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Abstract A plume model applied to radiosonde observations and the fifth generation ECMWF atmospheric reanalysis (ERA5) is used to assess the relative importance of lower-tropospheric moisture and temperature variability in the convective coupling of equatorial waves. Regression and wavenumber–frequency coherence analyses of satellite precipitation, outgoing longwave radiation (OLR), and plume model estimates of lower-tropospheric vertically integrated buoyancy (〈B〉) are used to identify the spatial and temporal scales where these variables are highly correlated. Precipitation and OLR show little coherence with 〈B〉 when zero entrainment is prescribed in the plume model. In contrast, precipitation and OLR vary coherently with 〈B〉 when “deep inflow” entrainment is prescribed, highlighting that entrainment occurring over a deep layer of the lower troposphere plays an important role in modifying the thermodynamic properties of convective plumes in the tropics. Consistent with previous studies, moisture variability is found to play a more dominant role than temperature variability in the convective coupling of the Madden–Julian oscillation (MJO) and equatorial Rossby (ER) waves, while temperature variability is found to play an important role in the convective coupling of Kelvin (KW) and inertio-gravity (IG) waves. Convective coupling is most strongly impacted by moisture variations in the 925–850- and 825–600-hPa layers for the MJO and ERs, and by 825–600-hPa temperature variations in KWs and IGs, with 1000–950-hPa moist static energy variations playing a relatively small role in convective coupling. Simulations of the Energy Exascale Earth System Model (E3SM), version 2, and a preoperational prototype of NOAA Global Forecast System (GFS) V17 are examined, the former showing unrealistically high coherence between precipitation and 1000-hPa moist static energy, the latter a more realistic relationship. 

Abstract This study investigates the role of soil moisture (SM) on the initiation and organization of convective systems using the convection‐permitting ICOsahedral Non‐hydrostatic (ICON) model. We conduct two sets of experiments: a Control experiment with interactive SM and a fixed SM experiment (FixedSM) with invariable SM conditions. We focus on two regions in South America: the Amazon and southeastern South America (SESA). Larger organized convective systems are associated with greater SM heterogeneity in both regions, though other large‐scale synoptic influences affect the robustness of this relationship in SESA. These results remain largely unaffected by disabling the effects of precipitation on SM in the FixedSM experiment, and complementary analyses using satellite‐based estimates of SM and precipitation support these findings. Spatial compositing of mesoscale environments in the Amazon shows the presence of well‐defined SM gradients, at a length scale of a few hundred kilometers, many hours before convective system detection. Larger SM gradients correspond to larger gradients in thermodynamic variables, particularly surface temperature and sensible heat flux, and are associated with larger convective systems. Overall, our findings suggest that surface heterogeneities such as SM gradients not only affect deep convection initiation, as previously suggested, but they can also encourage the growth and organization of convective systems into larger clusters, particularly in the absence of significant synoptic influences. 

Abstract Clouds constitute a large portion of uncertainty in predictions of equilibrium climate sensitivity (ECS). While low cloud feedbacks have been the focus of intermodel studies due to their high variability among global climate models, tropical high cloud feedbacks also exhibit considerable uncertainty. Here, we apply the cloud radiative kernel technique of Zelinka et al. to 22 models across the CMIP5 and CMIP6 ensembles to survey tropical high cloud feedbacks and analyze their relationship to ECS. We find that the net high cloud feedback and its altitude and optical depth feedback components are significantly positively correlated with ECS in the tropical mean. On the other hand, the tropical mean high cloud amount feedback is not correlated with ECS. These relationships are most pronounced outside of areas of strong climatological ascent, suggesting the importance of thin cirrus feedbacks. Finally, we explore connections between high cloud feedbacks, climate sensitivity, and mean state high cloud properties. In general, high ECS models are cloudier in the upper troposphere but have a thinner high cloud population. Moreover, we find that having more thin cirrus in the mean state relates to more positive high cloud altitude and optical depth feedbacks, and it either amplifies or dampens the high cloud amount feedback depending on the large-scale dynamical regime (amplifying in descent and dampening in ascent). In summary, our analysis highlights the importance of tropical high cloud feedbacks for driving intermodel spread in ECS and suggests that mean state high cloud characteristics might provide a unique opportunity for observationally constraining high cloud feedbacks. Significance StatementClouds play an important role in modulating the effects of climate change through feedback processes involving changes to their amount, altitude, and opacity. In this study, we seek to understand how changes to tropical high clouds under warming are related to the magnitude of warming that global climate models simulate. We find that tropical high cloud feedbacks robustly relate to the amount of warming a model predicts and that warmer models tend to have a thinner tropical high cloud climatology. Our results highlight a potential opportunity to form a new constraint using these relationships in order to narrow the spread of warming estimates among global climate models.