Editing IPCC:AR6/WGI/Chapter-7 (section)

====== Subtropical marine low-cloud feedback ======

It has long been argued that the response of marine boundary-layer clouds over the subtropical ocean to surface warming was the largest contributor to the spread among GCMs in the net cloud feedback ( [[#Boucher--2013|Boucher et al., 2013]] ). However, uncertainty of the marine low-cloud feedback has been reduced considerably since AR5 through combined knowledge from theoretical, modelling and observational studies ( [[#Klein--2017|Klein et al., 2017]] ). Processes that control the low-clouds are complex and involve coupling with atmospheric motions on multiple scales, from the boundary-layer turbulence to the large-scale subsidence, which may be represented by a combination of shallow and deep convective mixing ( [[#Sherwood--2014|Sherwood et al., 2014]] ).

In order to disentangle the large-scale processes that cause the cloud amount either to increase or decrease in response to the surface warming, the cloud feedback has been expressed in terms of several ‘cloud controlling factors’ ( [[#Qu--2014|Qu et al., 2014]] , 2015; [[#Zhai--2015|Zhai et al., 2015]] ; [[#Brient--2016|Brient and Schneider, 2016]] ; [[#Myers--2016|Myers and Norris, 2016]] ; [[#McCoy--2017a|McCoy et al., 2017a]] ). The advantage of this approach over conventional calculation of cloud feedbacks is that the temperature-mediated cloud response can be estimated without using information of the simulated cloud responses that are less well-constrained than the changes in the environmental conditions. Two dominant factors are identified for the subtropical low-clouds: a thermodynamic effect due to rising SST that acts to reduce low-cloud by enhancing cloud-top entrainment of dry air, and a stability effect accompanied by an enhanced inversion strength that acts to increase low-cloud ( [[#Qu--2014|Qu et al., 2014]] , 2015; [[#Kawai--2017|Kawai et al., 2017]] ). These controlling factors compensate with a varying degree in different ESMs, but can be constrained by referring to the observed seasonal or interannual relationship between the low-cloud amount and the controlling factors in the environment as a surrogate. The analysis leads to a positive local feedback that has the global contribution of 0.14 to 0.36 W m <sup>–2</sup> °C <sup>–1</sup> ( [[#Klein--2017|Klein et al., 2017]] ), to which the feedback in the stratocumulus regime dominates over the feedback in the trade cumulus regime ( [[#Cesana--2019|Cesana et al., 2019]] ; [[#Radtke--2021|Radtke et al., 2021]] ). The stratocumulus feedback may be underestimated because explicit simulations using LES show a larger local feedback of up to 2.5 W m <sup>–2</sup> °C <sup>–1</sup> , corresponding to the global contribution of 0.2 W m <sup>–2</sup> °C <sup>–1</sup> by multiplying the mean tropical stratocumulus fraction of about 8% ( [[#Bretherton--2015|Bretherton, 2015]] ). Supported by different lines of evidence, the subtropical marine low-cloud feedback is assessed as positive with ''high confidence'' . Based on the combined estimate using LESs and the cloud controlling factor analysis, the global contribution of the feedback due to marine low-clouds equatorward of 30° is assessed to be 0.2 ± 0.16 W m <sup>–2</sup> °C <sup>–1</sup> (one standard deviation), for which the range reflects methodological uncertainties.

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