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Understanding Cloud Droplet Spectral Dispersion Effect Using Empirical and Semi‐Analytical Parameterizations in NCAR CAM5.3

机译:了解使用NCAR CAM53中的经验和半分析参数化云液滴谱色散效果

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Five parameterizations of cloud droplet spectral shape are implemented in a global climate model to investigate the dispersion effect and aerosol indirect effect (AIE). We design a series of experiments by modifying the microphysical cloud scheme of NCAR CAM5.3 (National Center for Atmospheric Research Community Atmosphere Model Version 5.3). We employ four empirical (Martin94, RLiu03, PengL03, and Liu08) and one semi‐analytical (LiuLi15) expressions for cloud droplet spectral shape parameters. Analysis focuses on the instantaneous differences in the simulated cloud microphysical properties and the comparison between model output and satellite data. The results show that RLiu03, PengL03, and LiuLi15 produce wider droplet spectrum and faster autoconversion rate, but Liu08 has a narrower droplet spectrum and slower autoconversion rate than the default parameterization (Martin94) in CAM5.3. Global dispersion effects caused by the five parameterizations modify the aerosol indirect effect by ?10% (counteract) to 13% (strengthen). The simulated AIEs and dispersion effects exhibit noticeably spatial inhomogeneity. In the sensitive regions of AIE (Southeast Asia, North Pacific, and West Coast of South America), we decompose the response of shortwave cloud forcing to the change in droplet number for analysis. The varying dispersion effects can be explained by different responses of cloud properties in different spectral parameterizations. Plain Language Summary Increase of air pollution modifies the water cloud droplet size spectrum and further impacts on cloud physical properties, precipitation, and energy budget in atmosphere. We applied four empirical and one semi‐analytical schemes for calculating cloud droplet spectral shape parameters in a global climate model. The five spectral schemes have different impacts on cloud physical properties but have limited effects on global atmospheric energy and on total precipitation. The model simulated changes in cloud properties and in atmospheric energy are analyzed in detail, helping to understand the physical mechanism of the five spectral schemes.
机译:在全球气候模型中实施了云液滴谱形状的五个参数化,以研究分散效应和气溶胶间接效应(AIE)。我们通过修改NCAR CAM5.3的微物理云方案(国家大气研究社区氛围5.3版5.3版)设计了一系列实验。我们使用四个经验(Martin94,RLIU03,Pengl03和Liu08)和一个半分析(Liuli15)表达式,用于云液滴光谱形状参数。分析侧重于模拟云微物理特性的瞬时差异以及模型输出和卫星数据之间的比较。结果表明,RLIU03,PENGL03和Liuli15产生更广泛的液滴谱和更快的自电化转换率,但Liu08具有较窄的液滴频谱和比CAM5.3中的默认参数化(Martin94)更窄的自电电压率。由五个参数化引起的全局分散效应通过α0%(抵消)改变气溶胶间接效应至13%(加强)。模拟的AIE和色散效果表现出明显的空间不均匀性。在AIE(东南亚,北太平洋和南美洲西海岸)的敏感地区,我们分解了短波云强迫对分析液滴数变化的响应。可以通过在不同光谱参数化中的不同响应来解释不同的色散效果。简单的语言摘要增加空气污染的增加改变了水云液滴尺寸谱,进一步影响了大气中的云物理性质,降水和能源预算。我们应用了四种经验和一个半分析方案来计算全球气候模型中的云液滴谱形状参数。五种光谱方案对云物理性质产生不同的影响,但对全球大气能量和总降水有有限的影响。详细分析了云属性和大气能量的模拟变化,有助于了解五种光谱方案的物理机制。

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