The radiative response of tropical clouds to global warming exhibits a large spread among climate models, and this constitutes a major source of uncertainty for climate sensitivity estimates. To ...better interpret the origin of that uncertainty, we analyze the sensitivity of the tropical cloud radiative forcing to a change in sea surface temperature that is simulated by 15 coupled models simulating climate change and current interannual variability. We show that it is in regimes of large‐scale subsidence that the model results (1) differ the most in climate change and (2) disagree the most with observations in the current climate (most models underestimate the interannual sensitivity of clouds albedo to a change in temperature). This suggests that the simulation of the sensitivity of marine boundary layer clouds to changing environmental conditions constitutes, currently, the main source of uncertainty in tropical cloud feedbacks simulated by general circulation models.
This study diagnoses the climate sensitivity, radiative forcing and climate feedback estimates from eleven general circulation models participating in the Fifth Phase of the Coupled Model ...Intercomparison Project (CMIP5), and analyzes inter-model differences. This is done by taking into account the fact that the climate response to increased carbon dioxide (CO
2
) is not necessarily only mediated by surface temperature changes, but can also result from fast land warming and tropospheric adjustments to the CO
2
radiative forcing. By considering tropospheric adjustments to CO
2
as part of the forcing rather than as feedbacks, and by using the radiative kernels approach, we decompose climate sensitivity estimates in terms of feedbacks and adjustments associated with water vapor, temperature lapse rate, surface albedo and clouds. Cloud adjustment to CO
2
is, with one exception, generally positive, and is associated with a reduced strength of the cloud feedback; the multi-model mean cloud feedback is about 33 % weaker. Non-cloud adjustments associated with temperature, water vapor and albedo seem, however, to be better understood as responses to land surface warming. Separating out the tropospheric adjustments does not significantly affect the spread in climate sensitivity estimates, which primarily results from differing climate feedbacks. About 70 % of the spread stems from the cloud feedback, which remains the major source of inter-model spread in climate sensitivity, with a large contribution from the tropics. Differences in tropical cloud feedbacks between low-sensitivity and high-sensitivity models occur over a large range of dynamical regimes, but primarily arise from the regimes associated with a predominance of shallow cumulus and stratocumulus clouds. The combined water vapor plus lapse rate feedback also contributes to the spread of climate sensitivity estimates, with inter-model differences arising primarily from the relative humidity responses throughout the troposphere. Finally, this study points to a substantial role of nonlinearities in the calculation of adjustments and feedbacks for the interpretation of inter-model spread in climate sensitivity estimates. We show that in climate model simulations with large forcing (e.g., 4 × CO
2
), nonlinearities cannot be assumed minor nor neglected. Having said that, most results presented here are consistent with a number of previous feedback studies, despite the very different nature of the methodologies and all the uncertainties associated with them.
Anvil clouds cover extensive areas of the tropics, and their response to global warming can affect cloud feedbacks and climate sensitivity. A growing number of models and theories suggest that when ...the tropical atmosphere warms, anvil clouds rise and their coverage decreases, but observational support for this behavior remains limited. Here we use 10 years of measurements from the space‐borne CALIPSO lidar to analyze the vertical distribution of clouds and isolate the behavior of anvil clouds. On the interannual time scale, we find a strong evidence for anvil rise and coverage decrease in response to tropical warming. Using meteorological reanalyses, we show that this is associated with an increase in static stability and with a reduction in clear‐sky radiatively driven mass convergence at the anvil height. These relationships hold over a large range of spatial scales. This is consistent with the stability Iris mechanism suggested by theory and modeling studies.
Plain Language Summary
Anvil clouds cover about 40% of the tropics. Their response to global warming, especially changes in their height or in their horizontal extent, has the potential to affect the Earth's surface temperature. By analyzing 10 years of observations of the vertical distribution of clouds from a space‐borne lidar, we show that the anvils rise and reduce their coverage during the years that are anomalously warm. By using meteorological reanalyses, we further show that this behavior is consistent with the stability Iris effect suggested by theory and modeling studies. These results improve our physical understanding of the response of tropical clouds to warming and present relationships that may be used to test climate models.
Key Points
Space‐borne lidar observations show that anvil clouds rise and reduce their coverage when the tropics warm
Observations and meteorological reanalyses support the stability Iris effect mechanism
There is evidence for a stability Iris effect over a large range of spatial scales
The methods to quantify equilibrium climate sensitivity are still debated. We collect millennial length simulations of coupled climate models and show that the global mean equilibrium warming is ...higher than those obtained using extrapolation methods from shorter simulations. Specifically, 27 simulations with 15 climate models forced with a range of CO2 concentrations show a median 17% larger equilibrium warming than estimated from the first 150 years of the simulations. The spatial patterns of radiative feedbacks change continuously, in most regions reducing their tendency to stabilizing the climate. In the equatorial Pacific, however, feedbacks become more stabilizing with time. The global feedback evolution is initially dominated by the tropics, with eventual substantial contributions from the midlatitudes. Time dependent feedbacks underscore the need of a measure of climate sensitivity that accounts for the degree of equilibration, so that models, observations, and paleo proxies can be adequately compared and aggregated to estimate future warming.
Climate feedback analysis constitutes a useful framework for comparing the global mean surface temperature responses to an external forcing predicted by general circulation models (GCMs). ...Nevertheless, the contributions of the different radiative feedbacks to global warming (in equilibrium or transient conditions) and their comparison with the6 contribution of other processes (e.g., the ocean heat uptake) have not been quantified explicitly. Here these contributions from the classical feedback analysis framework are defined and quantified for an ensemble of 12 third phase of the Coupled Model Intercomparison Project (CMIP3)/Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) coupled atmosphere–ocean GCMs. In transient simulations, the multimodel mean contributions to global warming associated with the combined water vapor–lapse-rate feedback, cloud feedback, and ocean heat uptake are comparable. However, intermodel differences in cloud feedbacks constitute by far the most primary source of spread of both equilibrium and transient climate responses simulated by GCMs. The spread associated with intermodel differences in cloud feedbacks appears to be roughly 3 times larger than that associated either with the combined water vapor–lapse-rate feedback, the ocean heat uptake, or the radiative forcing.
Several studies have shown that most climate models underestimate cloud cover and overestimate cloud reflectivity, particularly for the tropical low‐level clouds. Here, we analyze the characteristics ...of low‐level tropical marine clouds simulated by six climate models, which provided COSP output within the CMIP6 project. CALIPSO lidar observations and PARASOL mono‐directional reflectance are used for model evaluation. It is found that the “too few, too bright” bias is still present for these models. The reflectance is particularly overestimated when cloud cover is low. Models do not simulate any optically thin clouds. They fail to reproduce the increasing cloud optical depth with increasing lower tropospheric stability as observed. These results suggest that most models do not sufficiently account for the effect of the small‐scale spatial heterogeneity in cloud properties or the variety of cloud types at the grid scale that is observed.
Plain Language Summary
Low‐level clouds are ubiquitous in the tropics and play an important role in Earth's radiative balance. Climate models do not explicitly resolve the main low‐level cloud formation processes, which must therefore be parameterized. This modeling work is difficult and in the previous generation of models low‐level clouds had a systematically too low fraction and too large brightness. This models' deficiency is known as the “too few too bright bias.” Here, we use six climate models of the latest generation that are compared to lidar and reflectance observations allowing for a detailed characterization of cloud properties. It is found that the too few too bright bias is still present for these models. Other common deficiencies in cloud simulation are revealed. At the daily time scale and models' grid scale, the lower the cloud cover, the greater the overestimation of the cloud brightness. Models do not simulate any thin clouds. They fail to reproduce the increasing cloud brightness with increasing stability of the lower troposphere as observed. The study suggests that most models do not sufficiently account for the variety of cloud properties and cloud types at the models' grid scale that is observed.
Key Points
The “too few too bright” bias is still present in six CMIP6 models for low‐level clouds
The overestimation of the low‐level cloud brightness gets higher as their cover is low
Models fail to reproduce the increasing cloud optical depth with increasing lower tropospheric stability as observed
The Global Land‐Atmosphere Climate Experiment–Coupled Model Intercomparison Project phase 5 (GLACE‐CMIP5) is a multimodel experiment investigating the impact of soil moisture‐climate feedbacks in ...CMIP5 projections. We present here first GLACE‐CMIP5 results based on five Earth System Models, focusing on impacts of projected changes in regional soil moisture dryness (mostly increases) on late 21st century climate. Projected soil moisture changes substantially impact climate in several regions in both boreal and austral summer. Strong and consistent effects are found on temperature, especially for extremes (about 1–1.5 K for mean temperature and 2–2.5 K for extreme daytime temperature). In the Northern Hemisphere, effects on mean and heavy precipitation are also found in most models, but the results are less consistent than for temperature. A direct scaling between soil moisture‐induced changes in evaporative cooling and resulting changes in temperature mean and extremes is found in the simulations. In the Mediterranean region, the projected soil moisture changes affect about 25% of the projected changes in extreme temperature.
Key Points
GLACE‐CMIP5 quantifies soil moisture feedbacks in climate projections
Impacts on late 21st century temperature and precipitation mean and extremes
Effects of about 25% for temperature extremes in Mediterranean region
Whereas it is well established that clouds are important to changes in Earth's surface temperature, their impact on changes of the large‐scale atmospheric circulation is less well understood. Here we ...study the radiative impact of clouds on the shift of the Intertropical Convergence Zone (ITCZ) in response to hemispheric surface albedo forcings. The problem is approached using aquaplanet simulations with four comprehensive atmosphere models. The radiative impact of clouds on the ITCZ shift differs in sign and magnitude across models and is responsible for half of the model spread in the ITCZ shift. The model spread is dominated by tropical clouds whose radiative impact is linked to the dependence of their cloud radiative properties on the circulation. The simulations not only demonstrate the importance of clouds for circulation changes but also propose a way to reduce the model uncertainty in ITCZ shifts.
Key Points
Radiative impact of clouds on ITCZ shift studied in climate models
Model spread in clouds is a dominant source for spread in ITCZ shift
Tuning the dependence of tropical clouds on circulation could reduce spread
We compare top‐of‐atmosphere (TOA) radiative fluxes observed by the Clouds and the Earth's Radiant Energy System (CERES) and simulated by seven general circulation models forced with observed ...sea‐surface temperature (SST) and sea‐ice boundary conditions. In response to increased SSTs along the equator and over the eastern Pacific (EP) following the so‐called global warming “hiatus” of the early 21st century, simulated TOA flux changes are remarkably similar to CERES. Both show outgoing shortwave and longwave TOA flux changes that largely cancel over the west and central tropical Pacific, and large reductions in shortwave flux for EP low‐cloud regions. A model's ability to represent changes in the relationship between global mean net TOA flux and surface temperature depends upon how well it represents shortwave flux changes in low‐cloud regions, with most showing too little sensitivity to EP SST changes, suggesting a “pattern effect” that may be too weak compared to observations.
Plain Language Summary
Earth's radiation budget describes the balance between radiation from the sun intercepted by Earth and radiation returned back to space through reflection of solar radiation and emission of terrestrial thermal infrared radiation. This balance is a fundamental property of Earth's climate system as it describes how Earth gains and sheds heat. Here we use observations from the Clouds and the Earth's Radiant Energy System (CERES) to evaluate how seven state‐of‐the‐art climate models represent changes in Earth's radiation budget during and following the so‐called global warming “hiatus” of the early 21st century. The models were provided observed sea‐surface temperature and sea‐ice boundary conditions as well as natural and anthropogenic forcings. We find remarkable agreement between observed and simulated differences in reflected solar and emitted thermal infrared radiation between the post‐hiatus and hiatus periods. Furthermore, a model's ability to correctly relate Earth's radiation budget and surface temperature is found to depend upon how well it represents reflected solar radiation changes in regions dominated by low clouds, particularly those over the eastern Pacific ocean.
Key Points
There is good agreement between radiation budget variations observed by CERES and simulated by seven state‐of‐the‐art climate models
The relationship between global mean net TOA radiation and surface temperature is sensitive to changes in regions dominated by low clouds
Most models underestimate shortwave flux changes in response to SST changes over the east Pacific, suggesting too weak a “pattern effect”
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