[论文解读] Stratocumulus over SouthEast Pacific: Idealized 2D simulations with the Lagrangian Cloud Model

Mirosław Andrejczuk, Alan Gadian+1 more|arXiv (Cornell University)|Nov 1, 2012

Climate variability and models参考文献 23被引用 3

一句话总结

本研究基于VOCALS观测，采用二维理想化设置的拉格朗日云模型（LCM）模拟东南太平洋层积云。该模型成功再现了液态水混合比和云滴数浓度等关键云特性，并捕捉到观测到的气溶胶-云滴关系，尽管其对大云滴浓度的估算偏低，且对微物理参数化方案的选择较为敏感。

ABSTRACT

In this paper a LES model with Lagrangian representation of microphysics is used to simulate stratucumulus clouds in idealized 2D set-up based on the VOCALS observations. The general features of the cloud simulated by the model, such as cloud water mixing ratio and cloud droplet number profile agree well with the observations. The model can capture observed relation between aerosol distribution and concentration measured below the cloud and cloud droplet number. Averaged over the whole cloud droplet spectrum from the numerical model and observed droplet spectrum are similar, with the observations showing a higher concentration of droplets bigger than 25 μm. Much bigger differences are present when comparing modelled and observed droplet spectrum on specific model level. Despite the fact that microphysics is formulated in a Lagrangian framework the standard deviation of the cloud droplet distribution is larger than 1 μm. There is no significant narrowing of the cloud droplet distribution in the up-drafts, but the distribution in the up-drafts is narrower than in the down-drafts. Modelled and observed standard deviation profiles agree well with observations for moderate/high cloud droplet numbers, with much narrower than observed droplet spectrum for low droplet number. Model results show that a significant percentage of droplets containing aerosol bigger than 0.3 μm didn't reach activation radius, yet exceeding 1 μm, what is typically measured as a cloud droplets. Also, the relationship between aerosol sizes and cloud droplet sizes is complex; there is a broad range of possible cloud droplet sizes for a given aerosol size.

研究动机与目标

• 将拉格朗日云模型（LCM）与东南太平洋层积云的真实VOCALS观测进行验证。
• 评估模型再现气溶胶粒径、云滴数浓度与云滴谱之间观测关系的能力。
• 研究LCM框架中数值参数对微物理与动力云特性的影响敏感性。
• 探讨拉格朗日方法在表征云滴谱展宽与活化过程方面的优势与局限性。

提出的方法

• LCM追踪数百万个代表气溶胶与云滴的拉格朗日质点，每个质点具有相同的化学与物理特性。
• 在拉格朗日框架中模拟微物理过程（包括凝结增长、活化、非活化及碰并-合并），并将其与欧拉动力学和热力学过程相耦合。
• 采用基于分档的云滴与气溶胶粒径分布表示方法，通过网格映射提高碰并事件的计算效率。
• 通过改变质点数量、分档分辨率、碰并频率及阈值参数等开展敏感性测试，以评估数值鲁棒性。
• 将模型输出与VOCALS实测的云水混合比、云滴数浓度及云滴谱进行对比。

实验结果

研究问题

• RQ1 拉格朗日云模型能否准确模拟观测到的层积云特性，如液态水混合比与云滴数浓度？
• RQ2 模型在多大程度上再现了云层下方气溶胶浓度与云滴数浓度之间的观测关系？
• RQ3 模型在多大程度上捕捉到观测到的云滴谱，特别是粒径大于25 µm的云滴浓度？
• RQ4 模型结果对数值参数（如质点数量、分档分辨率与碰并频率）的敏感性如何？
• RQ5 拉格朗日微物理过程在塑造云滴谱展宽方面起什么作用，特别是在上升气流与下沉气流中？

主要发现

• 模型对观测到的云水混合比与云滴数浓度廓线有良好再现，整体云特性匹配度高。
• 观测到的云滴谱中，粒径大于25 µm的云滴浓度高于模型模拟结果，表明大云滴形成过程被低估。
• 模型中云滴谱的标准差大于1 µm，且上升气流中未出现显著的谱形变窄现象，尽管上升气流中的云滴谱仍比下沉气流更窄。
• 在低云滴数条件下，模型生成的云滴谱比观测更窄，表明在云凝结核（CCN）浓度较低时，对谱形展宽的表征存在局限。
• 大量粒径大于0.3 µm的气溶胶粒子虽未成功活化，却仍能增长至超过1 µm，导致在观测中被误判为云滴。
• 对于给定气溶胶粒径，模型显示出广泛的云滴尺寸分布，凸显气溶胶与云滴尺寸之间复杂且非线性的关系。