The climatological atmospheric circulation is key to establishing the tropical ‘pattern effect’, whereby cloud feedbacks induced by sea surface temperature (SST) warming depend on the spatial structure of that warming. But how patterned warming-induced circulation changes affect cloud responses is less clear. Here we use idealized simulations with prescribed SST perturbations to understand the contributions to changes in tropical-mean cloud radiative effects (CRE) from different circulation regimes. We develop a novel framework based on moist static energy to understand the circulation response, targeting in particular the bulk circulation metric of ascent fraction. Warming concentrated in regions of ascent leads to a strong ‘upped-ante’ effect and spatial contraction of the ascending region. Our framework reveals substantial contributions to tropical-mean CRE changes not only from traditional ‘pattern effect’ regimes, but also from the intensification of convection in ascent regions as well as a smaller contribution from cloud changes in convective margins.

Regions along the edges of the tropics host vast populations and ecosystems which are sensitive to climate change. Here we examine the extent of tropical climate land areas in the ERA5 and MERRA-2 reanalyses in high-emission scenarios of 45 models participating in phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5/6). Based on the definition of tropical climate land areas as regions where the diurnal temperature range exceeds the seasonal temperature range, we find a net reduction of tropical land area with global warming. This change is primarily due to an increased seasonal temperature range, driven by enhanced summer warming. The reduction in tropical land area is consistent with the expansion of the subtropical descending zones and with the expansion of drylands with global warming. However, the particular contributions of dynamic and thermodynamic processes are not clear.

Uncertainty in the response of clouds to global warming remains a significant barrier to reducing uncertainty in climate sensitivity. A key question is the extent to which the dynamic component -- that which is due to changes in circulation rather than changes in the thermodynamic properties of clouds -- contributes to the total cloud feedback. Here, simulations with a range of cloud-resolving models are used to quantify the impact of circulation changes on tropical cloud feedbacks. The dynamic component of the cloud feedback is substantial for some models and is controlled both by SST-induced changes in circulation and nonlinearity in the climatological relationship between clouds and circulation. Differences in the longwave and shortwave dynamic components across models are linked to the extent to which ascending regions narrow or expand in response to a change in SST. The diversity of changes in ascent area is coupled to intermodel differences non-radiative diabatic heating in ascending regions.

Extreme temperatures have warmed substantially over recent decades and are projected to continue warming in response to future climate change. Warming of extreme temperatures is amplified over land where the impacts on human health, wildfire risk and food production are most severe. Using simulations with climate models, I show that hot days over tropical land warm substantially more than the average day. For example, warming of the hottest 1% of land days is 24% larger than the time-mean warming averaged across models. The climate-change response of extreme temperatures over tropical land is interpreted using a theory based on atmospheric dynamics. According to the theory, warming is amplified for hot land days because those days are dry: I term this the “drier get hotter” mechanism. Changes in near-surface relative humidity further increase tropical land warming , with decreases in land relative humidity particularly important. The theory advances physical understanding of the tropical climate and highlights land-surface dryness as a key factor determining how extreme temperatures will respond to future climate change.