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Mechanisms and Model Diversity of Trade-Wind Shallow Cumulus Cloud Feedbacks: A Review

机译:风向浅积云反馈的机制和模型多样性:综述

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摘要

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.
机译:贸易风区域的浅积云是长期以来气候敏感性估计不确定性的核心。在当前的气候模型中,行业中基于云的云量会严重影响云的反馈。因此,了解浅层对流区云基附近云量的关键控制因素已成为研究的重要课题。我们回顾了对这些关键控制因素的物理理解,并基于全局和高分辨率模型实验以及针对各种模型和观察的面向过程的分析,讨论了迄今为止已开发出的不同方法的价值。顺风云的反馈似乎取决于两个重要方面:(1)如何通过湍流,对流和辐射过程之间的局部相互作用来控制云基附近的混浊度; (2)这些过程如何与周围环境相互作用,并受中尺度组织的影响。我们对这些方面进行研究的综合研究表明,模型响应的巨大差异与控制贸易累积量的过程在模型中的运行方式的根本差异有关,尤其是它们是参数化还是已分解。在具有对流参数化的模型中,响应于环境条件的变化,云基附近的云量对对流混合的活力非常敏感。这与高分辨率模型的结果相反,高分辨率模型的结果表明,云基附近的云量几乎随变暖而不变,并且不受大规模环境变化的影响。使用当前的观察结果很难确定不确定性,因为贸易积云的变异性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。讨论了使用大域的观测和高分辨率建模来测试对控制浅积云响应的因素进行物理理解的新机会。

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