Clouds, Circulation, and Climate Sensitivity in a Radiative-Convective Equilibrium Channel Model

Tropical cloud and circulation changes are large sources of uncertainty in future climate change. This problem owes partly to the scale separation between large-scale tropical dynamics (~104km) and convective dynamics (~7 km), which generally requires parameterizing convection in models that resolve large-scale dynamics, or parameterizing (or omitting) large-scale dynamics in models that permit convection. Here we discuss simulations of radiative-convective equilibrium (RCE) across a wide range of surface temperatures in long-channel geometry—where the domain size and resolution marginally resolve both large-scale dynamics and convection. Self-aggregation of convection in these simulations spontaneously produces realistic dynamical regimes of large-scale vertical motion. The circulation weakens with surface warming but changes in the degree of self-aggregation depend on the metric that is used; there is no obvious trend in aggregation with warming. Surface warming causes an upward shift and decrease in area of high clouds, and a sharp decline in midlevel clouds, but no systematic trend in low cloud cover. We introduce a method for approximate radiative kernel feedback analysis in RCE, and apply it to both simulations in long-channel geometry and in a smaller square domain. The kernel-corrected cloud feedback is positive but its magnitude varies across temperatures. Compared to simulations that do not have aggregation, there is a more negative net feedback due to the effects of aggregation on relative humidity and cloud cover. These results are consistent with the hypothesis that self-aggregation moderately reduces climate sensitivity.National Science Foundation (U.S.) (Grant AGS-1623218)National Science Foundation (U.S.) (Grant AGS-1433251