The Radiative‐Convective Equilibrium Model Intercomparison Project (RCEMIP) exhibits a large spread in the simulated climate across models, including in profiles of buoyancy and relative humidity. Here we use simple theory to understand the control of stability, relative humidity, and their responses to warming. Across the RCEMIP ensemble, temperature profiles are systematically cooler than a moist adiabat, and convective available potential energy (CAPE) increases with warming at a rate greater than that expected from the Clausius‐Clapeyron relation. There is higher CAPE (greater instability) in models that are on average moister in the lower‐troposphere. To more explicitly evaluate the drivers of the intermodel spread, we use simple theory to estimate values of entrainment and precipitation efficiency (PE) given the simulated values of CAPE and lower‐tropospheric relative humidity. We then decompose the intermodel spread in CAPE and relative humidity (and their responses to warming) into contributions from variability in entrainment, PE, the temperature of the convecting top, and the inverse water vapor scale height. Model‐to‐model variation in entrainment is a dominant source of intermodel spread in CAPE and its changes with warming, while variation in PE is the dominant source of intermodel spread in relative humidity. We also decompose the magnitude of the CAPE increase with warming and find that atmospheric warming itself contributes most strongly to the CAPE increase, but the indirect effect of increases in the water vapor scale height with warming also contribute to increasing CAPE beyond that expected from Clausius‐Clapeyron.
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Abstract Radiative‐convective equilibrium (RCE) is particularly well suited for studying tropical deep‐convection, a regime of clouds that contributes some of the highest uncertainties to the estimates of total cloud feedback. In order to perform a comprehensive calculation and decomposition of cloud feedbacks in cloud‐permitting models, previously primarily done in global climate models, the configuration of a satellite simulator for use with offline data was successfully implemented. The resultant total cloud feedback is slightly positive, primarily driven by the longwave effects of increases in cloud altitude. The high‐cloud altitude feedback is robustly positive and has a central value and uncertainty well‐matched with prior estimates. Reductions in high cloud amount drive a tropical anvil cloud area feedback that is on average negative, consistent with prior estimates. However, a subset of models with finer horizontal grid spacing indicate that a positive tropical anvil cloud area feedback cannot be ruled out. Even though RCE is only applicable to tropical deep‐convective clouds, the RCE total cloud feedback is within the range of prior comprehensive estimates of the global total cloud feedback. This emphasizes that the tropics heavily influence the behavior of global cloud feedbacks and that RCE can be exploited to learn more about how processes related to deep convection control cloud feedbacks.
Free, publicly-accessible full text available November 1, 2024 -
Abstract The spontaneous self-aggregation (SA) of convection in idealized model experiments highlights the importance of interactions between tropical convection and the surrounding environment. The authors have shown that SA fundamentally changes with the background rotation in previous
f -plane simulations, in terms of both the resulting forms of organized convection and the relative roles of the physical feedbacks driving them. This study considers the dependence of SA on rotation in one large domain on theβ plane, introducing an additional layer of complexity. Simulations are performed with uniform thermal forcing and explicit convection. Focuses include statistical and structural analysis of the convective modes, process-oriented diagnostics of how they develop, and resulting mean states. Two regimes of SA emerge within the first 15 days, separated by a critical zone wheref is analogous to 10°–15° latitude. Organized convection at near-equatorial values off primarily consists of convectively coupled Kelvin waves. Wind speed–surface enthalpy flux feedbacks are the dominant process driving moisture variability early on, then clear-sky shortwave radiative feedbacks are strongest in wave maintenance. In contrast, at higherf , numerous tropical cyclones develop and coexist, dominated by surface flux and longwave processes. Tropical cyclogenesis is most pronounced at intermediatef (analogous to 25°–40°), but are longer-lived at higherf . The resulting modes of SA at lowf differ between theseβ -plane simulations (convectively coupled waves) and priorf -plane simulations (weak tropical cyclones or nonrotating clusters). Otherwise, these results provide further evidence for the changing roles of radiative, surface flux, and advective processes in influencing SA asf changes, as found in our previous study.Significance Statement In model simulations, convection often self-organizes due to interactions with its surrounding environment. These interactions are relevant in the real-world organization of rainfall and clouds, and may thus be useful to understand for improved prediction of tropical weather and climate. Previous work using a set of simple model experiments with constant Coriolis force showed that at different latitudes, different processes dominate, and different types of organized convection result. This study verifies that finding using a more complex and realistic model, where the Coriolis force varies within the domain to resemble different latitudes. Specifically, the convection here self-organizes into atmospheric waves (periodic disturbances) at low latitudes, and tropical cyclones at high latitudes.
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Abstract Previous work has found that as the surface warms the large‐scale tropical circulations weaken, convective anvil cloud fraction decreases, and atmospheric static stability increases. Circulation changes inevitably lead to changes in the humidity and cloud fields which influence the surface energetics. The exchange of mass between the boundary layer (BL) and the midtroposphere has also been shown to weaken in global climate models. What has remained less clear is how robust these changes in the circulation are to different representations of convection, clouds, and microphysics in numerical models. We use simulations from the Radiative‐Convective Equilibrium Model Intercomparison Project to investigate the interaction between overturning circulations, surface temperature, and atmospheric moisture. We analyze the underlying mechanisms of these relationships using a 21‐member model ensemble that includes both General Circulation Models and Cloud‐system Resolving Models. We find a large spread in the change of intensity of the overturning circulation. Both the range of the circulation intensity, and its change with warming can be explained by the range of the mean upward vertical velocity. There is also a consistent decrease in the exchange of mass between the BL and the midtroposphere. However, the magnitude of the decrease varies substantially due to the range of responses in both mean precipitation and mean precipitable water. We hypothesize based on these results that despite well understood thermodynamic constraints, there is still a considerable ability for the cloud fields and the precipitation efficiency to drive a substantial range of tropical convective responses to warming.
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Abstract Interactions between clouds, water vapor, radiation, and circulation influence tropical cyclone (TC) development. Many of these interactions can be quantified by understanding tendencies of the spatial variance of moist static energy (MSE). Dropsondes from aircraft reconnaissance sample profiles needed to compute MSE at fine vertical resolution, and may be useful in analyzing these feedbacks on TCs in situ. However, dropsondes are spatially sparse, and sample limited column depths depending on the type of reconnaissance mission. We use idealized convection‐permitting simulations to examine how MSE variability, and the feedbacks that influence it, are resolved using selected patterns of grid points meant to resemble dropsonde launch points in reconnaissance flight patterns. We first examine the column depth necessary to capture the MSE variability of the full atmosphere. We then study how these simulated flight patterns depict MSE variance and its relevant diabatic feedbacks in TCs of varying structure and intensity.
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Abstract High‐resolution modeling reveals a tendency for deep convection to spontaneously self‐aggregate from radiative‐convective equilibrium. Self‐aggregated convection takes different forms in nonrotating versus rotating environments, including tropical cyclones (TCs) in the latter. This suggests that self‐aggregation (SA), and the relative roles of the mechanisms that cause it, may undergo a gradual regime shift as the ambient rotation changes. We address this hypothesis using 31 cloud‐resolving model simulations on
f ‐planes corresponding to latitudes between 0.1° and 20°, spanning a range of weakly rotating environments largely unexplored in prior literature. Simulations are classified into three groups. The first (low‐f , 0.1°–5°) is characterized by the growth of several dry patches. Surface enthalpy flux feedbacks dominate in this initial growth phase, followed by radiative (primarily cloud longwave) effects. Eventually, convection takes the form of either a nonrotating band or a quasi‐circular cluster. In contrast, the 9°–20° (high‐f ) group dries less rapidly in early stages, though enhanced surface flux effects form a moist anomaly that undergoes TC genesis. The TC then acts to dry the remainder of the domain. Finally, a set of 6°–8° (medium‐f ) simulations fails to fully self‐aggregate, producing convection across most of the domain through the full 100‐day simulation. The combination of relatively weak diabatic feedbacks and a negative advective feedback prevents SA from completing in this group. The advective feedback becomes more negative with increasing rotation, but high‐f simulations compensate by having sufficiently strong surface flux feedbacks to support TC genesis. -
Abstract Characteristics of, and fundamental differences between, the radiative‐convective equilibrium (RCE) climate states following the Radiative‐Convective Equilibrium Model Intercomparison Project (RCEMIP) protocols in the Community Atmosphere Model version 5 (CAM5) and version 6 (CAM6) are presented. This paper explores the characteristics of clouds, moisture, precipitation and circulation in the RCE state, as well as the tropical response to surface warming, in CAM5 and CAM6 with different parameterizations. Overall, CAM5 simulates higher precipitation rates that result in larger global average precipitation, despite lower outgoing longwave radiation compared to CAM6. Differences in the structure of clouds, particularly the amount and vertical location of cloud liquid, exist between the CAM versions and can, in part, be related to distinct representations of shallow convection and boundary layer processes. Both CAM5 and CAM6 simulate similar peaks in cloud fraction, relative humidity, and cloud ice, linked to the usage of a similar deep convection parameterization. These anvil clouds rise and decrease in extent in response to surface warming. More generally, extreme precipitation, aggregation of convection, and climate sensitivity increase with warming in both CAM5 and CAM6. This analysis provides a benchmark for future studies that explore clouds, convection, and climate in CAM with the RCEMIP protocols now available in the Community Earth System Model. These results are discussed within the context of realistic climate simulations using CAM5 and CAM6, highlighting the usefulness of a hierarchical modeling approach to understanding model and parameterization sensitivities to inform model development efforts.
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Abstract The Radiative‐Convective Equilibrium Model Intercomparison Project (RCEMIP) consists of simulations at three fixed sea‐surface temperatures (SSTs: 295, 300, and 305 K) and thus allows for a calculation of the climate feedback parameter based on the change of the top‐of‐atmosphere radiation imbalance. Climate feedback parameters range widely across RCEMIP, roughly from
− 6 to 3 W m−2 K−1 , particularly across general‐circulation models (GCMs) as well as global and large‐domain cloud‐resolving models (CRMs). Small‐domain CRMs and large‐eddy simulations have a smaller range of climate feedback parameters due to the absence of convective self‐aggregation. More than 70–80% of the intermodel spread in the climate feedback parameter can be explained by the combined temperature dependencies of convective aggregation and shallow cloud fraction. Low climate sensitivities are associated with an increase of shallow cloud fraction (increasing the planetary albedo) and/or an increase in convective aggregation with warming. An increase in aggregation is associated with an increase in outgoing longwave radiation, caused primarily by mid‐tropospheric drying, and secondarily by an expansion of subsidence regions. Climate sensitivity is neither dependent on the average amount of aggregation nor on changes in deep/anvil cloud fraction. GCMs have a lower overall climate sensitivity than CRMs because in most GCMs convective aggregation increases with warming, whereas in CRMs, convective aggregation shows no consistent temperature trend. -
Abstract In a modeled environment of rotating radiative‐convective equilibrium (RCE), convective self‐aggregation may take the form of spontaneous tropical cyclogenesis. We investigate the processes leading to tropical cyclogenesis in idealized simulations with a three‐dimensional cloud‐permitting model configured in rotating RCE, in which the background planetary vorticity is varied across
f ‐plane cases to represent a range of deep tropical and near‐equatorial environments. Convection is initialized randomly in an otherwise homogeneous environment, with no background wind, precursor disturbance, or other synoptic‐scale forcing. We examine the dynamic and thermodynamic evolution of cyclogenesis in these experiments and compare the physical mechanisms to current theories. All simulations with planetary vorticity corresponding to latitudes from 10°–20° generate intense tropical cyclones, with maximum wind speeds of 80 m s−1or above. Time to genesis varies widely, even within a five‐member ensemble of 20° simulations, indicating large stochastic variability. Shared across the 10°–20° group is the emergence of a midlevel vortex in the days leading to genesis, which has dynamic and thermodynamic implications on its environment that facilitate the spin‐up of a low‐level vortex. Tropical cyclogenesis is possible in this model at values of Coriolis parameter as low as that representative of 1°. In these experiments, convection self‐aggregates into a quasicircular cluster, which then begins to rotate and gradually strengthen into a tropical storm, aided by strong near‐surface inflow that is already established days prior. Other experiments at these lower Coriolis parameters instead self‐aggregate into a nonrotating elongated band and fail to undergo cyclogenesis over the 100‐day simulation. -
Abstract 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.