect to aerosol load changes. Furthermore, in order to identify process-level discrepancies between the activation schemes in the absence of feedbacks, aerosol input fields from the GlobalModeling Initiative (GMI) chemical transport model were used to drive off-line comparisons between the sensitivities of the droplet number predicted by these parameterizations against predictions with detailed numerical simulations of the activation process. Important differences were observed particularly in their response to number concentration and hygroscopicity of fine and coarse mode aerosols. Overall, the parameterizations were capable of capturing the response of droplet concentrations to perturbations in aerosol number concentration, and updraft velocity better than to chemical composition variations.
机译:在这项工作中,我们研究云滴数浓度的气溶胶特性在全球环流模型(GCM)的框架内通过使用一些基于物理的液滴激活参数化的新开发的伴随矩阵的敏感性。这些激活参数化的伴随灵敏度在社区大气模型版本5,其包括交互式气雾剂和详述云微得到实施。这些模拟显示出高灵敏度的区域的图案清晰气溶胶数浓度与相对干净的环境中,以及表示相对于气溶胶负载变化饱和大陆和相对污染区重合。另外,为了识别在没有反馈的激活方案之间进程级的差异,从GlobalModeling倡议(GMI)化学输送模式气溶胶输入字段被用于将液滴数的由所预测的灵敏度之间驱除行比较这些参数化针对经活化处理的详细数值模拟预测。重要的区别是在其数目浓度和优良的吸湿性和粗略模式气溶胶响应特别观察到。总体而言,参数化是能够捕获液滴的浓度,以扰动气溶胶数浓度的响应,和上升气流的速度比的化学组成的变化更好。

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