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Shallow convective clouds play a crucial role in Earth's energy budget, as they modulate the radiative transfer in the atmosphere and participate in the vertical transport of aerosols, energy, and humidity. The parameterizations representing these complex, vital players in weather and climate models are mostly based on a description of steady‐state plumes and are a source of major uncertainty. Recently, several studies have shown that buoyant thermals are inherent in atmospheric convection and contain a toroidal (ring) vortex. This work studies those vortices in growing shallow cumulus (Cu) clouds using high‐resolution (10 m) Large Eddy Simulations that resolve these vortices in much detail. Recent analysis of such data showed that small‐scale turbulent diffusion is unable to explain the large diluted portion of the cloud. Here we advocate for the important role of the Cu toroidal vortex (TV) in cloud dilution and present the complex dynamics and structure of a Cu TV. Nevertheless, since the vortex dominates the cloud's dilution, simplicity emerges when considering the cloud's lateral mass flux profile. The cloud mixing is quantified using direct flux calculations and Eulerian tracers. In addition, Lagrangian tracers are used to identify the origin of the entrained air and its thermodynamic properties. It shows that most of the air entrained by the vortex is not recycled by the vortex, yet is significantly more humid than the environment. We suggest that the development of new models describing thermals, together with their toroidal vortices, might improve cloud parameterizations in weather and climate models. Plain Language Summary: Shallow convective clouds play a crucial role in climate as they transfer heat in the vertical dimension and affect radiation transfer in the atmosphere. These clouds are much smaller than climate models' resolution, and so they are represented by simplified equations in weather and climate models (parameterizations). This simple representation of such important processes is one of the largest sources of uncertainty in climate models. In particular, the process of clouds mixing with their dry surroundings is known to have a large contribution to the uncertainty reflected by clouds in climate prediction. In this work, we use high‐resolution simulations of cumulus clouds to investigate the toroidal (ring) vortex that is located at the top of a rising thermal (a known property of cumulus dynamics). We show that cloud‐scale vortices dominate cloud dilution and are at least as important as stochastic turbulent motions which are often considered in mixing parameterizations. These ideas can serve for future parameterizations of shallow cumulus clouds in coarse‐resolution models. Key Points: Coherent and turbulent toroidal (ring) vortices are presented in 10 m resolution LES of shallow cumulus cloudsThe toroidal vortex dominates the cloud's dilution, as shown by the cloud's lateral mass flux profile and Eulerian tracers analysisLagrangian tracers reveal that most entrained air is environmental (not recycled by the vortex) with high relative humidity [ABSTRACT FROM AUTHOR]

Clouds play a key role in Earth's energy budget and water cycle. Their response to global warming contributes the largest uncertainty to climate prediction. Here, by performing an empirical orthogonal function analysis on 42 years of reanalysis data of global cloud coverage, we extract an unambiguous trend and El-Niño–Southern-Oscillation-associated modes. The trend mode translates spatially to decreasing trends in cloud coverage over most continents and increasing trends over the tropical and subtropical oceans. A reduction in near-surface relative humidity can explain the decreasing trends in cloud coverage over land. Our results suggest potential stress on the terrestrial water cycle and changes in the energy partition between land and ocean, all associated with global warming. [ABSTRACT FROM AUTHOR]

Clouds play a key role in Earth's energy budget and water cycle. Their response to global warming contributes the largest uncertainty to climate prediction. Here, by performing an empirical orthogonal function analysis on 42 years of reanalysis data of global cloud coverage, we extract clear trend and ENSO-associated modes. The trend mode translates spatially to a decreasing trend in cloud coverage over most continents and an increasing trend over the tropical and subtropical oceans. A reduction in near-surface relative humidity can explain the decreasing trend in cloud coverage over land. Our results suggest potential stress on the terrestrial water cycle and changes in the energy partition between land and ocean, all associated with global warming. [ABSTRACT FROM AUTHOR]

Shallow convective clouds are important players in Earth's energy budget and hydrological cycle, and are abundant in the tropical and subtropical belts. They greatly contribute to the uncertainty in climate predictions due to their unresolved, complex processes that include coupling between the dynamics and microphysics. Analysis of cloud structure can be simplified by considering cloud motions as a combination of moist adiabatic motions like adiabatic updrafts and turbulent motions leading to deviation from adiabaticity. In this work, we study the sizes and occurrence of adiabatic regions in shallow cumulus clouds during their growth and mature stages, and use the adiabatic fraction (AF) as a continuous metric to describe cloud processes and properties from the core to the edge. To do so, we simulate isolated trade wind cumulus clouds of different sizes using the System of Atmospheric Modeling (SAM) model in high resolution (10 m) with the Hebrew University spectral bin microphysics (SBM). The fine features in the clouds' dynamics and microphysics, including small near-adiabatic volumes and a thin transition zone at the edge of the cloud (∼20–40 m in width), are captured. The AF is shown to be an efficient measure for analyzing cloud properties and key processes determining the droplet-size distribution formation and shape during the cloud evolution. Physical processes governing the properties of droplet size distributions at different cloud regions (e.g., core, edge) are analyzed in relation to AF. Significance Statement: 1) This study investigates the evolution of cumulus clouds (Cu) using a 10-m-resolution LES model with spectral bin microphysics. 2) The study improves the understanding of the mutual effects of adiabatic updrafts and lateral entrainment and mixing. 3) The study demonstrates the existence of an adiabatic core in nonprecipitating Cu. 4) Shapes of the droplet size distributions are closely related to the adiabatic fraction values. 5) Utilization of high resolution reveals the existence of physically significant small features in the cloud structure, such as a narrow cloud interface zone and small adiabatic volumes. [ABSTRACT FROM AUTHOR]