Search

Southern hemisphere subtropical anticyclones are projected to change in a warmer climate during both austral summer and winter. A recent study of CMIP 5 & 6 projections found a combination of local diabatic heating changes and static-stability-induced changes in baroclinic eddy growth as the dominant drivers. Yet the underlying mechanisms forcing these changes still remain uninvestigated. This study aims to enhance our mechanistic understanding of what drives these Southern Hemisphere anticyclones changes during both seasons. Using an AGCM, we decompose the response to CO2-induced warming into two components: (1) the fast atmospheric response to direct CO2 radiative forcing, and (2) the slow atmospheric response due to indirect sea surface temperature warming. Additionally, we isolate the influence of tropical diabatic heating with AGCM added heating experiments. As a complement to our numerical AGCM experiments, we analyze the Atmospheric and Cloud Feedback Model Intercomparison Project experiments. Results from sensitivity experiments show that slow subtropical sea surface temperature warming primarily forces the projected changes in subtropical anticyclones through baroclinicity change. Fast CO2 atmospheric radiative forcing on the other hand plays a secondary role, with the most notable exception being the South Atlantic subtropical anticyclone in austral winter, where it opposes the forcing by sea surface temperature changes resulting in a muted net response. Lastly, we find that tropical diabatic heating changes only significantly influence Southern Hemisphere subtropical anticyclone changes through tropospheric wind shear changes during austral winter. more...

Stomatal closure is a major physiological response to the increasing atmospheric carbon dioxide (CO2), which can lead to surface warming by regulating surface energy fluxes—a phenomenon known as CO2 physiological forcing. The magnitude of land surface warming caused by physiological forcing is substantial and varies across models. Here we assess the continental warming response to CO2 physiological forcing and quantify the resultant climate feedback using carbon–climate simulations from phases 5 and 6 of the Coupled Model Intercomparison Project, with a focus on identifying the cause of inter-model spread. It is demonstrated that the continental (40°–70°N) warming response to the physiological forcing in summer (~0.55 K) is amplified primarily due to cloud feedback (~1.05 K), whereas the other climate feedbacks, ranged from –0.57 K to 0.20 K, show relatively minor contributions. In addition, the strength of cloud feedback varies considerably across models, which plays a primary role in leading large diversity of the continental warming response to the physiological forcing. more...

The COVID-19 pandemic caused disruptions of public life and imposed lockdown measures in 2020 resulted in considerable reductions of anthropogenic aerosol emissions. It still remains unclear how the associated short-term changes in atmospheric chemistry influenced weather and climate on regional scales. To understand the underlying physical mechanisms, we conduct ensemble aerosol perturbation experiments with the Community Earth System Model, version 2. In the simulations reduced anthropogenic aerosol emissions in February generate anomalous surface warming and warm-moist air advection which promotes low-level cloud formation over China. Although the simulated response is weak, it is detectable in some areas, in qualitative agreement with the observations. The negative dynamical cloud feedback offsets the effect from reduced cloud condensation nuclei. Additional perturbation experiments with strongly amplified air pollution over China reveal a nonlinear sensitivity of regional atmospheric conditions to chemical/radiative perturbations. COVID-19-related changes in anthropogenic aerosol emissions provide an excellent testbed to elucidate the interaction between air pollution and climate. more...

This study reviews the research of the past 20-years on the role of anvil cirrus in the Earth’s climate – research initiated by Lindzen et al. (Bull. Am. Meteor. Soc. 82:417-432, 2001). The original study suggested that the anvil cirrus would shrink with warming, which was estimated to induce longwave cooling for the Earth. This is referred to as the iris effect since the areal change hypothetically resembles the light control by the human eye’s iris. If the effect is strong enough, it exerts a significant negative climate feedback which stabilizes tropical temperatures and limits climate sensitivity. Initial responses to Lindzen et al. (Bull. Am. Meteor. Soc. 82:417-432, 2001) denied the existence and effectiveness of the iris effect. Assessment of the debatable issues in these responses will be presented later in this review paper. At this point, the strong areal reduction of cirrus with warming appears very clearly in both climate models and satellite observations. Current studies found that the iris effect may not only come from the decreased cirrus outflow due to increased precipitation efficiency, but also from concentration of cumulus cores over warmer areas (the so-called aggregation effect). Yet, different opinions remain as to the radiative effect of cirrus clouds participating in the iris effect. For the iris effect to be most important, it must involve cirrus clouds that are not as opaque for visible radiation as they are for infrared radiation. However, current climate models often simulate cirrus clouds that are opaque in both visible and infrared radiation. This issue requires thorough examination as it seems to be opposed to conventional wisdom based on explicit observations. This paper was written in the hope of stimulating more effort to carefully evaluate these important issues. more...

Cloud radiative kernels were built by BCC_RAD (Beijing Climate Center radiative transfer model) radiative transfer code. Then, short-term cloud feedback and its mechanisms in East Asia (0.5°S–60.5°N, 69.5°–150.5°E) were analyzed quantitatively using the kernels combined with MODIS satellite data from July 2002 to June 2018. According to the surface and monsoon types, four subregions in East Asia—the Tibetan Plateau, northwest, temperate monsoon (TM), and subtropical monsoon (SM)—were selected. The average longwave, shortwave, and net cloud feedbacks in East Asia are −0.68 ± 1.20, 1.34 ± 1.08, and 0.66 ± 0.40 W m−2 K−1 (±2σ), respectively, among which the net feedback is dominated by the positive shortwave feedback. Positive feedback in SM is the strongest of all subregions, mainly due to the contributions of nimbostratus and stratus. In East Asia, short-term feedback in spring is primarily caused by marine stratus in SM, in summer is primarily driven by deep convective cloud in TM, in autumn is mainly caused by land nimbostratus in SM, and in winter is mainly driven by land stratus in SM. Cloud feedback in East Asia is chiefly driven by decreases in mid-level and low cloud fraction owing to the changes in relative humidity, and a decrease in low cloud optical thickness due to the changes in cloud water content. more...

Southern Ocean (SO) shortwave (SW) radiation biases are a common problem in contemporary general circulation models (GCMs), with most models exhibiting a tendency to absorb too much incoming SW radiation. These biases have been attributed to deficiencies in the representation of clouds during the austral summer months, either due to cloud cover or cloud optical thickness being too low. The problem has been the focus of many studies, most of which utilised satellite datasets for model evaluation. We use multi-year ship based observations and the CERES spaceborne radiation budget measurements to contrast cloud representation and SW radiation in the atmospheric component Global Atmosphere (GA) version 7.0 and 7.1 of the HadGEM3 GCM and the MERRA-2 reanalysis. We find that MERRA-2 is biased in the opposite direction to GA (reflects too much SW radiation). In addition, MERRA-2 performs better in terms of absolute SW bias than nudged runs of GA7.0 and GA7.1 in the 60–70° S latitude band. GA7.1 reduces the SO SW radiation biases relative to GA7.0, but significant errors remain at up to 20 W m−2 between 60 and 70° S in the austral summer months. Using ship-based ceilometer observations, we find low cloud below 2 km to be predominant in the Ross Sea and the Indian Ocean sector of the SO. Utilising a novel surface lidar simulator developed for this study, derived from an existing COSP-ACTSIM spaceborne lidar simulator, we find that GA7.0 and MERRA-2 both underestimate low cloud occurrence relative to the ship observations by 18–25 % on average, though the cloud cover in MERRA-2 is closer to observations by about 7 %. Based on radiosonde observations, we also find the low cloud to be strongly linked to boundary-layer atmospheric stability and the sea surface temperature. GA7.0 and MERRA-2 agree well with observations in terms of boundary-layer stability, suggesting that subgrid-scale parametrisations do not generate enough cloud in response to the thermodynamic profile of the atmosphere and the surface temperature. Our analysis shows that MERRA-2 has a much greater proportion of cloud liquid water in the SO in January than GA7.0, a likely key contributor to the difference in SW radiation. We show that boundary-layer stability and relative humidity fields are very similar in GA7.0 and MERRA-2, and unlikely to be the cause of the different cloud representation, suggesting that subgrid-scale parametrisations are responsible for the difference between the models. more...

A key contribution to the latest generation of climate projections for the UK (UKCP18) was a perturbed parameter ensemble (PPE) of global coupled models based on HadGEM3-GC3.05. Together with 13 CMIP5 simulations, this PPE provides users with a dataset that samples modelling uncertainty and is ideal for use in impacts studies. Evaluations of global mean surface temperatures for this PPE have shown twenty-first century warming rates consistently at the top end of the CMIP5 range. Here we investigate one potential contributory factor to this lack of spread: that the methodology to select plausible members from a larger, related PPE of atmosphere-only experiments preferentially ruled out those predicted to have more negative climate feedbacks (i.e. lower climate sensitivities). We confirm that this is indeed the case. We show that performance in extratropical long-wave cloud forcing played a key role in this by constraining ice cloud parameters, which in turn constrained the feedback distribution (though causal links are not established). The relatively weak relationship driving this constraint is shown to arise from stronger relationships for the long-wave and short-wave cloud feedback components, which largely cancel out due to changes in tropical high clouds. Moreover, we show that the strength of these constraints is due to a structural bias in extratropical long-wave cloud forcing across the PPE. We discuss how choices made in the methodology to pick the plausible PPE members may result in an overly strong constraint when there is a structural bias and possible improvements to this methodology for the future. more...

Low-level clouds over the tropical and sub-tropical oceans play a crucial role in the planetary radiative energy budget. However, they are challenging to model in climate simulations because they are affected by local processes that are still partially unknown. The control that mesoscale sea surface temperature structures have on the dynamics of the lower atmosphere on daily scales is emerging to be non-negligible and calls for more effort to be understood. During the EUREC4A field campaign, two of the research vessels (R/Vs) involved in the experiment sampled the edge of a cold mesoscale sea surface temperature (SST) patch in the north-western tropical Atlantic, crossing a gradient of roughly 0.75°C/100 km. The comprehensive set of instruments carried by the R/Vs allows an unprecedented characterization of the atmospheric response to the cold water forcing. The cold ocean patch weakens the vertical atmospheric mixing, reducing the boundary layer depth of roughly 200 m and the horizontal wind intensity of approximately 3 m s−1. At the same time, the humidity content in the sub-cloud layer increases and these conditions decrease the latent heat flux (by roughly 80 W m−2) and reduce vertical velocity fluctuations, making it less likely that moisture exceeds the lifting condensation level. As a consequence, fewer and thinner low-level clouds form over cold water. Independent satellite measurements are found to agree with the in-situ observations. The observed link between sea temperature and low-level clouds highlights its importance in the puzzle of modeling the sea-air-cloud interactions. Key Points Ship-based observations are used to characterize the lower atmospheric response to a cold patch in the north-western subtropical Atlantic Signatures in dynamical and thermodynamical atmospheric properties agree with a reduced vertical mixing over the cold patch Such a weaker vertical mixing is linked to a reduced shallow cloud cover because less moisture reaches the level of saturation Plain Language Summary Puffy clouds typically visible at sea strongly challenge climate models that struggle to represent their interaction with the sea surface and solar radiation. And as a consequence, these climate models cannot precisely estimate how much the Earth’s temperature will increase 100 years from now and its uncertainty. We went into the western Atlantic ocean for a month in Jan-Feb 2020 to measure sea surface temperature and cloud properties and observe how these changes occur. We saw clouds grow deeper over the warm water patches, holding more water and eventually raining. Weaker winds and more humid air occur on cold patches. Satellite observations seem to record the same behavior over a larger area in the same region. We detected a clear difference in cloud properties and amounts over warm and cold patches from all sensors, recording essential evidence of a feature that is hard to predict. We hope these observations will help to properly simulate the intensity and signs of low-cloud feedback over warm and cold oceanic patches of water to improve climate models. more...

Various studies reported an elevation dependent precipitation and temperature changes in mountainous regions of the world including the Himalayas. Various mechanisms are proposed to link the possible dependence of the precipitation and temperature on elevation with other variables, including, long- and short-wave radiation, albedo, clouds, humidity, etc. In the present study changes and trends of precipitation and temperature at different elevation ranges in the Indian Himalayan region (IHR) is assessed. Observations and modelling fields during the period 1970–2099 are used. Modelling simulations from the Coordinated Regional Climate Downscaling Experiment-South Asia experiments (CORDEX-SA) suites are considered. In addition, four seasons—winter (Dec, Jan, Feb: DJF), pre-monsoon (Mar, Apr, May: MAM), monsoon (Jun, Jul, Aug, Sep: JJAS) and post-monsoon (Oct, Nov: ON)—are considered to detect the possible seasonal response of elevation dependency. Firstly, precipitation and temperature fields, separately, as well as the diurnal temperature range (DTR) are assessed. Following, their long-term trends are investigated, if varying, at different elevational ranges in the IHR. To explain plausible physical mechanisms due to elevation dependency, trend of other variables viz., surface downward longwave radiation (DLR), total cloud faction, soil moisture, near surface specific humidity, surface snow melt and surface albedo, etc. are investigated. Results point towards an decreased (increased) precipitation in higher (lower) elevation. And amplified warming signals at higher elevations (above 3000 m), both in daytime and nighttime temperatures, during all seasons except the monsoon, are noticed. Increased DLR trends at higher elevation are also simulated well by the model and are likely the main elevation dependent driver in the IHR. more...

This study aims to create observation-based cloud radiative kernel (CRK) datasets and evaluate them by direct comparison of CRK and the CRK-derived cloud feedback datasets. Based on the Internation... more...

The daily cloud cycle or diurnal cloud cycle (DCC) and its response to global warming are critical to the Earth’s energy budget, but their radiative effects have not been systematically quantified. Toward this goal, here we analyze the radiation at the top of the atmosphere and propose a measure of the DCC radiative effect (DCCRE) as the difference between the total radiative fluxes with the full cloud cycle and its uniformly distributed cloud counterpart. When applied to the frequency of cloud occurrence, DCCRE is linked to the covariance between DCC and cloud radiative effects. Satellite observations show that the daily cloud cycle is strongly linked to pacific decadal oscillation (PDO) and climate hiatus, revealing its potential role in controlling climate variability. Climate model outputs show large inter-model spreads of DCCRE, accounting for approximately 20% inter-model spread of the cloud radiative effects. Climate models also suggest that while DCCRE is not sensitive to rising temperatures at the global scale, it can be important in certain regions. Such a framework can be used to conduct a more systematic evaluation of the DCC in climate models and observations with the goal to understand climate variability and reduce uncertainty in climate projections. more...

We ask what fundamental insights about the relationship of tropical convection to climate have arisen from recent investigations using simplified models. The vertical distribution of relative humidity should remain approximately constant in a changed climate. The temperature of clouds in the upper troposphere should also remain effectively constant for climate changes likely to occur in response to human-induced warming. The fractional coverage of convective clouds will likely decrease slightly with warming, but it is not known how the albedo and net radiative effect of tropical convective clouds will change. The areal extent and net radiative effect of tropical convective clouds depend on the interactions of radiation, cloud physics, and turbulence within the extended upper-level ice clouds. SST gradients develop naturally as a result of the aggregation of convection and large-scale thermodynamics and circulation act to couple the cloud properties and the SST. Radiative-convective equilibrium continues to provide insight into the structure and energy balance of the atmosphere by incorporating the interactions among radiation, cloud physics, and atmospheric motion. more...

Observations from multiple sensors on the NASA Aqua satellite are used to estimate the temporal and spatial variability of short-term cloud responses (CR) and cloud feedbacks λ for different cloud types, with respect to the interannual variability within the A-Train era (July 2002–June 2017). Short-term cloud feedbacks by cloud type are investigated both globally and locally by three different definitions in the literature: 1) the global-mean cloud feedback parameter λGG from regressing the global-mean cloud-induced TOA radiation anomaly ΔRG with the global-mean surface temperature change ΔTGS; 2) the local feedback parameter λLL from regressing the local ΔR with the local surface temperature change ΔTS; and 3) the local feedback parameter λGL from regressing global ΔRG with local ΔTS. Observations show significant temporal variability in the magnitudes and spatial patterns in λGG and λGL, whereas λLL remains essentially time invariant for different cloud types. The global-mean net λGG exhibits a gradual transition from negative to positive in the A-Train era due to a less negative λGG from low clouds and an increased positive λGG from high clouds over the warm pool region associated with the 2015/16 strong El Niño event. Strong temporal variability in λGL is intrinsically linked to its dependence on global ΔRG, and the scaling of λGL with surface temperature change patterns to obtain global feedback λGG does not hold. Despite the shortness of the A-Train record, statistically robust signals can be obtained for different cloud types and regions of interest. more...

Cloud distribution characteristics over the Tibetan Plateau in the summer monsoon period simulated by the Australian Community Climate and Earth System Simulator (ACCESS) model are evaluated using COSP [the CFMIP (Cloud Feedback Model Intercomparison Project) Observation Simulator Package]. The results show that the ACCESS model simulates less cumulus cloud at atmospheric middle levels when compared with observations from CALIPSO and CloudSat, but more ice cloud at high levels and drizzle drops at low levels. The model also has seasonal biases after the onset of the summer monsoon in May. While observations show that the prevalent high cloud at 9–10 km in spring shifts downward to 7–9 km, the modeled maximum cloud fractions move upward to 12–15 km. The reason for this model deficiency is investigated by comparing model dynamical and thermodynamical fields with those of ERA-Interim. It is found that the lifting effect of the Tibetan Plateau in the ACCESS model is stronger than in ERA-Interim, which means that the vertical velocity in the ACCESS model is stronger and more water vapor is transported to the upper levels of the atmosphere, resulting in more high-level ice clouds and less middle-level cumulus cloud over the Tibetan Plateau. The modeled radiation fields and precipitation are also evaluated against the relevant satellite observations. more...

A cloud feedback diagnostic package is implemented in the Australian Community Climate and Earth-System Simulator General Circulation Model, based on the methodology of “cloud radiative kernels.” Using separate increased sea surface temperature and CO 2 experiments, both the “rapid response” cloud contribution to forcing and temperature-mediated cloud feedbacks are analyzed. Under increased temperature and CO 2 changes, temperature-mediated cloud radiative feedback dominates over the rapid response in the final radiative response. Cloud feedback is positive in both long and short wave, with short wave dominating global values. Contributing most to this are low to mid-level clouds, of medium-to-high optical thickness. As a means of illustration of the methodology, a number of key parameters related to clouds, precipitation, and convection that are typically used in “tuning” in the model are modified. These changes result in substantial impacts on the model's current climate, but only modest changes to rapid response and feedbacks occur globally, regionally, and as a function of cloud optical thickness and height. This limited set of experiments shows that cloud adjustments and feedbacks in this model are robust under these changes, lending confidence that both model climate change projections and the conclusions of attribution studies are not overly sensitive to such parameterization tuning. Of course, a considerably larger set of experiments would be needed to demonstrate that feedbacks and rapid response are robust under the wider set of tuning adjustments commonly undertaken. more...

A calibrated single-model ensemble (SME) derived from the NCAR Community Atmosphere Model, version 3.1, is used to test two hypothesized emergent constraints on cloud feedback and equilibrium climate sensitivity (ECS). The Fasullo and Trenberth relative humidity (RH) metric and the Sherwood et al. lower-tropospheric mixing (LTMI) metric are computed for the present-day climate of the SME, and the relationships between the metrics, ECS, and cloud and other climate feedbacks are examined. The tropical convergence zone relative humidity (RHM) and the parameterized lower-tropospheric mixing (LTMIS) are positively correlated to ECS, and each is associated with a different spatial pattern of tropical shortwave cloud feedback in the SME. However, neither of those metrics is linked to the type of cloud response hypothesized by its authors. The resolved lower-tropospheric mixing (LTMID) is positively correlated to ECS for a subset of the SME having LTMID over a threshold value. LTMI and the RH for the dry, descending branch of the Hadley cell (RHD) narrow and shift upward the posterior estimates of ECS in the SME, but the SME bias in RHD and concerns over poorly understood physical mechanisms suggest the narrowing could be spurious for both constraints. While calibrated SME results may not generalize to multimodel ensembles, they can enhance the process understanding of emergent constraints and serve as out-of-sample tests of robustness. more...

Emergent constraints are quantities that are observable from current measurements and have skill predicting future climate. This study explores 19 previously proposed emergent constraints related to equilibrium climate sensitivity (ECS; the global-average equilibrium surface temperature response to CO2doubling). Several constraints are shown to be closely related, emphasizing the importance for careful understanding of proposed constraints. A new method is presented for decomposing correlation between an emergent constraint and ECS into terms related to physical processes and geographical regions. Using this decomposition, one can determine whether the processes and regions explaining correlation with ECS correspond to the physical explanation offered for the constraint. Shortwave cloud feedback is generally found to be the dominant contributor to correlations with ECS because it is the largest source of intermodel spread in ECS. In all cases, correlation results from interaction between a variety of terms, reflecting the complex nature of ECS and the fact that feedback terms and forcing are themselves correlated with each other. For 4 of the 19 constraints, the originally proposed explanation for correlation is borne out by our analysis. These four constraints all predict relatively high climate sensitivity. The credibility of six other constraints is called into question owing to correlation with ECS coming mainly from unexpected sources and/or lack of robustness to changes in ensembles. Another six constraints lack a testable explanation and hence cannot be confirmed. The fact that this study casts doubt upon more constraints than it confirms highlights the need for caution when identifying emergent constraints from small ensembles. more...

Low-level cloud feedbacks vary in magnitude but are positive in most climate models, due to reductions in low-level cloud fraction. This study explores the impact of surface evaporation on low-level cloud fraction feedback by performing climate change experiments with the aquaplanet configuration of the HadGEM2-A climate model, forcing surface evaporation to increase at different rates in two ways. Forcing the evaporation diagnosed in the surface scheme to increase at 7% K−1with warming (more than doubling the hydrological sensitivity) results in an increase in global mean low-level cloud fraction and a negative global cloud feedback, reversing the signs of these responses compared to the standard experiments. The estimated inversion strength (EIS) increases more rapidly in these surface evaporation forced experiments, which is attributed to additional latent heat release and enhanced warming of the free troposphere. Stimulating a 7% K−1increase in surface evaporation via enhanced atmospheric radiative cooling, however, results in a weaker EIS increase compared to the standard experiments and a slightly stronger low-level cloud reduction. The low-level cloud fraction response is predicted better by EIS than surface evaporation across all experiments. This suggests that surface-forced increases in evaporation increase low-level cloud fraction mainly by increasing EIS. Additionally, the results herein show that increases in surface evaporation can have a very substantial impact on the rate of increase in radiative cooling with warming, by modifying the temperature and humidity structure of the atmosphere. This has implications for understanding the factors controlling hydrological sensitivity. more...

Radiative feedbacks are known to determine climate sensitivity. Global top-of-atmosphere radiation correlations with surface temperature performed here show that decadal variability in surface temperature is also reinforced by strong positive feedbacks in models, both in the long wave (LW) and short wave (SW), offsetting much of the Planck radiative damping. Net top-of-atmosphere feedback is correlated with the magnitude of decadal temperature variability, particularly in the tropics. This indicates decadal-timescale radiative reinforcement of surface temperature variability. Assuming a simple global ocean mixed layer response, the reinforcement is found to be of a magnitude comparable to that required for typical decadal global scale anomalies. The magnitude of decadal variability in the tropics is uncorrelated with LW feedbacks, but it is correlated with total SW feedbacks, which are, in turn, correlated with tropical SW cloud feedback. Globally, water vapour/lapse rate, surface albedo and cloud feedbacks on decadal timescales are, on average, as strong as those operating under climate change. Together these results suggest that some of the physical processes responsible for setting the magnitude of global temperature change in the twenty-first century and climate sensitivity also help set the magnitude of the natural decadal variability. Furthermore, a statistically significant correlation exists between climate sensitivity and decadal variability in the tropics across CMIP5 models, although this is not apparent in the earlier generation of CMIP3 models. Thus although the link to sensitivity is not conclusive, this opens up potential paths to improve our understanding of climate feedbacks, climate sensitivity and decadal climate variability, and has the potential to reduce the associated uncertainty. more...

The sensitivity in detecting thin clouds of the cloud screening method being used in the CM SAF cloud, albedo and surface radiation data set from AVHRR data (CLARA-A2) cloud climate data record (CDR) has been evaluated using cloud information from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the CALIPSO satellite. The sensitivity, including its global variation, has been studied based on collocations of Advanced Very High Resolution Radiometer (AVHRR) and CALIOP measurements over a 10-year period (2006–2015). The cloud detection sensitivity has been defined as the minimum cloud optical thickness for which 50 % of clouds could be detected, with the global average sensitivity estimated to be 0.225. After using this value to reduce the CALIOP cloud mask (i.e. clouds with optical thickness below this threshold were interpreted as cloud-free cases), cloudiness results were found to be basically unbiased over most of the globe except over the polar regions where a considerable underestimation of cloudiness could be seen during the polar winter. The overall probability of detecting clouds in the polar winter could be as low as 50 % over the highest and coldest parts of Greenland and Antarctica, showing that a large fraction of optically thick clouds also remains undetected here. The study included an in-depth analysis of the probability of detecting a cloud as a function of the vertically integrated cloud optical thickness as well as of the cloud's geographical position. Best results were achieved over oceanic surfaces at mid- to high latitudes where at least 50 % of all clouds with an optical thickness down to a value of 0.075 were detected. Corresponding cloud detection sensitivities over land surfaces outside of the polar regions were generally larger than 0.2 with maximum values of approximately 0.5 over the Sahara and the Arabian Peninsula. For polar land surfaces the values were close to 1 or higher with maximum values of 4.5 for the parts with the highest altitudes over Greenland and Antarctica. It is suggested to quantify the detection performance of other CDRs in terms of a sensitivity threshold of cloud optical thickness, which can be estimated using active lidar observations. Validation results are proposed to be used in Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulation Package (COSP) simulators for cloud detection characterization of various cloud CDRs from passive imagery. more...

An atmospheric general circulation model (AGCM) is forced with patterns of observed sea surface temperature (SST) change and those output from atmosphere–ocean GCM (AOGCM) climate change simulations to demonstrate a strong dependence of climate feedback on the spatial structure of surface temperature change. Cloud and lapse rate feedbacks are found to vary the most, depending strongly on the pattern of tropical Pacific SST change. When warming is focused in the southeast tropical Pacific—a region of climatological subsidence and extensive marine low cloud cover—warming reduces the lower-tropospheric stability (LTS) and low cloud cover but is largely trapped under an inversion and hence has little remote effect. The net result is a relatively weak negative lapse rate feedback and a large positive cloud feedback. In contrast, when warming is weak in the southeast tropical Pacific and enhanced in the west tropical Pacific—a strong convective region—warming is efficiently transported throughout the free troposphere. The increased atmospheric stability results in a strong negative lapse rate feedback and increases the LTS in low cloud regions, resulting in a low cloud feedback of weak magnitude. These mechanisms help explain why climate feedback and sensitivity change on multidecadal time scales in AOGCM abrupt4xCO2simulations and are different from those seen in AGCM experiments forced with observed historical SST changes. From the physical understanding developed here, one should expect unusually negative radiative feedbacks and low effective climate sensitivities to be diagnosed from real-world variations in radiative fluxes and temperature over decades in which the eastern Pacific has lacked warming. more...

Differences among climate models in equilibrium climate sensitivity (ECS; the equilibrium surface temperature response to a doubling of atmospheric CO2) remain a significant barrier to the accurate assessment of societally important impacts of climate change. Relationships between ECS and observable metrics of the current climate in model ensembles, so-called emergent constraints, have been used to constrain ECS. Here a statistical method (including a backward selection process) is employed to achieve a better statistical understanding of the connections between four recently proposed emergent constraint metrics and individual feedbacks influencing ECS. The relationship between each metric and ECS is largely attributable to a statistical connection with shortwave low cloud feedback, the leading cause of intermodel ECS spread. This result bolsters confidence in some of the metrics, which had assumed such a connection in the first place. Additional analysis is conducted with a few thousand artificial metrics that are randomly generated but are well correlated with ECS. The relationships between the contrived metrics and ECS can also be linked statistically to shortwave cloud feedback. Thus, any proposed or forthcoming ECS constraint based on the current generation of climate models should be viewed as a potential constraint on shortwave cloud feedback, and physical links with that feedback should be investigated to verify that the constraint is real. In addition, any proposed ECS constraint should not be taken at face value since other factors influencing ECS besides shortwave cloud feedback could be systematically biased in the models. more...

This paper introduces an idealized general circulation model (GCM) in which water vapor and clouds are tracked as tracers, but are not allowed to affect circulation through either latent heat release or cloud radiative effects. The cloud scheme includes an explicit treatment of cloud microphysics and diagnoses cloud fraction from a prescribed subgrid distribution of total water. The model is capable of qualitatively capturing many large-scale features of water vapor and cloud distributions outside of the boundary layer and deep tropics. The subtropical dry zones, midlatitude storm tracks, and upper-tropospheric cirrus are simulated reasonably well. The inclusion of cloud microphysics (namely rain re-evaporation) has a modest but significant effect of moistening the lower troposphere in this model. When being subjected to a uniform fractional increase of saturated water vapor pressure, the model produces little change in cloud fraction. A more realistic perturbation, which considers the nonlinearity of the Clausius–Clapeyron relation and spatial structure of CO2-induced warming, results in a substantial reduction in the free-tropospheric cloud fraction. This is reconciled with an increase of relative humidity by analyzing the probability distributions of both quantities, and may help explain partly similar decreases in cloud fraction in full GCMs. The model provides a means to isolate individual processes or model components for studying their influences on cloud simulation in the extratropical free troposphere. more...

We examine the effects of non-linear interactions between surface albedo, water vapor and cloud cover (referred to as climate variables) on amplified warming of the polar regions, using a new energy balance model. Our simulations show that the sum of the contributions to surface temperature changes due to any variable considered in isolation is smaller than the temperature changes from coupled feedback simulations. This non-linearity is strongest when all three climate variables are allowed to interact. Surface albedo appears to be the strongest driver of this non-linear behavior, followed by water vapor and clouds. This is because increases in longwave radiation absorbed by the surface, related to increases in water vapor and clouds, and increases in surface absorbed shortwave radiation caused by a decrease in surface albedo, amplify each other. Furthermore, our results corroborate previous findings that while increases in cloud cover and water vapor, along with the greenhouse effect itself, warm the polar regions, water vapor also significantly warms equatorial regions, which reduces polar amplification. Changes in surface albedo drive large changes in absorption of incoming shortwave radiation, thereby enhancing surface warming. Unlike high latitudes, surface albedo change at low latitudes are more constrained. Interactions between surface albedo, water vapor and clouds drive larger increases in temperatures in the polar regions compared to low latitudes. This is in spite of the fact that, due to a forcing, cloud cover increases at high latitudes and decreases in low latitudes, and that water vapor significantly enhances warming at low latitudes. more...

Radiative kernels are used to quantify the instantaneous radiative forcing of aerosols and the aerosol-mediated cloud response in coupled ocean–atmosphere model simulations under both historical and future emission scenarios. The method is evaluated using matching pairs of historical climate change experiments with and without aerosol forcing and accurately captures the spatial pattern and global-mean effects of aerosol forcing. It is shown that aerosol-driven changes in the atmospheric circulation induce additional cloud changes. Thus, the total aerosol-mediated cloud response consists of both local microphysical changes and nonlocal dynamical changes that are driven by hemispheric asymmetries in aerosol forcing. By comparing coupled and fixed sea surface temperature (SST) simulations with identical aerosol forcing, the relative contributions of these two components are isolated, exploiting the ability of prescribed SSTs to also suppress changes in the atmospheric circulation. The radiative impact of the dynamical cloud changes is found to be comparable in magnitude to that of the microphysical cloud changes and acts to further amplify the interhemispheric asymmetry of the aerosol radiative forcing. The dynamical cloud response is closely linked to the meridional displacement of the Hadley cell, which, in turn, is driven by changes in the cross-equatorial energy transport. In this way, the dynamical cloud changes act as a positive feedback on the meridional displacement of the Hadley cell, roughly doubling the projected changes in cross-equatorial energy transport compared to that from the microphysical changes alone. more...

This paper reports on a new index for low cloud cover (LCC), the estimated cloud-top entrainment index (ECTEI), which is a modification of estimated inversion strength (EIS) and takes into account a cloud-top entrainment (CTE) criterion. Shipboard cloud observation data confirm that the index is strongly correlated with LCC. It is argued here that changes in LCC cannot be fully determined from changes in EIS only, but can be better determined from changes in both EIS and sea surface temperature (SST) based on the ECTEI. Furthermore, it is argued that various proposed predictors of LCC change, including the moist static energy vertical gradient, SST, and midlevel clouds, can be better understood from the perspective of the ECTEI. more...

Over the tropical Atlantic during boreal spring, average interhemispheric differences in sea-surface temperature (SST) coincide with a coherent pattern of interannual climate variability often referred to as the Atlantic Meridional Mode. This includes anomalous SST and sea-level pressure roughly anti-symmetric about the equator, as well as cross-equatorial near-surface winds directed toward the warmer hemisphere. Within subtropical marine boundary layer cloud regions in both hemispheres, enhanced cloudiness associated with this variability is co-located with cool SST, a strong temperature inversion, and cold horizontal surface temperature advection, while reduced cloudiness is associated with the opposite meteorological conditions. This is indicative a positive cloud feedback that reinforces the underlying SST anomalies. The simulation of this feedback varies widely among models participating in phase 5 of the Coupled Model Intercomparison Project. Models that fail to simulate this feedback substantially underestimate the amplitudes of typical tropical Atlantic interhemispheric variability in cloudiness off of the equator, SST, and atmospheric circulation. Models that correctly reproduce a positive cloud feedback generally produce higher and more realistic amplitudes of variability, but with substantial scatter. Marine boundary layer clouds therefore appear to be a key element of springtime coupled atmosphere–ocean variability over the tropical Atlantic. A markedly more successful simulation of this variability in climate models may be obtained by better representing boundary layer cloud processes. more...

Cloud-circulation feedback by latent heating (LH) is a major contributor for driving atmospheric circulation. This study examines the potential role of spatial variations of LH in driving a mini-circulation for generating the “pool of inhibited cloudiness”, where cloud formation in the lower and middle troposphere is significantly inhibited over the southwest Bay of Bengal (BoB) during the Indian summer monsoon. Spaceborne observations show that LH rates in the deep convective regions of the head BoB are as high as 0.2 K/h, while that over the “pool” are about 5 times smaller. This differential heating results in modulating the mean circulation. 20 years of reanalysis data show good correlation between (a) upper troposphere (300 hPa) convergence and lower tropospheric (1000 hPa) divergence at the “pool” and (b) lower tropospheric divergence at the “pool” and lower tropospheric convergence at the head BoB as well as at the west coast of India. Besides the orographic influence, a portion of the air mass descending at the “pool” arises from deep convective regions in the north BoB and equatorial trough. This subsidence is responsible for the persistent inhibition to cloud formation at the “pool”. This case forms a classic example of the cloud-circulation feedback. more...

Cloud response to Earth’s changing climate is one of the largest sources of uncertainty among global climate model (GCM) projections. Two of the largest sources of uncertainty are the spread in equilibrium climate sensitivity (ECS) and uncertainty in radiative forcing due to uncertainty in the aerosol indirect effect. Satellite instruments with sufficient accuracy and on-orbit stability to detect climate change–scale trends in cloud properties will improve confidence in the understanding of the relationship between observed climate change and cloud property trends, thus providing information to better constrain ECS and radiative forcing. This study applies a climate change uncertainty framework to quantify the impact of measurement uncertainty on trend detection times for cloud fraction, effective temperature, optical thickness, and water cloud effective radius. Although GCMs generally agree that the total cloud feedback is positive, disagreement remains on its magnitude. With the climate uncertainty framework, it is demonstrated how stringent measurement uncertainty requirements for reflected solar and infrared satellite measurements enable improved constraint of SW and LW cloud feedbacks and the ECS by significantly reducing trend uncertainties for cloud fraction, optical thickness, and effective temperature. The authors also demonstrate improved constraint on uncertainty in the aerosol indirect effect by reducing water cloud effective radius trend uncertainty. more...

Arctic climate change in winter is tightly linked to changes in the strength of surface temperature inversions, which occur frequently in the present climate as Arctic air masses form during polar night. Recent work proposed that, in a warmer climate, increasing low-cloud optical thickness of maritime air advected over high-latitude landmasses during polar night could suppress the formation of Arctic air masses, amplifying winter warming over continents and sea ice. But this mechanism was based on single-column simulations that could not assess the role of fractional cloud cover change. This paper presents two-dimensional cloud-resolving model simulations that support the single-column model results: low-cloud optical thickness and duration increase strongly with initial air temperature, slowing the surface cooling rate as the climate is warmed. The cloud-resolving model cools less at the surface than the single-column model, and the sensitivity of its cooling to warmer initial temperatures is also higher, because it produces cloudier atmospheres with stronger lower-tropospheric mixing and distributes cloud-top cooling over a deeper atmospheric layer with larger heat capacity. Resolving larger-scale cloud turbulence has the greatest impact on the microphysics schemes that best represent general observed features of mixed-phase clouds, increasing their sensitivity to climate warming. These findings support the hypothesis that increasing insulation of the high-latitude land surface by low clouds in a warmer world could act as a strong positive feedback in future climate change and suggest studying Arctic air formation in a three-dimensional climate model. more...

Global coupled climate models have large long-standing cloud and radiation biases, calling into question their ability to simulate climate and climate change. This study assesses the impact of reducing shortwave radiation biases on climate sensitivity within the Community Earth System Model (CESM). The model is modified by increasing supercooled cloud liquid to better match absorbed shortwave radiation observations over the Southern Ocean while tuning to reduce a compensating tropical shortwave bias. With a thermodynamic mixed-layer ocean, equilibrium warming in response to doubled CO2 increases from 4.1 K in the control to 5.6 K in the modified model. This 1.5 K increase in equilibrium climate sensitivity is caused by changes in two extratropical shortwave cloud feedbacks. First, reduced conversion of cloud ice to liquid at high southern latitudes decreases the magnitude of a negative cloud phase feedback. Second, warming is amplified in the mid-latitudes by a larger positive shortwave cloud feedback. The positive cloud feedback, usually associated with the subtropics, arises when sea surface warming increases the moisture gradient between the boundary layer and free troposphere. The increased moisture gradient enhances the effectiveness of mixing to dry the boundary layer, which decreases cloud amount and optical depth. When a full-depth ocean with dynamics and thermodynamics is included, ocean heat uptake preferentially cools the mid-latitude Southern Ocean, partially inhibiting the positive cloud feedback and slowing warming. Overall, the results highlight strong connections between Southern Ocean mixed-phase cloud partitioning, cloud feedbacks, and ocean heat uptake in a climate forced by greenhouse gas changes. more...

Just as the iris of human eye controls the light influx (iris effect), tropical anvil cirrus clouds may regulate the Earth's surface warming by controlling outgoing longwave radiation. This study examines this possible effect with monthly satellite observations such as Tropical Rainfall Measuring Mission (TRMM) precipitation, Moderate Resolution Imaging Spectroradiometer cirrus fraction, and Clouds and the Earth's Radiant Energy System top-of-the-atmosphere radiative fluxes averaged over different tropical domains from March 2000 to October 2014. To confirm that high-level cirrus is relevant to this study, Cloud-Aerosol Lidar with Orthogonal Polarization high cloud observations were also analyzed from June 2006 to December 2015. Our analysis revealed that the increase in sea surface temperature in the tropical western Pacific tends to concentrate convective cloud systems. This concentration effect very likely induces the significant reduction of both stratiform rain rate and cirrus fraction, without appreciable change in the convective rain rate. This reduction of stratiform rain rate and cirrus fraction cannot be found over its subregion or the tropical eastern Pacific, where the concentration effect of anvil cirrus is weak. Consistently, over the tropical western Pacific, the higher ratio of convective rain rate to total rain rate (i.e., precipitation efficiency) significantly correlates with warmer sea surface temperature and lower cirrus fraction. The reduced cirrus eventually increased outgoing longwave radiation to a greater degree than absorbed solar radiation. Finally, the negative relationship between precipitation efficiency and cirrus fraction tends to correspond to a low global equilibrium climate sensitivity in the models in the Coupled Model Intercomparison Project Phase 5. This suggests that tropical anvil cirrus clouds exert a negative climate feedback in strong association with precipitation efficiency. more...

This study examines at the process level the climate difference between 2002–13 and 1984–95 in ERA-Interim. A linearized radiative transfer model is used to calculate the temperature change such that its thermal radiative cooling would balance the energy flux perturbation associated with the change of an individual process, without regard to what causes the change of the process in the first place. The global mean error of the offline radiative transfer model calculations is 0.09 K, which corresponds to the upper limit of the uncertainties from a single term in the decomposition analysis. The process-based decomposition indicates that the direct effect of the increase of CO2 (0.15 K) is the largest contributor to the global warming between the two periods (about 0.27 K). The second and third largest contributors are the cloud feedback (0.14 K) and the combined effect of the oceanic heat storage and evaporation terms (0.11 K), respectively. The largest warming associated with the oceanic heat storage term is found in the tropical Pacific and Indian Oceans, with relatively weaker warming over the tropical Atlantic Ocean. The increase in atmospheric moisture adds another 0.1 K to the global surface warming, but the enhancement in tropical convections acts to reduce the surface warming by 0.17 K. The ice-albedo and atmospheric dynamical feedbacks are the two leading factors responsible for the Arctic polar warming amplification (PWA). The increase of atmospheric water vapor over the Arctic region also contributes substantially to the Arctic PWA pattern. more...

Uncertainty in the equilibrium climate sensitivity (ECS) of the Earth continues to be large. Aspects of the cloud feedback problem have been identified as fundamental to the uncertainty in ECS. Recent analyses have shown that changes to cloud forcing with climate change can be decomposed into contributions from changes in cloud occurrence that are proportional to globally averaged temperature change and changes associated with rapid adjustments in the system that are independent of changes to globally averaged surface temperature. Together these responses enhance warming due to (1) cloud feedback from increasing cloud altitude by upper tropospheric clouds and (2) decreases in cloud coverage by marine boundary layer clouds. We argue that active remote sensing from space can play a unique and crucial role in constraining our understanding of these separate phenomena. For 1, the feedback associated with changing tropical cirrus is predicted to emerge from the statistical noise of the climate system within the next one to two decades. However, active remote sensing will need to continue for that signal to be observed since accurate placement of these clouds in the vertical dimension is necessary. For 2, the processes associated with changes to marine boundary layer clouds have been linked to the coupling between cloud and precipitation microphysics and air motions over remote ocean basins where precipitation formation in shallow convection is modulated by changes to aerosols and thermodynamics. Exploiting the synergy in combined active and passive remote sensing is likely one of the only ways of constraining our evolving theoretical understanding of low-level cloud processes as represented in cloud-resolving models and for validating global-scale models. more...

This study proposes the generality of surface air temperature (SAT)–atmospheric circulation feedback during high-temperature weather in late July 2003 over East China by using the Advanced Research Weather Research and Forecasting model (WRF; Version 3) simulations with a succession of 24-h integrations, i.e. on a daily scale, the SAT increase leads to a weakened ridge of the western Pacific subtropical high in the lower troposphere (i.e. negative feedback), whereas it leads to a strengthened ridge in the upper troposphere (i.e. positive feedback) and vice versa. Additionally, using the balance equation of temperature, the feedbacks are clarified from the diurnal-variation perspective. This shows many complex details, e.g. the changes in geopotential heights are more complex than those in air temperatures, and the overall daily feedback appears to be dominated by the feedback during the phase with intense daytime surface heating. All of the WRF-modified land surface conditions can lead to large changes in the maximum, minimum, and average SATs over the mean diurnal scale, with generally larger differences induced by land surface schemes than those induced by initial soil moisture, suggesting that the SAT–circulation feedback can be greatly reduced (or amplified) by different land conditions over the diurnal weather scale and that diurnal variations could substantially contribute to longer timescale climate. more...

Coincident instantaneous broadband radiation budget measurements from Clouds and Earth's Radiant Energy System and cloud vertical structure information from CloudSat-Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations radar-lidar observations are combined to study the relationship of cloud vertical structure to top-of-atmosphere energy balance fluctuations. Varying optical and physical thickness of high ice clouds produces most of the covariation between albedo and outgoing longwave radiation in regions of tropical convection. Rainy cores of tropical convective clouds have a negative impact on the radiation balance, while nonprecipitating anvil clouds have a positive effect. The effect of anvil clouds on the radiative heating profile is to warm near cloud base and cool near cloud top, and to reduce the radiative cooling rate in the clear air below the cloud. The cooling rate in the clear air below the anvil is reduced to small values for moderately thick anvils, and the driving of instability in the anvil itself also saturates for relatively thin clouds. It is hypothesized that the dependence of radiative heating on cloud thickness may be important in driving the distribution of tropical cloud structures toward one that produces net neutrality of the cloud radiative effect at the top-of-the-atmosphere, as is found in regions of deep convection over ocean areas with high and relatively uniform surface temperatures. This idea is tested with a single-column model, which indicates that cloud-radiation interactions affect anvil cloud properties, encouraging further investigation of the hypothesis. more...

Whether a cloud is predominantly water or ice strongly influences interactions between clouds and radiation coming down from the Sun or up from the Earth. Being able to simulate cloud phase transitions accurately in climate models based on observational data sets is critical in order to improve confidence in climate projections, because this uncertainty contributes greatly to the overall uncertainty associated with cloud-climate feedbacks. Ultimately, it translates into uncertainties in Earth's sensitivity to higher CO2 levels. While a lot of effort has recently been made toward constraining cloud phase in climate models, more remains to be done to document the radiative properties of clouds according to their phase. Here we discuss the added value of a new satellite data set that advances the field by providing estimates of the cloud radiative effect as a function of cloud phase and the implications for climate projections. more...

Intermodel compensation between cloud feedback and rapid cloud adjustment has important implications for the range of model-inferred climate sensitivity. Although this negative intermodel correlation exists in both realistic (e.g., coupled ocean–atmosphere models) and idealized (e.g., aqua-planet) model configurations, the compensation appears to be stronger in the latter. The cause of the compensation between feedback and adjustment, and its dependence on model configuration remain poorly understood. In this study, we examine the characteristics of the cloud feedback and adjustment in model simulations with differing complexity, and analyze the causes responsible for their compensation. We show that in all model configurations, the intermodel compensation between cloud feedback and cloud adjustment largely results from offsetting changes in marine boundary-layer clouds. The greater prevalence of these cloud types in aqua-planet models is a likely contributor to the larger correlation between feedback and adjustment in those configurations. It is also shown that differing circulation changes in the aqua-planet configuration of some models act to amplify the intermodel range and sensitivity of the cloud radiative response by about a factor of 2. more...

Despite the increasing sophistication of climate models, the amount of surface warming expected from a doubling of atmospheric CO $$_2$$ (equilibrium climate sensitivity) remains stubbornly uncertain, in part because of differences in how models simulate the change in global albedo due to clouds (the shortwave cloud feedback). Here, model differences in the shortwave cloud feedback are found to be closely related to the spatial pattern of the cloud contribution to albedo ( $$\alpha$$ ) in simulations of the current climate: high-feedback models exhibit lower (higher) $$\alpha$$ in regions of warm (cool) sea-surface temperatures, and therefore predict a larger reduction in global-mean $$\alpha$$ as temperatures rise and warm regions expand. The spatial pattern of $$\alpha$$ is found to be strongly predictive ( $$r=0.84$$ ) of a model’s global cloud feedback, with satellite observations indicating a most-likely value of $$0.58\pm 0.31$$ Wm $$^{-2}$$ K $$^{-1}$$ (90% confidence). This estimate is higher than the model-average cloud feedback of 0.43 Wm $$^{-2}$$ K $$^{-1}$$ , with half the range of uncertainty. The observational constraint on climate sensitivity is weaker but still significant, suggesting a likely value of 3.68 ± 1.30 K (90% confidence), which also favors the upper range of model estimates. These results suggest that uncertainty in model estimates of the global cloud feedback may be substantially reduced by ensuring a realistic distribution of clouds between regions of warm and cool SSTs in simulations of the current climate. more...

The high-latitude climate system contains complicated, but largely veiled physical feedback processes. Climate predictions remain uncertain, especially for the Northern High Latitudes (NHL; north of 60°N), and observational constraint on climate modeling is vital. This study estimates local radiative feedbacks for NHL based on the CERES/Terra satellite observations during March 2000–November 2014. The local shortwave (SW) and longwave (LW) radiative feedback parameters are calculated from linear regression of radiative fluxes at the top of the atmosphere on surface air temperatures. These parameters are estimated by the de-seasonalization and 12-month moving average of the radiative fluxes over NHL. The estimated magnitudes of the SW and the LW radiative feedbacks in NHL are 1.88 ± 0.73 and 2.38 ± 0.59 W m−2 K−1, respectively. The parameters are further decomposed into individual feedback components associated with surface albedo, water vapor, lapse rate, and clouds, as a product of the change in climate variables from ERA-Interim reanalysis estimates and their pre-calculated radiative kernels. The results reveal the significant role of clouds in reducing the surface albedo feedback (1.13 ± 0.44 W m−2 K−1 in the cloud-free condition, and 0.49 ± 0.30 W m−2 K−1 in the all-sky condition), while the lapse rate feedback is predominant in LW radiation (1.33 ± 0.18 W m−2 K−1). However, a large portion of the local SW and LW radiative feedbacks were not simply explained by the sum of these individual feedbacks. more...

Climate modes of variability over the Atlantic and Pacific may be amplified by a positive feedback between sea-surface temperature (SST) and marine boundary layer clouds. However, it is well known that climate models poorly simulate this feedback. Does this deficiency contribute to model-to-model differences in the representation of climate modes of variability? Over both the North Atlantic and Pacific, typical summertime interannual to interdecadal SST variability exhibits horseshoe-like patterns of co-located anomalies of shortwave cloud radiative effect (CRE), low-level cloud fraction, SST, and estimated inversion strength over the subtropics and midlatitudes that are consistent with a positive cloud feedback. During winter over the midlatitudes, this feedback appears to be diminished. Models participating in the Coupled Model Intercomparison Project phase 5 that simulate a weak feedback between subtropical SST and shortwave CRE produce smaller and less realistic amplitudes of summertime SST and CRE variability over the northern oceans compared to models with a stronger feedback. The change in SST amplitude per unit change in CRE amplitude among the models and observations may be understood as the temperature response of the ocean mixed layer to a unit change in radiative flux over the course of a season. These results highlight the importance of boundary layer clouds in interannual to interdecadal atmosphere–ocean variability over the northern oceans during summer. The results also suggest that deficiencies in the simulation of these clouds in coupled climate models contribute to underestimation in their simulation of summer-to-summer SST variability. more...

Models disagree on a significant number of responses to climate change, such as climate feedback, regional changes, or the strength of equilibrium climate sensitivity. Emergent constraints aim to reduce these uncertainties by finding links between the inter-model spread in an observable predictor and climate projections. In this paper, the concepts underlying this framework are recalled with an emphasis on the statistical inference used for narrowing uncertainties, and a review of emergent constraints found in the last two decades. Potential links between highlighted predictors are explored, especially those targeting uncertainty reductions in climate sensitivity, cloud feedback, and changes of the hydrological cycle. Yet the disagreement across emergent constraints suggests that the spread in climate sensitivity can not be significantly narrowed. This calls for weighting the realism of emergent constraints by quantifying the level of physical understanding explaining the relationship. This would also permit more efficient model evaluation and better targeted model development. In the context of the upcoming CMIP6 model intercomparison a growing number of new predictors and uncertainty reductions is expected, which call for robust statistical inferences that allow cross-validation of more likely estimates. more...

Numerical simulations are performed to investigate the radiative and cloud microphysical effects (direct and indirect effects respectively) of the Saharan dust aerosols and the subsequent perturbations of the radiation budget over the tropical East Atlantic Ocean. Simulations are conducted for July 1–31, 2010 over three two-way nested domains covering 0–25°N, 30–60°W using the Weather Research and Forecasting model coupled with Chemistry module (WRF-Chem-V3.6.1). Simulations of the dust direct effect over the outermost domain suggest that the dust-induced lower level heating increases the stability of the lower troposphere and reduces the cloud cover (up to 9%) underneath the maximum dust layer. Once the direct and indirect effects are considered together, dust particles act as cloud condensation nuclei and produce smaller sized cloud droplets. Overall, for the innermost domain, the mean cloud droplet radius becomes ~14% smaller in the presence of dust (12.4 μm and 10.7 μm in dust-free and dust-laden conditions respectively). Contrary to the direct effect, the coupled direct and indirect effects of dust not only reduces (up to 17%) the cloud cover below the maximum dust layer but also enhances (up to 9%) the cloud cover above the dust layers. The direct radiative forcing of dust excluding (including) cloud feedback are −13.66 (−4.83) and −11.25 (−1.22) W/m2 at the surface and at the top of the atmosphere, respectively. Coupled direct and indirect effects of dust result in the net radiative forcing of dust to −8.14 and −5.03 W/m2 at the surface and at the top of the atmosphere, respectively. more...