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首页> 外文期刊>Journal of Advances in Modeling Earth Systems >Parametric behaviors of CLUBB in simulations of low clouds in the Community Atmosphere Model (CAM)
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Parametric behaviors of CLUBB in simulations of low clouds in the Community Atmosphere Model (CAM)

机译:CLUBB在社区大气模型(CAM)中模拟低云的参数行为

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In this study, we investigate the sensitivity of simulated low clouds to 14 selected tunable parameters of Cloud Layers Unified By Binormals (CLUBB), a higher?¢????order closure (HOC) scheme, and four parameters of the Zhang?¢????McFarlane (ZM) deep convection scheme in the Community Atmosphere Model version 5 (CAM5). A Quasi?¢????Monte Carlo (QMC) sampling approach is adopted to effectively explore the high?¢????dimensional parameter space and a generalized linear model is applied to study the responses of simulated cloud fields to tunable parameters. Our results show that the variance in simulated low?¢????cloud properties (cloud fraction and liquid water path) can be explained by the selected tunable parameters in two different ways: macrophysics itself and its interaction with microphysics. First, the parameters related to dynamic and thermodynamic turbulent structure and double Gaussian closure are found to be the most influential parameters for simulating low clouds. The spatial distributions of the parameter contributions show clear cloud?¢????regime dependence. Second, because of the coupling between cloud macrophysics and cloud microphysics, the coefficient of the dissipation term in the total water variance equation is influential. This parameter affects the variance of in?¢????cloud cloud water, which further influences microphysical process rates, such as autoconversion, and eventually low?¢????cloud fraction. This study improves understanding of HOC behavior associated with parameter uncertainties and provides valuable insights for the interaction of macrophysics and microphysics.
机译:在这项研究中,我们调查了模拟低云对14个选定的云层的可调整参数的敏感性,该可调整参数由Binormals(CLUBB)统一,具有较高的阶次封闭(HOC)方案,并且具有Zhang的四个参数社区大气模型版本5(CAM5)中的McFarlane(ZM)深对流方案。采用拟蒙特卡罗(QMC)抽样方法有效地探索了高维参数空间,并采用广义线性模型研究了模拟云场对可调参数的响应。我们的结果表明,模拟的低云特性(云分数和液态水路径)的变化可以通过选择的可调参数以两种不同方式来解释:宏观物理学本身及其与微观物理学的相互作用。首先,与动态和热力学湍流结构以及双高斯封闭有关的参数被发现是模拟低云的最有影响力的参数。参数贡献的空间分布显示出清晰的云,政区依赖性。其次,由于云宏观物理学和云微观物理学之间的耦合,总水方差方程中耗散项的系数具有影响力。该参数影响云中云水的方差,这进一步影响了微物理过程速率,例如自动转换,最终影响了云中低云量。这项研究提高了对与参数不确定性相关的HOC行为的理解,并为宏观物理学和微观物理学的相互作用提供了宝贵的见解。

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