The Diurnal Path to Persistent Convective Self-Aggregation

Clustering of tropical thunderstorms constitutes an important climate feedback because it influences the radiative balance. Convective self-aggregation (CSA) is a profound modeling paradigm for explaining the clustering of tropical oceanic thunderstorms. However, CSA is hampered in the realistic limit of fine model resolution when cold pools-dense air masses beneath thunderstorm clouds-are well-resolved. Studies on CSA usually assume the surface temperature to be constant, despite realistic surface temperatures varying significantly between night and day. Here we mimic the diurnal cycle in cloud-resolving numerical experiments by prescribing a surface temperature oscillation. Our simulations show that the diurnal cycle enables CSA at fine resolutions, and that the process is even accelerated by finer resolutions. We attribute these findings to vigorous combined cold pools emerging in symbiosis with mesoscale convective systems. Such cold pools suppress buoyancy in extended regions (∼100 km) and enable the formation of persistent dry patches. Our findings help clarify how the tropical cloud field forms sustained clusters under the diurnal forcing and may have implications for the origin of extreme thunderstorm rainfall and tropical cyclones.

Significant Amplification of Instantaneous Extreme Precipitation With Convective Self-Aggregation

This work explores the effect of convective self-aggregation on extreme rainfall intensities through an analysis at several stages of the cloud lifecycle. In addition to increases in 3-hourly extremes consistent with previous studies, we find that instantaneous rainrates increase significantly (+30%). We mainly focus on instantaneous extremes and, using a recent framework, relate their increase to increased precipitation efficiency: the local increase in relative humidity drives larger accretion efficiency and lower re-evaporation. An in-depth analysis based on an adapted scaling for precipitation extremes reveals that the dynamic contribution decreases (-25%) while the thermodynamic is slightly enhanced (+5%) with convective self-aggregation, leading to lower condensation rates. When the atmosphere is more organized into a moist convecting region and a dry convection-free region, deep convective updrafts are surrounded by a warmer environment which reduces convective instability and thus the dynamic contribution. The moister boundary-layer explains the positive thermodynamic contribution. The microphysic contribution is increased by +50% with aggregation. The latter is partly due to reduced evaporation of rain falling through a moister near-cloud environment, but also to the associated larger accretion efficiency. Thus, a potential change in convective organization regimes in a warming climate could lead to an evolution of tropical precipitation extremes significantly different than that expected from thermodynamical considerations. The relevance of self-aggregation to the real tropics is still debated. Improved fundamental understanding of self-aggregation, its sensitivity to warming and connection to precipitation extremes, is hence crucial to achieve accurate rainfall projections in a warming climate.

Forcing Convection to Aggregate Using Diabatic Heating Perturbations

Tropical deep convection can aggregate into large clusters, which can have impacts on the local humidity and precipitation. Sea surface temperature (SST) gradients have been shown to organize convection, yet there has been little work done to investigate the impact of diabatic heating perturbations in the atmosphere on the aggregation of convection. Here we investigate how anomalous diabatic heating of the atmospheric column, through an idealized aerosol plume, affects the existence and mechanisms of convective aggregation in non-rotating, global radiative-convective equilibrium simulations. We show that the aerosol forcing has the ability to increase the degree of aggregation, especially at lower SSTs. Detailed investigation shows that the diabatic heating source incites a thermally driven circulation, forced by the shortwave perturbation. The increase in aggregation is caused in part by this circulation, and in part by the longwave heating anomalies occurring due to the surface convergence of moisture and convection. At higher SSTs, longwave feedbacks are crucial for the aggregation of convection, even with the shortwave heating perturbation. At lower SSTs, convection is able to aggregate with the shortwave perturbation in the absence of longwave feedbacks. These perturbations provide a link to studying the effects of absorbing aerosol plumes on convection, for example during the Indian monsoon season. We argue that, as there is aggregation for plumes with realistic aerosol absorption optical depths, this could be an analogue for real-world organization in regions with high pollution.

Self-Aggregation of Convective Clouds With Interactive Sea Surface Temperature

This study investigates the feedbacks between an interactive sea surface temperature (SST) and the self-aggregation of deep convective clouds, using a cloud-resolving model in nonrotating radiative-convective equilibrium. The ocean is modeled as one layer slab with a temporally fixed mean but spatially varying temperature. We find that the interactive SST decelerates the aggregation and that the deceleration is larger with a shallower slab, consistent with earlier studies. The surface temperature anomaly in dry regions is positive at first, thus opposing the diverging shallow circulation known to favor self-aggregation, consistent with the slower aggregation. But surprisingly, the driest columns then have a negative SST anomaly, thus strengthening the diverging shallow circulation and favoring aggregation. This diverging circulation out of dry regions is found to be well correlated with the aggregation speed. It can be linked to a positive surface pressure anomaly (PSFC), itself the consequence of SST anomalies and boundary layer radiative cooling. The latter cools and dries the boundary layer, thus increasing PSFC anomalies through virtual effects and hydrostasy. Sensitivity experiments confirm the key role played by boundary layer radiative cooling in determining PSFC anomalies in dry regions, and thus the shallow diverging circulation and the aggregation speed.

Clouds and Convective Self-Aggregation in a Multimodel Ensemble of Radiative-Convective Equilibrium Simulations

The Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative-convective equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climate sensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique among intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud-resolving models (CRMs), large eddy simulations (LES), and global cloud-resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self-aggregation in large domains and agree that self-aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self-aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than unaggregated simulations.