The impact of parametrized convection on cloud feedback

Webb, Mark J.; Lock, A. P.; Bretherton, Christopher S.; Bony, Sandrine; Cole, Jason N. S.; Idelkadi, Abderrahmane; Kang, Sarah M.; Koshiro, Tsuyoshi; Kawai, Hideaki; Ogura, Tomoo; Roehrig, Romain; Shin, Yechul; Mauritsen, Thorsten; Sherwood, Steven C.; Vial, Jessica; Watanabe, Masahiro; Woelfle, Matthew D.; Zhao, Ming

doi:10.1098/rsta.2014.0414

Cited by 80 publications

(99 citation statements)

References 93 publications

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“…Previous studies have shown lower tropospheric stability (LTS) to be a useful diagnostic tool that connects low-cloud changes to the characteristics of the large-scale environment, especially within traditionally defined stratocumulus regions (Klein & Hartmann, 1993;Medeiros et al, 2008;Webb et al, 2015;Wood & Bretherton, 2006). We analyze the EIS, which can be thought of as a correction to the LTS based on the moist adiabatic profile.…”

Section: Methodology Of Analysismentioning

confidence: 99%

“…They, as did most previous studies (e.g., Klein & Hartmann, 1993;Wood & Bretherton, 2006), focused on five oceanic regions which are important for stratocumulus decks of radiatively active lowlevel clouds. Only recently have the fields of stability, low-level clouds, and low-level temperature begun to be investigated over larger swaths of the globe (Grise & Medeiros, 2016;Rose & Rayborn, 2016;Webb et al, 2015;Zhou et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

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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: Methodology Of Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Diversity of Cloud Responses to Twentieth Century Sea Surface Temperatures

Silvers

Paynter

Zhao

2018

Geophysical Research Letters

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“…Last but not least we investigate the impact of parameterized convection on ECS by performing a simulation in which we completely switched off convection (simulation NOCONV) as in Webb et al (2015). This is normally performed only in simulations run at horizontal resolutions of less than 10 km, at which the vertical motions associated with deep convection start to be resolved.…”

Section: Model Set-up and Experimentsmentioning

confidence: 99%

The importance of mixed-phase and ice clouds for climate sensitivity in the global aerosol–climate model ECHAM6-HAM2

Lohmann

Neubauer

2018

Atmos. Chem. Phys.

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Abstract. How clouds change in a warmer climate remains one of the largest uncertainties for the equilibrium climate sensitivity (ECS). While a large spread in the cloud feedback arises from low-level clouds, it was recently shown that mixed-phase clouds are also important for ECS. If mixedphase clouds in the current climate contain too few supercooled cloud droplets, too much ice will change to liquid water in a warmer climate. As shown by Tan et al. (2016), this overestimates the negative cloud-phase feedback and underestimates ECS in the CAM global climate model (GCM). Here we use the newest version of the ECHAM6-HAM2 GCM to investigate the importance of mixed-phase and ice clouds for ECS.Although we also considerably underestimate the fraction of supercooled liquid water globally in the reference version of the ECHAM6-HAM2 GCM, we do not obtain increases in ECS in simulations with more supercooled liquid water in the present-day climate, different from the findings by Tan et al. (2016). We hypothesize that it is not the global supercooled liquid water fraction that matters, but only how well low-and mid-level mixed-phase clouds with cloud-top temperatures in the mixed-phase temperature range between 0 and −35 • C that are not shielded by higher-lying ice clouds are simulated. These occur most frequently in midlatitudes, in particular over the Southern Ocean where they determine the amount of absorbed shortwave radiation. In ECHAM6-HAM2 the amount of absorbed shortwave radiation over the Southern Ocean is only significantly overestimated if all clouds below 0 • C consist exclusively of ice. Only in this simulation is ECS significantly smaller than in all other simulations and the cloud optical depth feedback is the dominant cloud feedback. In all other simulations, the cloud optical depth feedback is weak and changes in cloud feedbacks associated with cloud amount and cloud-top pressure dominate the overall cloud feedback. However, apart from the simulation with only ice below 0 • C, differences in the overall cloud feedback are not translated into differences in ECS in our model. This insensitivity to the cloud feedback in our model is explained with compensating effects in the clear sky.

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“…There are discussions if cirrus clouds are mainly formed by homogeneous nucleation as we assume in our reference simulation or are formed heterogeneously (Cziczo et al, 2013;Spichtinger and Krämer, 2012;Kärcher, 2017). We investigate the impact of homogeneous vs. heterogeneous freezing in cirrus and ECS by performing a simulation in which we completely switched off convection (simulation NOCONV) as was done in Webb et al (2015). This is normally done only in simulations run at horizontal resolutions of less than 10 km, where the vertical motions associated with deep convection start to be resolved.…”

Section: Model Set-up and Experimentsmentioning

confidence: 99%

The importance of mixed-phase clouds for climate sensitivity in the global aerosol-climate model ECHAM6-HAM2

Lohmann¹,

Neubauer²

2018

Preprint

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Abstract. Clouds are important in the climate system because of their large influence on the radiation budget. On the one hand, they scatter solar radiation and with that cool the climate. On the other hand, they absorb and re-emit terrestrial radiation, which causes a warming. How clouds change in a warmer climate is one of the largest uncertainties for the equilibrium climate sensitivity (ECS). While a large spread in the cloud feedback arises from low-level clouds, it was recently shown that also mixed-phase clouds are important for ECS. If mixed-phase clouds in the current climate contain too few supercooled cloud 5 droplets, too much ice will change to liquid water in a warmer climate. As shown by Tan et al. (2016), this overestimates the negative cloud phase feedback and underestimates ECS in the CAM global climate model (GCM). Here we are using the newest version of the ECHAM6-HAM2 GCM to investigate the importance of mixed-phase clouds for ECS.Although we also considerably underestimate the fraction of supercooled liquid water globally in the reference version of ECHAM6-HAM2 GCM, we do not obtain increases in ECS in simulations with more supercooled liquid water in the present-

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The impact of parametrized convection on cloud feedback

Cited by 80 publications

References 93 publications

The Diversity of Cloud Responses to Twentieth Century Sea Surface Temperatures

The Diversity of Cloud Responses to Twentieth Century Sea Surface Temperatures

The importance of mixed-phase and ice clouds for climate sensitivity in the global aerosol–climate model ECHAM6-HAM2

The importance of mixed-phase clouds for climate sensitivity in the global aerosol-climate model ECHAM6-HAM2

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