Cloud Feedback Research Articles

On the Importance of a Geostationary View for Tropical Cloud Feedback

AbstractThis study shows that geostationary satellites are critical to estimate the accurate cloud feedback strength over the tropical western Pacific (TWP). Cloud feedback strength was calculated by the simultaneous relation between cloud cover and sea surface temperature (SST) over the TWP [120°E–170°E, 20°S–20°N]. During 2011–2018, the cloud cover was obtained by geostationary earth orbit satellite (GEO) and low‐level earth orbit satellite (LEO) (AGEO, ALEO), and the NOAA's all‐sky SST (To) was weighted with the clear‐sky fraction observed by GEO and LEO (TwGEO; TwLEO). The linear regression coefficients between clouds and SST are very different: −7.93%K−1 (AGEO/TwGEO), −6.94%K−1 (ALEO/TwGEO), −1.35%K−1 (AGEO/TwLEO), −0.69%K−1 (ALEO/TwLEO), −0.02 %K−1 (AGEO/To), and −0.50 %K−1 (ALEO/To). Among these, only the TwGEO values provided a valid cloud feedback signal. This is because GEO's field of view is large enough to simultaneously capture cloud cover over the entire TWP.

Cloud properties and their projected changes in CMIP models with low to high climate sensitivity

Abstract. Since the release of the first Coupled Model Intercomparison Project version 6 (CMIP6) simulations, one of the most discussed topics is the higher effective climate sensitivity (ECS) of some of the models, resulting in an increased range of ECS values in CMIP6 compared to previous CMIP phases. An important contribution to ECS is the cloud climate feedback. Although climate models have continuously been developed and improved over the last few decades, a realistic representation of clouds remains challenging. Clouds contribute to the large uncertainties in modeled ECS, as projected changes in cloud properties and cloud feedbacks also depend on the simulated present-day fields. In this study, we investigate the representation of both cloud physical and radiative properties from a total of 51 CMIP5 and CMIP6 models. ECS is used as a simple metric to group the models, as the sensitivity of the physical cloud properties to warming is closely related to cloud feedbacks, which in turn are known to have a large contribution to ECS. Projected changes in the cloud properties in future scenario simulations are analyzed by the ECS group. In order to help with interpreting the projected changes, model results from historical simulations are also analyzed. The results show that differences in the net cloud radiative effect as a reaction to warming among the three model groups are driven by changes in a range of cloud regimes rather than individual regions. In polar regions, high-ECS models show a weaker increase in the net cooling effect of clouds, due to warming, than the low-ECS models. At the same time, high-ECS models show a decrease in the net cooling effect of clouds over the tropical ocean and the subtropical stratocumulus regions, whereas low-ECS models show either little change or even an increase in the cooling effect. Over the Southern Ocean, the low-ECS models show a higher sensitivity of the net cloud radiative effect to warming than the high-ECS models.

Observing the LMC with APEX: Signatures of large-scale feedback in the molecular clouds of 30 Doradus

Context. Stellar feedback plays a crucial role in star formation and the life cycle of molecular clouds. The intense star formation region 30 Doradus, which is located in the Large Magellanic Cloud (LMC), is a unique target for detailed investigation of stellar feedback owing to the proximity of the hosting galaxy and modern observational capabilities that together allow us to resolve individual molecular clouds – nurseries of star formation. Aims. We study the impact of large-scale feedback on the molecular gas using the new observational data in the 12CO(3 − 2) line obtained with the APEX telescope. Methods. Our data cover an unprecedented area of 13.8 sq. deg. of the LMC disc with a spatial resolution of 5 pc and provide an unbiased view of the molecular clouds in the galaxy. Using these data, we located molecular clouds in the disc of the galaxy, estimated their properties, such as the areal number density, relative velocity and separation, width of the line profile, CO line luminosity, size, and virial mass, and compared these properties of the clouds of 30 Doradus with those in the rest of the LMC disc. Results. We find that, compared with the rest of the observed molecular clouds in the LMC disc, those in 30 Doradus show the highest areal number density; they are spatially more clustered, they move faster with respect to each other, and they feature larger linewidths. In parallel, we do not find statistically significant differences in such properties as the CO line luminosity, size, and virial mass between the clouds of 30 Doradus and the rest of the observed field. Conclusions. We interpret our results as signatures of gas dispersal and fragmentation due to high-energy large-scale feedback.

Atmosphere and ocean energy transport in extreme warming scenarios

Extreme scenarios of global warming out to 2300 from the SSP5-8.5 extension scenario are analyzed in three state-of-the-art climate models, including two models with climate sensitivity greater than 4.5°C. The result is some of the largest warming amounts ever seen in simulations run over the historical record and into the future. The simulations exhibit between 9.3 and 17.5°C global mean temperature change between pre-Industrial and the end of the 23rd century. The extremely large changes in global temperature allow exploration of fundamental questions in climate dynamics, such as the determination of moisture and energy transports, and their relation to global atmosphere-ocean circulation. Three models performed simulations of SSP5-8.5 to 2300: MRI-ESM2-0, IPSL-CM6A-LR, and CanESM5. We analyze these simulations to improve understanding of climate dynamics, rather than as plausible futures. In the model with the most warming, CanESM5, the moisture content of the planet more than doubles, and the hydrologic cycle increases in intensity. In CanESM5 and IPSL-CM6A-LR nearly all sea ice is eliminated in both summer and winter in both hemispheres. In all three models, the Hadley circulation weakens, the tropopause height rises, and storm tracks shift poleward, to varying degrees. We analyze the moist static energy transports in the simulations using a diffusive framework. The dry static energy flux decreases to compensate for the increased moisture transport; however the compensation is imperfect. The total atmospheric transport increases but not as quickly as expected with a constant diffusivity. The decrease in eddy intensity plays an important role in determining the energy transports, as do the pattern of cloud feedbacks and the strength of ocean circulations.

Larger Cloud Liquid Water Enhances Both Aerosol Indirect Forcing and Cloud Radiative Feedback in Two Earth System Models

AbstractPrevious studies have noticed that the Coupled Model Intercomparison Project Phase 6 (CMIP6) models with a stronger cooling from aerosol‐cloud interactions (ACI) also have an enhanced warming from positive cloud feedback, and these two opposing effects are counter‐balanced in simulations of the historical period. However, reasons for this anti‐correlation are less explored. In this study, we perturb the cloud ice microphysical processes to obtain cloud liquid of varying amounts in two Earth System Models (ESMs). We find that the model simulations with a larger liquid water path (LWP) tend to have a stronger cooling from ACI and a stronger positive cloud feedback. More liquid clouds in the mean‐state present more opportunities for anthropogenic aerosol perturbations and also weaken the negative cloud feedback at middle to high latitudes. This work, from a cloud state perspective, emphasizes the influence of the mean‐state LWP on effective radiative forcing due to ACI (ERFACI).

Comparison of Short‐Term Cloud Feedbacks at Top of the Atmosphere and the Surface in Observations and AMIP6 Models

AbstractWe compared short‐term cloud feedback, defined at the top of the atmosphere (TOA), the atmospheric column (ATM), and the surface (SFC), between observations and models participating in Atmospheric Model Intercomparison Project Phase 6 (AMIP6) for the period 2000–2014. The globally averaged net cloud feedbacks observed at TOA, ATM, and SFC are −0.06 ± 0.63, −0.17 ± 0.70, and 0.11 ± 0.81 W m−2 K−1, respectively. While most models produced TOA cloud feedbacks that agreed with the observations within uncertainty ranges, the intermodel spread at SFC and within ATM was relatively larger. This demonstrates that models are diverse in how their TOA feedback is distributed between ATM and SFC. Because short‐term cloud feedback is mainly driven by El Niño–Southern Oscillation (ENSO), the global‐mean cloud feedback was further decomposed into components from the ENSO and non‐ENSO regions. Results show that cloud feedback in these two regions tends to be inversely related. Compared to observations, almost all models overestimated the longwave cloud feedback in the ENSO region due to the overestimation of cloud amount changes for high‐topped clouds. For these models, it is the offset between deviations in ENSO and non‐ENSO regions that leads to the overall agreement of global mean with observations. Sensitivity tests show that the main conclusions still hold when alternative kernels are used in estimating cloud feedback.

Evaluating Cloud Feedback Components in Observations and Their Representation in Climate Models

AbstractThis study quantifies the contribution of individual cloud feedbacks to the total short‐term cloud feedback in satellite observations over the period 2002–2014 and evaluates how they are represented in climate models. The observed positive total cloud feedback is primarily due to positive high‐cloud altitude, extratropical high‐ and low‐cloud optical depth, and land cloud amount feedbacks partially offset by negative tropical marine low‐cloud feedback. Seventeen models from the Atmosphere Model Intercomparison Project of the sixth Coupled Model Intercomparison Project are analyzed. The models generally reproduce the observed moderate positive short‐term cloud feedback. However, compared to satellite estimates, the models are systematically high‐biased in tropical marine low‐cloud and land cloud amount feedbacks and systematically low‐biased in high‐cloud altitude and extratropical high‐ and low‐cloud optical depth feedbacks. Errors in modeled short‐term cloud feedback components identified in this analysis highlight the need for improvements in model simulations of the response of high clouds and tropical marine low clouds. Our results suggest that skill in simulating interannual cloud feedback components may not indicate skill in simulating long‐term cloud feedback components.

ENSO Disrupts Boreal Winter CRE Feedback

Abstract Twenty years of satellite-based cloud and radiation observations allow us to examine the observed cloud radiative effect (CRE) feedback (i.e., CRE change per unit change in global mean surface temperature). By employing a decomposition method to separate the contribution of “internal changes” and “relative-frequency-of-occurrence (RFO) changes” of distinct cloud regime (CR) groups, notable seasonal contrasts of CRE feedback characteristics emerge. Boreal winter CRE feedback is dominated by the positive shortwave CRE (SWCRE) feedback of oceanic low-thick clouds, due to their decreasing RFO as temperature rises. This signal is most likely due to El Niño–Southern Oscillation (ENSO) activity. When ENSO signals are excluded, boreal winter CRE feedback becomes qualitatively similar to the boreal summer feedback, where several CR groups contribute to the total CRE feedback more evenly. Most CR groups’ CRE feedbacks largely come from changing RFO (e.g., the predominant transition from oceanic cumulus to broken clouds and more occurrences of higher convective clouds with warming temperature). At the same time, low-thick and broken clouds experience optical thinning and decreasing cloud fraction, and these features are more prominent in boreal summer than winter. Overall, the seasonally asymmetric patterns of CRE feedback, primarily due to ENSO, introduce complexity in assessments of CRE feedback.

Seasonal Variations and Spatial Patterns of Arctic Cloud Changes in Association with Sea Ice Loss during 1950–2019 in ERA5

Abstract The dynamic and thermodynamic mechanisms that link retreating sea ice to increased Arctic cloud amount and cloud water content are unclear. Using the fifth generation of the ECMWF Reanalysis (ERA5), the long-term changes between years 1950–79 and 1990–2019 in Arctic clouds are estimated along with their relationship to sea ice loss. A comparison of ERA5 to CERES satellite cloud fractions reveals that ERA5 simulates the seasonal cycle, variations, and changes of cloud fraction well over water surfaces during 2001–20. This suggests that ERA5 may reliably represent the cloud response to sea ice loss because melting sea ice exposes more water surfaces in the Arctic. Increases in ERA5 Arctic cloud fraction and water content are largest during October–March from ∼950 to 700 hPa over areas with significant (≥15%) sea ice loss. Further, regions with significant sea ice loss experience higher convective available potential energy (∼2–2.75 J kg−1), planetary boundary layer height (∼120–200 m), and near-surface specific humidity (∼0.25–0.40 g kg−1) and a greater reduction of the lower-tropospheric temperature inversion (∼3°–4°C) than regions with small (<15%) sea ice loss in autumn and winter. Areas with significant sea ice loss also show strengthened upward motion between 1000 and 700 hPa, enhanced horizontal convergence (divergence) of air, and decreased (increased) relative humidity from 1000 to 950 hPa (950–700 hPa) during the cold season. Analyses of moisture divergence, evaporation minus precipitation, and meridional moisture flux fields suggest that increased local surface water fluxes, rather than atmospheric motions, provide a key source of moisture for increased Arctic clouds over newly exposed water surfaces during October–March. Significance Statement Sea ice loss has been shown to be a primary contributor to Arctic warming. Despite the evidence linking large sea ice retreat to Arctic warming, some studies have suggested that enhanced downwelling longwave radiation associated with increased clouds and water vapor is the primary reason for Arctic amplification. However, it is unclear how sea ice loss is linked to changes in clouds and water vapor in the Arctic. Here, we investigate the relationship between Arctic sea ice loss and changes in clouds using the ERA5 dataset. Improved knowledge of the relationship between Arctic sea ice loss and changes in clouds will help further our understanding of the role of the cloud feedback in Arctic warming.

Understanding changes in cloud simulations from E3SM version 1 to version 2

Abstract. This study documents clouds simulated by the Energy Exascale Earth System Model (E3SM) version 2 (E3SMv2) and attempts to understand what causes the model behavior change in clouds relative to E3SMv1. This is done by analyzing the last 30-year (1985–2014) data from the 165-year historical simulations using E3SMv1 and v2 and four sensitivity tests to isolate the impact of changes in model parameter choices in its turbulence, shallow convection, and cloud macrophysics parameterization (Cloud Layers Unified By Binormals, CLUBB); microphysical parameterization (MG2); and deep-convection scheme (ZM), as well as model physics changes in convective triggering. It is shown that E3SMv2 significantly improves the simulation of subtropical coastal stratocumulus clouds and clouds with optical depth larger than 3.6 over the stratocumulus-to-cumulus transition regimes, where the shortwave cloud radiative effect (SWCRE) is also improved, and the Southern Ocean (SO) while seeing an overall slight degradation in low clouds over other tropical and subtropical oceans. The better performance in E3SMv1 over those regions is partially due to error compensation between its simulated optically thin and intermediate low clouds for which E3SMv2 actually improves simulation of optically intermediate low clouds. Sensitivity tests indicate that the changes in low clouds are primarily due to the tuning done in CLUBB. The impact of the ZM tuning is mainly on optically intermediate and thick high clouds, contributing to an improved SWCRE and longwave cloud radiative effect (LWCRE). The impact of the MG2 tuning and the new convective trigger is primarily on the high latitudes and the SO. They have a relatively smaller impact on clouds than CLUBB tuning and ZM tuning do. This study offers additional insights into clouds simulated in E3SMv2 by utilizing multiple data sets and the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP) diagnostic tool as well as sensitivity tests. The improved understanding will benefit future E3SM developments.

Perturbing Parameters to Understand Cloud Contributions to Climate Change

Abstract The sensitivity of cloud feedbacks to atmospheric model parameters is evaluated using a CAM6 perturbed parameter ensemble (PPE). The CAM6 PPE perturbs 45 parameters across 262 simulations, 206 of which are used here. The spread in the total cloud feedback and its six components across the CAM6 PPE are comparable to the spread across the CMIP6 and AMIP ensembles, indicating that parametric uncertainty mirrors structural uncertainty. However, the high-cloud altitude feedback is generally larger in the CAM6 PPE than WCRP assessment, CMIP6, and AMIP values. We evaluate the influence of each of the 45 parameters on the total cloud feedback and each of the six cloud feedback components. We also explore whether the CAM6 PPE can be used to constrain the total cloud feedback, with inconclusive results. Further, we find that despite the large parametric sensitivity of cloud feedbacks in CAM6, a substantial increase in cloud feedbacks from CAM5 to CAM6 is not a result of changes in parameter values. Notably, the CAM6 PPE is run with a more recent version of CAM6 (CAM6.3) than was used for AMIP (CAM6.0) and has a smaller total cloud feedback (0.56 W m−2 K−1) as compared to CAM6.0 (0.81 W m−2 K−1) owing primarily to reductions in low clouds over the tropics and midlatitudes. The work highlights the large sensitivity of cloud feedbacks to both parameter values and structural details in CAM6.

Causes of Reduced Climate Sensitivity in E3SM From Version 1 to Version 2

AbstractThe effective climate sensitivity in the Department of Energy's Energy Exascale Earth System Model (E3SM) has decreased from 5.3 K in version 1 to 4.0 K in version 2. This reduction is mainly due to a weaker positive cloud feedback that leads to a stronger negative radiative feedback. Present‐day atmosphere‐only experiments with uniform 4 K sea surface temperature warming are used to separate the contributions of individual model modifications to the reduced cloud feedback. We find that the reduced cloud feedback is mostly driven by changes over the tropical marine low cloud regime, mainly related to a new trigger function for the deep convection scheme and modifications in the cloud microphysics scheme. The new trigger function helps weaken the low cloud reduction by increasing the cloud water detrainment at low levels from deep convection under warming. Changes to the formula of autoconversion rate from liquid to rain and an introduced minimum cloud droplet number concentration threshold in cloud microphysical calculations help sustain clouds against dissipation by suppressing precipitation generation with warming. In the midlatitudes, the increased Wegener‐Bergeron‐Findeisen (WBF) efficiency strongly reduces present‐day liquid water and leads to a stronger negative cloud optical depth feedback. The reduced trade cumulus cloud feedback in v2 is closer to estimates from recent observational and large‐eddy modeling studies but might not be due to the right physical reasons. The reduced mid‐latitude cloud feedback may be more plausible because more realistic present‐day mixed‐phase clouds are produced through the change in the WBF efficiency.

Declining Geoengineering Efficacy Caused by Cloud Feedbacks in Transient Solar Dimming Experiments

Abstract Solar radiation management (SRM) with injections of aerosols into the stratosphere has emerged as a research area of focus with the potential to cool the planet. However, the amount of SRM required to achieve a given level of cooling, and how this relationship evolves in response to increasing greenhouse gas emissions, remains uncertain. Here, we explore the evolution of solar dimming efficacy over time by defining and quantifying a new SRM feedback term, which is analogous to conventional radiative feedbacks. Using Earth system model simulations that dynamically adjust the amount of insolation to offset global mean warming from increasing CO2, we find that positive SRM feedbacks decrease global planetary albedo and diminish the efficacy of solar dimming. Physically, the decrease in albedo is primarily due to reductions in optically thick tropical cloud fraction in the boundary layer and midtroposphere, which is driven by a drying and destabilization of the tropical mid- to lower troposphere. These results offer an energetic explanation for reduced cloud fraction commonly observed in idealized SRM experiments, as well as reaffirm the need to understand the troposphere response, particularly from clouds, in realizable geoengineering experiments and their potential to feed back onto SRM efficacy. Significance Statement The goal of this study is to understand how the effectiveness of solar geoengineering may evolve over time. Using a climate model with the ability to directly tune the amount of incoming sunlight, we explore the potential for feedback loops in the climate system to diminish or amplify the desired effect of solar tuning, which is to offset greenhouse gas–induced warming. For this climate model and this solar geoengineering proxy, in particular, we find that feedback loops reduce Earth’s albedo and therefore diminish the desired effect of turning down the sun over time. This study lays the groundwork for understanding potential feedback loops in climate model simulations that represent solar geoengineering in a more realistic way.

Climate Change Response of Tropical Atlantic Clouds in a Kilometer‐Resolution Model

AbstractEstimates of the tropical cloud feedback of global climate models (GCMs) show a large inter‐model spread due to the small‐scale nature of convective cloud processes. Estimates from large‐eddy simulations (LES) are more consistent among themselves, but difficult to scale to the climate system. Here we consider a compromise between GCMs and LES, and study how tropical clouds over the Atlantic respond to a climate perturbation in a regional kilometer‐resolution model. We perform two 4‐year‐long simulations at 3.3 km horizontal grid spacing with the limited‐area model COSMO on a 9,000 × 7,000 km2 domain covering the tropical Atlantic: a control simulation and a climate change simulation using the pseudo‐global warming approach. In a previous publication we have demonstrated that this approach yields a credible representation of the tropical climate without the double‐ITCZ bias commonly seen in GCMs. Here we address the cloud feedback and find a reduction of ITCZ high‐cloud cover resulting in a negative longwave cloud feedback similar to the CMIP6 ensemble mean. We find a reduction of stratocumulus clouds, which we argue is primarily a thermodynamic response. More surprisingly, the shallow cumulus cloud cover over the West Atlantic increases, which we argue is due to increased stability resulting in weaker entrainment and a more humid boundary layer. The mean shortwave cloud feedback over the tropical Atlantic is positive, comparable to the CMIP6 ensemble mean. The emerging estimate of the total cloud‐radiative feedback over the Atlantic is slightly negative, consistent with CMIP6 GCMs, but it is substantially stronger than that of the driving GCM.

What Are the Main Causes of Positive Subtropical Low Cloud Feedbacks in Climate Models?

AbstractWe investigate positive subtropical low cloud feedback mechanisms in climate models which have performed the CMIP6/CFMIP‐3 AMIP and AMIP uniform +4K experiments while saving CFMIP‐3 process diagnostics on model levels. Our analysis focuses on the trade cumulus/stratocumulus transition region between California and Hawaii, where positive low cloud feedbacks are present in the JJA season. We introduce a methodology to test various positive cloud feedback mechanisms proposed in the literature as the main causes of the low cloud responses in the models. Causal hypotheses are tested by comparing their predictions with the models' responses of clouds, cloud controlling factors, boundary layer depth and temperature/humidity tendencies to climate warming. Changes in boundary layer depth, relative humidity in the cloud layer, convective moistening rate and large‐scale humidity advection at the top of the boundary layer are shown to be crucial for identifying the main causes of the low cloud reductions in the models. For the cases examined, our approach narrows down the seven mechanisms considered to between one and three remaining candidates for each model. No single mechanism considered can explain the feedback in all of the models at the locations examined, but the surface latent heat flux/convective entrainment mechanism remains a candidate for BCC‐CSM2‐MR, IPSL‐CM6A‐LR, and MRI‐ESM2.0, while the surface upwelling longwave mechanism remains for CESM2, HadGEM3‐GC3.1‐LL, and MIROC6.

Global and Regional Climate Feedbacks in Response to Uniform Warming and Cooling

AbstractWe compare the radiative feedbacks in an ensemble of global climate models under uniform 4 K warming and cooling of sea surface temperatures. The global‐mean net feedback is less stabilizing under warming in all nine models. This results primarily from less stabilizing water vapor and extra‐tropical shortwave cloud feedbacks, partially offset by more stabilizing tropical cloud feedbacks. The zonal‐mean feedbacks are also robust across the ensemble. In the extra‐tropics, the less stabilizing shortwave cloud feedback under warming is associated with further poleward migration of the mean Southern Hemisphere jet in some models. However, additional experiments with an aquaplanet version of the HadGEM3 model suggest that the asymmetry of the jet shift is not driving the asymmetry in the cloud feedbacks at these latitudes. In the tropics, the stronger water vapor feedback under warming is offset by weaker shortwave cloud feedbacks. The result is that the ensemble spread in the differences between the global feedbacks under warming and cooling is mainly driven by their differences in the tropics. The spatial distribution of the feedbacks largely reflects the zonal‐mean behavior, although there is considerable model spread in the regional cloud feedbacks, particularly in the tropical shortwave cloud feedback. Comparison with CO2‐ and solar‐forced coupled experiments suggests that the global‐mean longwave cloud feedback is nearly invariant to warming and cooling, regardless of the nature of the forcing. The shortwave cloud feedback is generally more positive under warming in the coupled models, consistent with the uniform SST perturbation experiments.

Anomalous Meltwater From Ice Sheets and Ice Shelves Is a Historical Forcing

AbstractRecent mass loss from ice sheets and ice shelves is now persistent and prolonged enough that it impacts downstream oceanographic conditions. To demonstrate this, we use an ensemble of coupled GISS‐E2.1‐G simulations forced with historical estimates of anomalous freshwater, in addition to other climate forcings, from 1990 through 2019. There are detectable differences in zonal‐mean sea surface temperatures (SST) and sea ice in the Southern Ocean, and in regional sea level around Antarctica and in the western North Atlantic. These impacts mostly improve the model's representation of historical changes, including reversing the forced trends in Antarctic sea ice. The changes in SST may have implications for estimates of the SST pattern effect on climate sensitivity and for cloud feedbacks. We conclude that the changes are sufficiently large that model groups should strive to include more accurate estimates of these drivers in all‐forcing historical simulations in future coupled model intercomparisons.

Surface Temperature Pattern Scenarios Suggest Higher Warming Rates Than Current Projections

AbstractAtmosphere‐ocean general circulation models (AOGCMs) struggle to reproduce recently observed sea surface temperature (SST) trend patterns. Here, we quantify the relevance of this SST pattern uncertainty to global‐mean temperature projections through convolving Green's functions with SST pattern scenarios that differ from the ones AOGCMs produce by themselves. We find that future SST pattern uncertainty has a significant impact on projections, such as increasing total model uncertainty by 40% in a high‐emissions scenario by 2085. A reversal of the current cooling trend in the East Pacific over the next few decades could lead to a period of global‐mean warming with a 60% higher rate than currently projected. SST pattern uncertainty works through a destabilization of the shortwave cloud feedback to affect temperature projections. It is critical for climate change impact, adaptation, and mitigation assessments to incorporate this previously unaccounted for uncertainty until we trust the evolution of SST patterns in AOGCMs.

The Temperature Control of Cloud Adiabatic Fraction and Coverage

AbstractThe fraction of cloud water compared to its adiabatic value is defined as the adiabatic fraction, fad. The accuracy of cloud representation in climate models is highly sensitive to mixing rate, manifested in fad. Here, we present the first fad distribution of marine boundary layer clouds over global oceans, retrieved by satellite observations. The fad is shown to decrease exponentially with cloud base temperature (CBT) and cloud depth, in agreement with the increasing evaporation capacity of entrained warmer air. Cloud cover decreases with increasing CBT, but to a much lesser extent than fad. The dependence of fad on CBT has little dependence on relative humidity or precipitation. The relationship between CBT and fad highlights the importance of CBT as a core control factor on cloud evaporation. The simultaneous decrease in cloud water content and cover with increasing CBT can lead to positive cloud feedback, resulting in greater future climate warming.

Explicitly Resolved Cloud Feedbacks in the Radiative‐Convective Equilibrium Model Intercomparison Project

AbstractRadiative‐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.