Shallowness of tropical low clouds as a predictor of climate models’ response to warming

Brient, Florent; Schneider, Tapio; Tan, Zhihong; Bony, Sandrine; Qu, Xiaoshu; Hall, Alex

doi:10.1007/s00382-015-2846-0

Cited by 120 publications

(174 citation statements)

References 79 publications

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“…Recent work has increasingly highlighted the critical role of cloud base cloudiness in determining the climate sensitivity of GCMs (Brient et al, 2015;Vial et al, 2017). The atmospheric stability (EIS or LTS) provides an excellent diagnostic tool with which to determine how parameterized turbulence and convection influence the low-level atmospheric temperature.…”

Section: Discussionmentioning

confidence: 99%

The Diversity of Cloud Responses to Twentieth Century Sea Surface Temperatures

Silvers

Paynter

Zhao

2018

Geophysical Research Letters

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Low‐level clouds are shown to be the conduit between the observed sea surface temperatures (SST) and large decadal fluctuations of the top of the atmosphere radiative imbalance. The influence of low‐level clouds on the climate feedback is shown for global mean time series as well as particular geographic regions. The changes of clouds are found to be important for a midcentury period of high sensitivity and a late century period of low sensitivity. These conclusions are drawn from analysis of amip‐piForcing simulations using three atmospheric general circulation models (AM2.1, AM3, and AM4.0). All three models confirm the importance of the relationship between the global climate sensitivity and the eastern Pacific trends of SST and low‐level clouds. However, this work argues that the variability of the climate feedback parameter is not driven by stratocumulus‐dominated regions in the eastern ocean basins, but rather by the cloudy response in the rest of the tropics.

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Section: Discussionmentioning

confidence: 99%

The Diversity of Cloud Responses to Twentieth Century Sea Surface Temperatures

Silvers

Paynter

Zhao

2018

Geophysical Research Letters

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“…Indeed the cloud fraction near the inversion level appears to be more variable than that at cloud base (Nuijens et al 2014), varies strongly with the intensity of the convective mass flux (e.g., Brient et al 2016;Vial et al 2016) and strongly influences the variations of the total cloud cover (Rodts et al 2003). The cloud fraction near the inversion level will be estimated through different methods.…”

Section: Estimating the Distribution Of Clouds In The Trade-wind Bounmentioning

confidence: 99%

“…Their response to global warming is thus critical for global-mean cloud feedbacks, and actually it is their differing response to warming that explains most of the spread of climate sensitivity across climate models (Bony et al 2004;Bony and Dufresne 2005;Webb et al 2006;Medeiros et al 2008;Vial et al 2013;Boucher et al 2013;Medeiros et al 2015). Model diversity in the strength of the vertical mixing of water vapour within the first few kilometres above the ocean surface (in association with both convective and large-scale circulations) is thought to explain half of the variance in climate sensitivity estimates across models (Sherwood et al 2014): the lower-tropospheric mixing dehydrates the cloud layer near its base at an increasing rate as the climate warms and this rate scales with the mixing strength in the current climate (Sherwood et al (2014); Gettelman et al (2012); Tomassini et al (2015); Brient et al (2016); Stevens et al (2016); Vial et al (2016), Fig. 1).…”

Section: Introductionmentioning

confidence: 99%

EUREC4A: A Field Campaign to Elucidate the Couplings Between Clouds, Convection and Circulation

et al. 2017

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Trade-wind cumuli constitute the cloud type with the highest frequency of occurrence on Earth, and it has been shown that their sensitivity to changing environmental conditions will critically influence the magnitude and pace of future global warming. Research over the last decade has pointed out the importance of the interplay between clouds, convection and circulation in controling this sensitivity. 123Surv Geophys (2017) 38:1529-1568 https://doi.org/10.1007/s10712-017-9428-0 cumuli at cloud base is very sensitive to changes in environmental conditions, while process models suggest the opposite. To understand and resolve this contradiction, we propose to organize a field campaign aimed at quantifying the physical properties of tradecumuli (e.g., cloud fraction and water content) as a function of the large-scale environment. Beyond a better understanding of clouds-circulation coupling processes, the campaign will provide a reference data set that may be used as a benchmark for advancing the modelling and the satellite remote sensing of clouds and circulation. It will also be an opportunity for complementary investigations such as evaluating model convective parameterizations or studying the role of ocean mesoscale eddies in air-sea interactions and convective organization.

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“…It has been hypothesized that as SSTs rise, enhanced mixing of the boundary layer air with the drier free troposphere dries out the cloud layer and results in less clouds [e.g., Rieck et al, 2012]. Brient et al [2016] showed that models with a pronounced maximum in low cloud amount at cloud base are most susceptible to convective drying, but not through a reduction of clouds throughout the cloud layer, as shown by Rieck et al [2012], rather by a reduction of cloud amount at cloud base. This effect is pronounced in our simulations, and is robust as it appears irrespective of the domain size.…”

Section: Journal Of Advances In Modeling Earth Systems 101002/2016msmentioning

confidence: 99%

“…However, the total response of low clouds to warming in GCMs results from a balance between drying from the convective parameterization and moistening by the turbulence parameterization. Different balances between these processes were argued [Brient et al, 2016;Sherwood et al, 2014] to be one of the primary factors leading to the spread of total feedback in CMIP models. All of our simulations show (Figure 9) a uniform decrease of cloud liquid water (0.6 km) and a decrease with height of low-level water vapor in response to warming but the response of cloud cover and RH is not systematic across domains.…”

Section: Journal Of Advances In Modeling Earth Systems 101002/2016msmentioning

confidence: 99%

Radiative convective equilibrium as a framework for studying the interaction between convection and its large‐scale environment

Silvers

Stevens

Mauritsen

et al. 2016

J Adv Model Earth Syst

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An uncertain representation of convective clouds has emerged as one of the key barriers to our understanding of climate sensitivity. The large gap in resolved spatial scales between General Circulation Models (GCMs) and high resolution models has made a systematic study of convective clouds across model configurations difficult. It is shown here that the simulated atmosphere of a GCM in Radiative Convective Equilibrium (RCE) is sufficiently similar across a range of domain sizes to justify the use of RCE to study both a GCM and a high resolution model on the same domain with the goal of improved constraints on the parameterized clouds. Simulations of RCE with parameterized convection have been analyzed on domains with areas spanning more than two orders of magnitude ( ), all having the same grid spacing of . The simulated climates on different domains are qualitatively similar in their degree of convective organization, the precipitation rates, and the vertical structure of the clouds and water vapor, with the similarity increasing as the domain size increases. Sea surface temperature perturbation experiments are used to estimate the climate feedback parameter for the differently configured experiments, and the cloud radiative effect is computed to examine the role which clouds play in the response. Despite the similar climate states between the domains the feedback parameter varies by more than a factor of two; the hydrological sensitivity parameter is better behaved, varying by a factor of 1.4. The sensitivity of the climate feedback parameter to domain size is related foremost to a nonsystematic response of low‐level clouds as well as an increasingly negative longwave feedback on larger domains.

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Shallowness of tropical low clouds as a predictor of climate models’ response to warming

Abstract: climatological shallowness of low clouds and thus to the spread of low-cloud changes under global warming.

Cited by 120 publications

References 79 publications

The Diversity of Cloud Responses to Twentieth Century Sea Surface Temperatures

The Diversity of Cloud Responses to Twentieth Century Sea Surface Temperatures

EUREC4A: A Field Campaign to Elucidate the Couplings Between Clouds, Convection and Circulation

Radiative convective equilibrium as a framework for studying the interaction between convection and its large‐scale environment

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