Interpretation of the positive low-cloud feedback predicted by a climate model under global warming

By F. Brient, Sandrine Bony. Climate Dynamics, 2013

174 citations recorded by the source corpus.

The response of low-level clouds to climate change has been identified as a major contributor to the uncertainty in climate sensitivity estimates among climate models. By analyzing the behaviour of low-level clouds in a hierarchy of models (coupled ocean-atmosphere model, atmospheric general circulation model, aqua-planet model, single-column model) using the same physical parameterizations, this study proposes an interpretation of the strong positive low-cloud feedback predicted by the IPSL-CM5A climate model under climate change. In a warmer climate, the model predicts an enhanced clear-sky radiative cooling, stronger surface turbulent fluxes, a deepening and a drying of the planetary boundary layer, and a decrease of tropical low-clouds in regimes of weak subsidence. We show that the decrease of low-level clouds critically depends on the change in the vertical advection of moist static energy from the free troposphere to the boundary-layer. This change is dominated by variations in the vertical gradient of moist static energy between the surface and the free troposphere just above the boundary-layer. In a warmer climate, the thermodynamical relationship of Clausius-Clapeyron increases this vertical gradient, and then the import by large-scale subsidence of low moist static energy and dry air into the boundary layer. This results in a decrease of the low-level cloudiness and in a weakening of the radiative cooling of the boundary layer by low-level clouds. The energetic framework proposed in this study might help to interpret inter-model differences in low-cloud feedbacks under climate change.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/9b72cd9bde72849edcca2d4c70cf27826ab5f4ea

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Citations in the corpus

Uncertainty in Model Climate Sensitivity Traced to Representations of Cumulus Precipitation Microphysics (2016, background): “…sensitivity between GCMs (e.g., Cess et al. 1990; Zhang et al. 1994; Cess et al. 1996; Soden et al. 2004;Wyant et al. 2006; Ringer et al. 2006; Bony et al. 2006; Medeiros et al. 2008; Wyant et al. 2009; Brient and Bony 2012, 2013; Bretherton et al. 2014; Ringer et al. 2014; Webb et al. 2015).”
Aerosol and ozone changes as forcing for climate evolution between 1850 and 2100 (2013, methodology): “2010). The assessment of the long-term trends induced by the use of the historical anthropogenic emission datasets in global chemical models is discussed in Lamarque et al. (2010) and is not tackled in this paper.”
Origins of differences in climate sensitivity, forcing and feedback in climate models (2013, background): “More recently, Brient and Bony (2012) have argued that changes in the vertical gradient of moist static energy in a warmer climate increase the amount of dry air imported into the boundary layer in a new version of the IPSL model, leading to a reduction in cloud and a positive feedback.”
Mechanisms of marine low cloud sensitivity to idealized climate perturbations: A single‐LES exploration extending the CGILS cases (2013, methodology): “(Brient and Bony [2012] found a slight increase in low cloud in their 43 CO2 SCM simulations of S6.) This suggests that radiation balance is not a primary control on the cloud cover in this case. On the other hand, a 10% reduction in wind speed induces a large (13%) relative decrease in SWCRE, showi”
Cloud feedback mechanisms and their representation in global climate models (2017, unknown): “As the climate warms, convective moisture fluxes strengthen due to the robust increase of the vertical gradient of specific humidity controlled by the Clausius-Clapeyron relationship.(82) Increasing convective moisture fluxes between the PBL and the free troposphere lead to a relatively drier PBL wi”
The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6. (2016, background): “A warming or cooling of the atmosphere of equal magnitude while maintaining relative humidity will for example generate different changes in absolute humidity and its horizontal and vertical gradients, which have been linked to cloud feedbacks (Brient and Bony, 2013; Sherwood et al., 2014), the atmo”