The Change in Low Cloud Cover in a Warmed Climate Inferred from AIRS, MODIS, and ERA-Interim

Abstract

Decreases in subtropical low cloud cover (LCC) occur in climate model simulations of global warming. In this study 8-day-averaged observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) spanning 2002-14 are combined with European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis to compute the dependence of the observed variability of LCC on various predictor variables. Large-scale thermodynamic and dynamic predictors of LCC are selected based on insight from large-eddy simulations (LESs) and observational analysis. It is found that increased estimated inversion strength (EIS) is associated with increased LCC. Drying of the free troposphere is associated with decreased LCC. Decreased LCC accompanies subsidence in regions of relatively low EIS; the opposite is found in regions of high EIS. Finally, it is found that increasing sea surface temperature (SST) leads to a decrease in LCC. These results are in keeping with previous studies of monthly and annual data. Based upon the observed response of LCC to natural variability of the control parameters, the change in LCC is estimated for an idealized warming scenario where SST increases by 1 K and EIS increases by 0.2 K. For this change in EIS and SST the LCC is inferred to decrease by 0.5%-2.7% when the regression models are trained on data observed between 408S and 408N and by 1.1%-1.4% when trained on data from trade cumulusdominated regions. When the data used to train the regression model are restricted to stratocumulusdominated regions the change in LCC is highly uncertain and varies between 21.6% and 11.4%, depending on the stratocumulus-dominated region used to train the regression model.

Cloud feedback mechanisms and their representation in global climate models

“…These studies show that low clouds in both models and observations are mostly sensitive to changes in SST and inversion strength. Although these two effects would tend to cancel each other, observations and GCM simulations constrained by observations suggest that SST‐mediated low cloud reduction with warming dominates, increasing the likelihood of a positive low cloud feedback and high climate sensitivity . Nevertheless, recent ground‐based observations of covariations of ShCu with meteorological conditions suggest that a majority of GCMs are unlikely to represent the temporal dynamics of the cloudy boundary layer .…”

Low-Cloud Feedbacks from Cloud-Controlling Factors: A Review

“…Then we can predict how the low clouds will change with climate warming under the assumption that the sensitivities of clouds to their controlling factors are time-scale invariant. This approach has been taken in five recent studies (Qu et al 2015b;Zhai et al 2015;Myers and Norris 2016;McCoy et al 2017, in chronological order; hereafter these studies will be named ''Q15,'' ''Z15, '' ''M16,'' ''B16'' and ''M17,'' respectively). In this paper, we review these studies.…”

Observational Constraints on Cloud Feedbacks: The Role of Active Satellite Sensors

“…A number of other recent studies use one or both of these short-term variability approaches (Brient and Schneider 2016;Myers and Norris 2016;McCoy et al 2017). Uncertainties in feedbacks estimated from these studies are still relatively large, but a meta-analysis by Klein et al (2017, this issue) is able to derive a useful constraint on global models which indicates negative and near-zero tropical cloud feedbacks are unlikely.…”