On the spread of changes in marine low cloud cover in climate model simulations of the 21st century

Qu, Xiaoshu; Hall, Alex; Klein, Stephen A.; Caldwell, Peter

doi:10.1007/s00382-013-1945-z

Cited by 172 publications

(250 citation statements)

References 79 publications

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“…As computed here, the sum of these windows occupy about 6% of the globe. The same computations with the windows from Qu et al (2014) accounts for around 13% of while occupying about 9% of the globe (supporting information Figure S1). In all cases, contributions to the decadal variability of from particular tropical windows are minimal.…”

Section: Discussionmentioning

confidence: 70%

“…The known connections between LCC and SST Myers & Norris, 2016;Qu et al, 2014;Zhou et al, 2016) combined with the strong linear dependence of LCC anomalies on the EIS field shown in the previous subsection encourage examination of the global trends of LCC and EIS. A strong relationship…”

Section: Response Of Clouds To Eis and Sst Patternsmentioning

confidence: 82%

“…Following the work of Qu et al (2014Qu et al ( , 2015 and Z16, we use multiple linear regression to estimate the dependence of ΔLCC on ΔEIS and ΔSST for three AGCMs over the historical period. The linear model of LCC change works well when applied to both ±30 ∘ and ±60 ∘ .…”

Section: Discussionmentioning

confidence: 99%

“…In particular, increasing EIS and LCC occurs in regions of decreasing SST (northeastern and southeastern Pacific, the Indian Ocean, the southern Atlantic, and the Southern Ocean). This relationship has been thoroughly discussed in the literature in the context of stratocumulus regions and subsiding circulations (e.g., Klein & Hartmann, 1993;Myers & Norris, 2013;Qu et al, 2014Qu et al, , 2015Wood & Bretherton, 2006). Figure 3 shows the relationship to also be important across much of the world ocean.…”

Section: 1002/2017gl075583mentioning

confidence: 95%

“…To probe the dependence of LCC on low-level stability multiple linear regression is used to decompose ΔLCC into a linear combination of ΔEIS and ΔSST. The anomalous changes of tropical marine LCC were shown (Qu et al, 2014;Z16) to be well explained by a linear combination of the change in EIS and SST. The coefficients and can thus be determined for particular experiments or models in the following assumed relationship:…”

Section: Dependence Of Lcc On Eis and Sstmentioning

confidence: 98%

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The Diversity of Cloud Responses to Twentieth Century Sea Surface Temperatures

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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: 70%

Section: Response Of Clouds To Eis and Sst Patternsmentioning

confidence: 82%

Section: Discussionmentioning

confidence: 99%

Section: 1002/2017gl075583mentioning

confidence: 95%

Section: Dependence Of Lcc On Eis and Sstmentioning

confidence: 98%

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The Diversity of Cloud Responses to Twentieth Century Sea Surface Temperatures

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Low cloud reduction in a greenhouse‐warmed climate: Results from Lagrangian LES of a subtropical marine cloudiness transition

Bretherton

Blossey

2014

J Adv Model Earth Syst

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Lagrangian large-eddy simulations of a composite stratocumulus to cumulus transition case over the subtropical northeast Pacific Ocean are subject to perturbed forcings that isolate the cloud response to CO 2 , to overall tropical warming, and to increased inversion stability over the subtropical subsidence regions. These simulations show that a tropical surface warming of 4 K induces substantial stratocumulus thinning via a thermodynamic mechanism: increased cloud layer humidity flux in a warmer climate induces an entrainment liquid-flux adjustment that dries the stratocumulus cloud layer, whether well mixed or cumulus coupled. A radiative mechanism amplifies this response: increased emissivity of the free troposphere due to increased CO 2 and water vapor reduces radiative driving of turbulence in a stratocumulus-capped boundary layer; a thinner stratocumulus layer accompanies less turbulence. In combination, a 4 K warming and CO 2 quadrupling greatly reduce low cloud and weaken the simulated shortwave cloud radiative effect by over 50%. Large increases in inversion stability in the stratocumulus regions could counter much of this cloudiness reduction.

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Statistical significance of climate sensitivity predictors obtained by data mining

Caldwell

Bretherton

Zelinka

et al. 2014

Geophysical Research Letters

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Several recent efforts to estimate Earth's equilibrium climate sensitivity (ECS) focus on identifying quantities in the current climate which are skillful predictors of ECS yet can be constrained by observations. This study automates the search for observable predictors using data from phase 5 of the Coupled Model Intercomparison Project. The primary focus of this paper is assessing statistical significance of the resulting predictive relationships. Failure to account for dependence between models, variables, locations, and seasons is shown to yield misleading results. A new technique for testing the field significance of data‐mined correlations which avoids these problems is presented. Using this new approach, all 41,741 relationships we tested were found to be explainable by chance. This leads us to conclude that data mining is best used to identify potential relationships which are then validated or discarded using physically based hypothesis testing.

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On the spread of changes in marine low cloud cover in climate model simulations of the 21st century

Cited by 172 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

Low cloud reduction in a greenhouse‐warmed climate: Results from Lagrangian LES of a subtropical marine cloudiness transition

Statistical significance of climate sensitivity predictors obtained by data mining

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