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Inconsistent findings in soil moisture (SM)‐precipitation feedback literature motivate further research into the role of the boundary layer in these feedbacks. The present study explores mechanisms that can explain the spatial patterns found in a previous analysis employing satellite measured SM: positive feedback in the semi‐arid western U.S. (higher morning SM predicting greater likelihood of afternoon rainfall), and negative feedback in the humid east. Using a cloud–topped boundary layer model, we examine how evaporative fraction (EF, a proxy for SM) influences cloud mass flux (CMF). We then use logistic regression to relate CMF to precipitation. The results are consistent with the previous analysis: in semi‐arid areas, increased humidification with increased EF dominates CMF strength, yielding net positive feedbacks; in humid areas, reductions in convective velocity with increasing EF dominate the CMF, yielding net negative feedbacks. Such offsetting feedbacks may contribute to inconsistencies reported in the literature.

We analyze the atmospheric processes that explain the large changes in radiative feed-backs between the two latest climate configurations of the Hadley Centre Global Environmental model. We use a large set of atmosphere-only climate-change simulations (amip and amip-p4K) to separate the contributions to the differences in feedback parameter from all the atmospheric model developments between the two latest model configurations. We show that the differences are mostly driven by changes in the shortwave cloud radiative feedback in the midlatitudes, mainly over the Southern Ocean. Two new schemes explain most of the differences: the introduction of a new aerosol scheme; and the development of a new mixed-phase cloud scheme. Both schemes reduce the strength of the pre-existing shortwave negative cloud feedback in the midlatitudes. The new aerosol scheme dampens a strong aerosol-cloud interaction, and it also suppresses a negative clear-sky shortwave feedback. The mixed-phase scheme increases the amount of cloud liquid water path (LWP) in the present-day, thereby reducing the radiative effciency of the increase of LWP in the warmer climate. It also enhances a strong, pre-existing, positive cloud fraction feedback. We assess the realism of the changes by comparing present-day simulations against observations, and discuss avenues that could help constrain the relevant processes.

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. Plain Language Summary This study investigates tropical clouds and climate using results from more than 30 different numerical models set up in a simplified framework. The data set of model simulations is unique in that it includes a wide range of model types configured in a consistent manner. We address some of the biggest open questions in climate science, including how cloud properties change with warming and the role that the tendency of clouds to form clusters plays in determining the average climate and how climate changes. While there are large differences in how the different models simulate average temperature, humidity, and cloudiness, in a majority of models, the amount of high clouds decreases as climate warms. Nearly all models simulate a tendency for clouds to cluster together. There is agreement that when the clouds are clustered, the atmosphere is drier with fewer clouds overall. We do not find a conclusive result for how cloud clustering changes as the climate warms. Key Points Temperature, humidity, and clouds in radiative‐convective equilibrium vary substantially across models Models agree that self‐aggregation dries the atmosphere and reduces high cloudiness There is no consistency in how self‐aggregation depends on warming

The high‐cloud amount responses to sea surface temperature (SST) changes were investigated based on simulations with radiative‐convective equilibrium configuration using a high‐resolution nonhydrostatic icosahedral atmospheric model. The radiative‐convective equilibrium was calculated using a nonrotating sphere with Earth radius and a 14‐km horizontal mesh with uniform SSTs of 300 and 304 K. Two types of cloud microphysics schemes (single‐ and double‐moment bulk schemes) and two types of vertical layer configurations (38 and 78 layers) were tested. The radiatively driven circulation weakens with increasing SST in all simulation pairs due to the increase in the static stability, as suggested in previous studies. In contrast, the high‐cloud amount increases in three simulation pairs and decreases in one pair. These indicate that the weakening of radiatively driven circulation with increasing SST does not always accompany the high‐cloud amount decrease. We determined that the tropopause layer was wet (dry) in simulations that showed positive (negative) high‐cloud cover responses. The radiatively driven upward moisture transport just below the wet tropopause layer increases with increasing SST in the simulation pairs with positive high‐cloud amount responses, and this causes the supply of ice condensate to the lower layer through the sedimentation process, while this feedback was not observed in the simulation pair with the negative response. These indicate that the high‐cloud cover response depends on the occurrence of the feedback and there is a feedback threshold among the variety of simulations. And furthermore, these speculate that whether the feedback mechanism is effective or not has the large impact on high‐cloud responses in the real atmosphere. Key Points The high‐cloud amount responses on SST changes depend on both the vertical resolution and microphysics scheme Radiation‐cloud feedbacks near the tropopause can increase clouds in warmer climates despite weakening of radiatively forced circulation The high‐cloud responses in the real atmosphere depend on whether the feedback mechanisms are effective or not

The new capabilities of global storm‐resolving models to resolve individual clouds allow for a more physical perspective on the tropical high‐cloud radiative effect and how it might change with warming. In this study, we develop a conceptual model of the high‐cloud radiative effect as a function of cloud thickness measured by ice water path. We use atmospheric profiles from a global ICON simulation with 5km $5\\hspace*{.5em}\\mathrm{k}\\mathrm{m}$ horizontal grid spacing to calculate the radiation offline with the ARTS line‐by‐line radiative transfer model. The conceptual model of the high‐cloud radiative effect reveals that it is sufficient to approximate high clouds as a single layer characterized by an albedo, emissivity and temperature, which vary with ice water path. The increase of the short‐wave high‐cloud radiative effect with ice water path is solely explained by the high‐cloud albedo. The increase of the long‐wave high‐cloud radiative effect with ice water path is governed by an increase of emissivity for ice water path below 10−1kgm−2 $1{0}^{-1}\\hspace*{.5em}\\mathrm{k}\\mathrm{g}\\hspace*{.5em}{\\mathrm{m}}^{-\\mathrm{2}}$, and by a decrease of high‐cloud temperature with increasing ice water path above this threshold. The mean high‐cloud radiative effect from the ARTS simulations for the chosen day of this ICON model run is 1.25Wm−2 $1.25\\hspace*{.5em}\\mathrm{W}\\hspace*{.5em}{\\mathrm{m}}^{-\\mathrm{2}}$, which is closely matched by our conceptual model with 1.26Wm−2 $1.26\\hspace*{.5em}\\mathrm{W}\\hspace*{.5em}{\\mathrm{m}}^{-}\\mathrm{2}$. Because the high‐cloud radiative effect depends on the assumed radiative alternative, assumptions on low clouds make a substantial difference. The conceptual model predicts that doubling the fraction of low clouds roughly doubles the positive high‐cloud radiative effect. Plain Language Summary High clouds are widespread within the tropics and can either amplify or dampen global warming if they change in a way that affects their ability to reflect solar or absorb terrestrial thermal radiation. To better understand how high clouds within the tropics might influence global warming, we use high‐resolution climate models that are able to resolve individual clouds. Those models allow us to interpret the effect of high clouds on solar and thermal radiation as a function of the cloud thickness. To better understand this dependence, we develop a conceptual model of high clouds that breaks the physical mechanisms down to their main parts. The conceptual model shows that high clouds can be well approximated as a single layer whose reflectivity, temperature and transparency to thermal radiation depend on the cloud thickness. We find that high clouds are slightly warming the Earth in the current climate, which is well reproduced by the conceptual model. The conceptual model reveals that if more low clouds exist below the high clouds, the warming effect of high clouds is increased. Key Points The complexity of tropical high‐cloud radiative effect is reduced by conceptualizing it as a function of the ice water path High clouds within our model simulation are characterized by a weakly positive high‐cloud radiative effect Low clouds render the high‐cloud radiative effect positive

Cloud‐resolving models have shown that under certain conditions, the Radiative‐Convective Equilibrium (RCE) could become unstable and lead to the spontaneous organization of the atmosphere into dry and wet areas, and the aggregation of convection. In this study, we show that this “self‐aggregation” behavior also occurs in nonrotating RCE simulations performed with the IPSL‐CM5A‐LR General Circulation Model (GCM), and that it exhibits a strong dependence on sea surface temperature (SST). We investigate the physical mechanisms that control the initiation of self‐aggregation in this model, and their dependence on temperature. At low SSTs, the onset of self‐aggregation is primarily controlled by the coupling between low‐cloud radiative effects and shallow circulations and the formation of “radiatively driven cold pools” in areas devoid of deep convection, while at high SSTs it is primarily controlled by the coupling between surface fluxes and circulation within convective areas. At intermediate temperatures, the occurrence of self‐aggregation is less spontaneous and depends on initial conditions, but it can arise through a combination of both mechanisms. Through their coupling to circulation and surface fluxes, the radiative effects of low‐level clouds play a critical role in both initiation mechanisms, and the sensitivity of boundary layer clouds to surface temperature explains to a large extent the temperature dependence of convective self‐aggregation. At any SST, the presence of cloud‐radiative effects in the free troposphere is necessary to the initiation, growth, and maintenance of convective aggregation. Key Points: Temperature dependence of convective self‐aggregation in a GCM The physical mechanisms that initiate aggregation depend on temperature Low‐cloud sensitivity to SST contributes to a large extent to the SST dependence of aggregation

The influence of cloud modelling uncertainties on the projection of the tropical low‐cloud response to global warming is explored by perturbing model parameters of the IPSL‐CM5A climate model in a range of configurations (realistic general circulation model, aqua‐planet, single‐column model). While the positive sign and the mechanism of the low‐cloud response to climate warming predicted by the model are robust, the amplitude of the response can vary considerably depending on the model tuning parameters. Moreover, the strength of the low‐cloud response to climate change exhibits a strong correlation with the strength of the low‐cloud radiative effects simulated in the current climate. We show that this correlation primarily results from a local positive feedback (referred to as the “beta feedback”) between boundary‐layer cloud radiative cooling, relative humidity and low‐cloud cover. Based on this correlation and observational constraints, it is suggested that the strength of the tropical low‐cloud feedback predicted by the IPSL‐CM5A model in climate projections might be overestimated by about fifty percent. Key Points Correlation between low‐cloud radiative effects in present and future climates Due to a positive radiative feedback between low clouds and relative humidity Observations help constrain the strength of climate change low‐cloud feedbacks

The physical mechanism of low‐cloud feedbacks is examined by using perturbed‐parameter ensemble experiments in a unified scheme of boundary layer turbulence and shallow convection, named Cloud Layers Unified by Binormals (CLUBB) coupled to Community Atmosphere Model version 5 (CAM5). The shortwave cloud feedbacks in CAM5‐CLUBB are positive in the most stable tropical regime, which is related to the weaker turbulence in the planetary boundary layer (PBL) in a warmer climate that is possibly triggered by the strengthened stability of the cloud layer. The positive feedback between low cloud cover (LCC), cloud top radiative cooling, and PBL turbulent mixing may further enhance the decrease in LCC. The stronger inversion stability of PBL partly counters the decrease in LCC, and a recently developed index, the estimated cloud‐top entrainment index, is a better predictor for LCC changes than conventional stability indices. The relative strength of shallow convection increases in the warmer climate, but its effect on low‐cloud feedback is complicated by the unified treatment of shallow convection and PBL turbulence in CLUBB. Stronger shallow convection means more convective drying but also less PBL turbulence and less LCC in the present climate, which leads to less reduction in LCC. The parameters related to dynamic turbulent structure and double Gaussian closure in CLUBB are the most influential parameters on low‐cloud feedbacks. Our results suggest that a unified treatment of shallow convection and turbulence may give rise to the predominate role of the PBL turbulent mixing in determining low‐cloud feedback. Plain Language Summary Low‐cloud feedbacks are examined in a unified scheme of boundary layer turbulence and shallow convection (Cloud Layers Unified by Binormal) by using perturbed‐parameter ensemble experiments. The shortwave low‐cloud feedbacks are found to be positive in the most stable cloud regime, which is related to the weaker turbulence in the planetary boundary layer (PBL) in a warmer climate. The relative strength of shallow convection increases in the warmer climate, but its effect on low‐cloud feedback is complicated by the unified treatment of shallow convection and PBL turbulence in Cloud Layers Unified by Binormal. The stronger inversion stability of PBL partly counters the decrease in low cloud cover, and a recently developed index, the estimated cloud‐top entrainment index, is a better predictor for low cloud cover changes than conventional stability indices. Our results suggest that a unified treatment of shallow convection and turbulence may give rise to the predominate role of the PBL turbulent mixing in determining low‐cloud feedback. Key Points A unified turbulence and shallow convection scheme produces a positive low‐cloud feedback The positive low‐cloud feedback is related to the weaker turbulence in the planetary boundary layer The effect of shallow convection on low‐cloud feedback is complicated in this unified scheme

We present nonrotating simulations with the Goddard Earth Observing System (GEOS) atmospheric general circulation model (AGCM) in a square limited area domain over uniform sea surface temperature. As in previous studies, convection spontaneously aggregates into humid clusters, driven by a combination of radiative and moisture‐convective feedbacks. The aggregation is qualitatively independent of resolution, with horizontal grid spacing from 3 to 110 km, with both explicit and parameterized deep convection. A budget for the spatial variance of column moist static energy suggests that longwave radiative and surface flux feedbacks help establish aggregation, while the shortwave feedback contributes to its maintenance. Mechanism‐denial experiments confirm that aggregation does not occur without interactive longwave radiation. Ice cloud radiative effects help support the humid convecting regions but are not essential for aggregation, while liquid clouds have a negligible effect. Removing the dependence of parameterized convection on tropospheric humidity reduces the intensity of aggregation but does not prevent the formation of dry regions. In domain sizes less than (5,000 km)2, the aggregation forms a single cluster, while larger domains develop multiple clusters. Larger domains initialized with a single large cluster are unable to maintain them, suggesting an upper size limit. Surface wind speed increases with domain size, implying that maintenance of the boundary layer winds may limit cluster size. As cluster size increases, large boundary layer temperature anomalies develop to maintain the surface pressure gradient, leading to an increase in the depth of parameterized convective heating and an increase in gross moist stability. Key Points The sensitivity of parameterized convection to midtropospheric humidity enhances aggregation Humid clusters have a maximum scale of 3–4,000 km, limited by the boundary layer momentum balance Larger clusters have warmer humid‐region boundary layers and deeper convective heating

The response to warming of tropical low-level clouds including both marine stratocumulus and trade cumulus is a major source of uncertainty in projections of future climate. Climate model simulations of the response vary widely, reflecting the difficulty the models have in simulating these clouds. These inadequacies have led to alternative approaches to predict low-cloud feedbacks. Here, we review an observational approach that relies on the assumption that observed relationships between low clouds and the “cloud-controlling factors” of the large-scale environment are invariant across time-scales. With this assumption, and given predictions of how the cloud-controlling factors change with climate warming, one can predict low-cloud feedbacks without using any model simulation of low clouds. We discuss both fundamental and implementation issues with this approach and suggest steps that could reduce uncertainty in the predicted low-cloud feedback. Recent studies using this approach predict that the tropical low-cloud feedback is positive mainly due to the observation that reflection of solar radiation by low clouds decreases as temperature increases, holding all other cloud-controlling factors fixed. The positive feedback from temperature is partially offset by a negative feedback from the tendency for the inversion strength to increase in a warming world, with other cloud-controlling factors playing a smaller role. A consensus estimate from these studies for the contribution of tropical low clouds to the global mean cloud feedback is 0.25 ± 0.18 W m −2  K −1 (90% confidence interval), suggesting it is very unlikely that tropical low clouds reduce total global cloud feedback. Because the prediction of positive tropical low-cloud feedback with this approach is consistent with independent evidence from low-cloud feedback studies using high-resolution cloud models, progress is being made in reducing this key climate uncertainty.