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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.

 

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 previousf-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 theβplane, 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 wherefis analogous to 10°–15° latitude. Organized convection at near-equatorial values offprimarily 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 lowfdiffer 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 asfchanges, as found in our previous study.

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.

 

Abstract A complete understanding of the development of tropical cyclones (TC) remains elusive and forecasting TC intensification remains challenging. This motivates further research into the physical processes that govern TC development. One process that has, until recently, been under-investigated is the role of radiation. Here, the importance of radiative feedbacks in TC development and the mechanisms underlying their influence is investigated in a set of idealized convection-permitting simulations. A TC is allowed to form after initialization from a mesoscale warm, saturated bubble on an f -plane, in an otherwise quiescent and moist neutral environment. Tropical storm formation is delayed by a factor of two or three when radiative feedbacks are removed by prescribing a fixed cooling profile or spatially homogenizing the model-calculated cooling profiles. The TC’s intensification rate is also greater when longwave radiative feedbacks are stronger. Radiative feedbacks in the context of a TC arise from interactions between spatially and temporally varying radiative heating and cooling (driven by the dependence of radiative heating and cooling rate on clouds and water vapor) and the developing TC (the circulation of which shapes the structure of clouds and water vapor). Further analysis and additional mechanism denial experiments pinpoint the longwave radiative feedback contributed by ice clouds as the strongest influence. Improving the representation of cloud-radiative feedbacks in forecast models therefore has the potential to yield critical advancements in TC prediction. 

This study investigates Gulf Stream (GS) sea surface temperature (SST) anomalies associated with the extratropical transition (ET) of tropical cyclones (TCs) in the North Atlantic. Composites of western North Atlantic TCs indicate that GS SSTs are warmer, and both large‐ and fine‐scale SST gradients are weaker than average, for TCs that begin the ET process but do not complete it, compared with TCs that do. Further analysis suggests that the associated fine‐scale GS SST gradient anomalies are related to atmospheric processes but not the same as those that are typically associated with the onset of ET. As sensible heat flux gradients and surface diabatic frontogenesis are shown to generally scale with the local SST gradient strength, these results suggest that knowledge of the fine‐scale GS SST gradient in the weeks prior to the arrival of a TC might potentially provide additional information regarding the likelihood of that system completing ET.

 

Abstract This study compares the spread in climatological tropical cyclone (TC) precipitation across eight different reanalysis datasets: NCEP-CFSR, ERA-20C, ERA-40, ERA5, ERA-Interim, JRA-55, MERRA-2, and NOAA-20C. TC precipitation is assigned using manual tracking via a fixed 500-km radius from each TC center. The reanalyses capture similar general spatial patterns of TC precipitation and TC precipitation fraction, defined as the fraction of annual precipitation assigned to TCs, and the spread in TC precipitation is larger than the spread in total precipitation across reanalyses. The spread in TC precipitation relative to the inter-reanalysis mean TC precipitation, or relative spread, is larger in the east Pacific than in the west Pacific. Partitioned by reanalysis intensity, the largest relative spread across reanalyses in TC precipitation is from high-intensity TCs. In comparison with satellite observations, reanalyses show lower climatological mean annual TC precipitation over most areas. A comparison of area-averaged precipitation rate in TCs composited over reanalysis intensity shows the spread across reanalyses is larger for higher intensity TCs. Testing the sensitivity of TC precipitation assignment to tracking method shows that climatological mean annual TC precipitation is systematically larger when assigned via manual tracking versus objective tracking. However, this tendency is minimized when TC precipitation is normalized by TC density. Overall, TC precipitation in reanalyses is affected by not only horizontal output resolution or any TC preprocessing, but also data assimilation and parameterization schemes. The results indicate that improvements in the representation of TCs and their precipitation in reanalyses are needed to improve overall precipitation. 

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.

 

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.

 

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 onf‐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‐fsimulations compensate by having sufficiently strong surface flux feedbacks to support TC genesis.

 

The tall clouds that comprise tropical storms, hurricanes, and typhoons—or more generally, tropical cyclones (TCs)—are highly effective at trapping the infrared radiation welling up from the surface. This cloud–infrared radiation feedback, referred to as the “cloud greenhouse effect,” locally warms the lower–middle troposphere relative to a TC’s surroundings through all stages of its life cycle. Here, we show that this effect is essential to promoting and accelerating TC development in the context of two archetypal storms—Super Typhoon Haiyan (2013) and Hurricane Maria (2017). Namely, this feedback strengthens the thermally direct transverse circulation of the developing storm, in turn both promoting saturation within its core and accelerating the spin-up of its surface tangential circulation through angular momentum convergence. This feedback therefore shortens the storm’s gestation period prior to its rapid intensification into a strong hurricane or typhoon. Further research into this subject holds the potential for key progress in TC prediction, which remains a critical societal challenge.