Shallow cumulus clouds in the trade-wind regions are at the heart of the long standing uncertainty in climate sensitivity estimates. In current climate models, cloud feedbacks are strongly influenced by cloud-base cloud amount in the trades. Therefore, understanding the key factors controlling cloudiness near cloud-base in shallow convective regimes has emerged as an important topic of investigation. We review physical understanding of these key controlling factors and discuss the value of the different approaches that have been developed so far, based on global and high-resolution model experimentations and process-oriented analyses across a range of models and for observations. The trade-wind cloud feedbacks appear to depend on two important aspects: (1) how cloudiness near cloud-base is controlled by the local interplay between turbulent, convective and radiative processes; (2) how these processes interact with their surrounding environment and are influenced by mesoscale organization. Our synthesis of studies that have explored these aspects suggests that the large diversity of model responses is related to fundamental differences in how the processes controlling trade cumulus operate in models, notably, whether they are parameterized or resolved. In models with parameterized convection, cloudiness near cloud-base is very sensitive to the vigor of convective mixing in response to changes in environmental conditions. This is in contrast with results from high-resolution models, which suggest that cloudiness near cloud-base is nearly invariant with warming and independent of large-scale environmental changes. Uncertainties are difficult to narrow using current observations, as the trade cumulus variability and its relation to large-scale environmental factors strongly depend on the time and/or spatial scales at which the mechanisms are evaluated. New opportunities for testing physical understanding of the factors controlling shallow cumulus cloud responses using observations and high-resolution modeling on large domains are discussed.

中文翻译：

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信风浅积云反馈的机制和模型多样性：综述


信风地区的浅层积云是气候敏感性估计长期存在的不确定性的核心。在当前的气候模型中，云反馈受到行业中云基云量的强烈影响。因此，了解控制浅对流区域云底附近云量的关键因素已成为一个重要的研究课题。我们回顾了对这些关键控制因素的物理理解，并讨论了迄今为止开发的不同方法的价值，这些方法基于全局和高分辨率模型实验以及跨一系列模型和观测的面向过程的分析。信风云反馈似乎取决于两个重要方面：（1）云底附近的云量如何受到湍流、对流和辐射过程之间局部相互作用的控制； （2）这些过程如何与周围环境相互作用并受到中尺度组织的影响。我们对这些方面的研究的综合表明，模型响应的巨大多样性与控制贸易积云的过程如何在模型中运行的根本差异有关，特别是它们是参数化的还是解析的。在参数化对流模型中，云底附近的云量对响应环境条件变化的对流混合强度非常敏感。这与高分辨率模型的结果形成鲜明对比，高分辨率模型表明云底附近的云量几乎不随变暖而变化，并且与大规模环境变化无关。 使用当前的观测结果很难缩小不确定性，因为贸易积云的变化及其与大规模环境因素的关系在很大程度上取决于评估机制的时间和/或空间尺度。讨论了使用大域观测和高分辨率建模来测试对控制浅积云响应因素的物理理解的新机会。