A new release of the Max Planck Institute for Meteorology Earth System Model version 1.2 (MPI‐ESM1.2) is presented. The development focused on correcting errors in and improving the physical processes representation, as well as improving the computational performance, versatility, and overall user friendliness. In addition to new radiation and aerosol parameterizations of the atmosphere, several relatively large, but partly compensating, coding errors in the model's cloud, convection, and turbulence parameterizations were corrected. The representation of land processes was refined by introducing a multilayer soil hydrology scheme, extending the land biogeochemistry to include the nitrogen cycle, replacing the soil and litter decomposition model and improving the representation of wildfires. The ocean biogeochemistry now represents cyanobacteria prognostically in order to capture the response of nitrogen fixation to changing climate conditions and further includes improved detritus settling and numerous other refinements. As something new, in addition to limiting drift and minimizing certain biases, the instrumental record warming was explicitly taken into account during the tuning process. To this end, a very high climate sensitivity of around 7 K caused by low‐level clouds in the tropics as found in an intermediate model version was addressed, as it was not deemed possible to match observed warming otherwise. As a result, the model has a climate sensitivity to a doubling of CO2 over preindustrial conditions of 2.77 K, maintaining the previously identified highly nonlinear global mean response to increasing CO2 forcing, which nonetheless can be represented by a simple two‐layer model.

The Radiative‐Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative‐convective equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climate sensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique among intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud‐resolving models (CRMs), large eddy simulations (LES), and global cloud‐resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self‐aggregation in large domains and agree that self‐aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self‐aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than unaggregated simulations.

General circulation models show that as the surface temperature increases, the convective anvil clouds shrink. By analyzing radiativeconvective equilibrium simulations, we show that this behavior is rooted in basic energetic and thermodynamic properties of the atmosphere: As the climate warms, the clouds rise and remain at nearly the same temperature, but find themselves in a more stable atmosphere; this enhanced stability reduces the convective outflow in the upper troposphere and decreases the anvil cloud fraction. By warming the troposphere and increasing the upper-tropospheric stability, the clustering of deep convection also reduces the convective outflow and the anvil cloud fraction. When clouds are radiatively active, this robust coupling between temperature, high clouds, and circulation exerts a positive feedback on convective aggregation and favors the maintenance of strongly aggregated atmospheric states at high temperatures. This stability iris mechanism likely contributes to the narrowing of rainy areas as the climate warms. Whether or not it influences climate sensitivity requires further investigation.anvil cloud | cloud feedback | convective aggregation | large-scale circulation | climate sensitivity H ow do clouds respond to a change in surface temperature? The answer is central to understanding how Earth's average surface temperature responds to external perturbations. But understanding how clouds change, particularly high clouds, is also crucial for understanding how regional patterns of temperature and rainfall may change with surface warming (1-5).Compelling physical arguments, with varying degrees of observational support, suggest that cloud changes with warming constitute a net positive feedback on radiative forcing (6). Two main contributors to this positive feedback are an expected reduction of low-level cloud amount (7-10) and a rise of high-level clouds (11,12). Some arguments have also been advanced for negative feedbacks that would reduce the sensitivity of Earth's temperature to perturbations, through for instance a greater preponderance of liquid in clouds at warmer temperatures (13) or, for reasons that are unclear, a reduction in the relative area of the wet, vs. dry, tropics with warming (14, 15). The wet tropics are very much associated with the occurrence of precipitating deep convection, whose detrained water condensate gives rise to the formation of high-level clouds referred to as anvils. A natural question thus arises: How does the area of the wet tropics, in particular their high anvil clouds, respond to warming?A seminal contribution to understanding controls on anvil clouds was the idea of Hartmann and Larson (11) that water vapor acts, through its control on clear-sky radiative cooling, as a thermostatic control of the height at which convective outflow occurs. According to this idea [known as the fixed anvil temperature (FAT) hypothesis] anvil clouds occur at the height where the convective detrainment maximizes. This height can be determined, via mass conservation, fr...

The representation of tropical precipitation is evaluated across three generations of models participating in the Coupled Model Intercomparison Project (CMIP), phases 3, 5 and 6. Compared to state-of-the-art observations, improvements in tropical precipitation in the CMIP6 models are identified for some metrics, but we find no general improvement in tropical precipitation on different temporal and spatial scales. Our results indicate overall little changes across the CMIP phases for the summer monsoons, the double-ITCZ bias and the diurnal cycle of tropical precipitation. We find a reduced amount of drizzle events in CMIP6, but tropical precipitation occurs still too frequently. Continuous improvements across the CMIP phases are identified for the number of consecutive dry days, the representation of modes of variability, namely the Madden-Julian Oscillation and the El Niño Southern Oscillation, as well as the trends in dry months in the 20th century. The observed positive trend in extreme wet months is, however, not captured by any of the CMIP phases, which simulate negative trends for extremely wet months in the 20th century. The regional biases are larger than a climate-change signal one hopes to use the models to identify. Given the pace of climate change as compared to the pace of model improvements to simulate tropical precipitation, we question the past strategy of the development of the present class of global climate models as the mainstay of the scientific response to climate change. We suggest to explore alternative approaches such as high-resolution storm-resolving models that can offer better prospects to inform us about how tropical precipitation might change with anthropogenic warming.

Radiative‐convective equilibrium simulations with the general circulation model ECHAM6 are used to explore to what extent the dependence of large‐scale convective self‐aggregation on sea‐surface temperature (SST) is driven by the convective parameterization. Within the convective parameterization, we concentrate on the entrainment parameter and show that large‐scale convective self‐aggregation is independent of SST when the entrainment rate for deep convection is set to zero or when the convective parameterization is removed from the model. In the former case, convection always aggregates very weakly, whereas in the latter case, convection always aggregates very strongly. With a nontrivial representation of convective entrainment, large‐scale convective self‐aggregation depends nonmonotonically on SST. For SSTs below 295 K, convection is more aggregated the smaller the SST because large‐scale moisture convergence is relatively small, constraining convective activity to regions with high wind‐induced surface moisture fluxes. For SSTs above 295 K, convection is more aggregated the higher the SST because entrainment is most efficient in decreasing updraft buoyancy at high SSTs, amplifying the moisture‐convection feedback. When halving the entrainment rate, convection is less efficient in reducing updraft buoyancy, and convection is less aggregated, in particular at high SSTs. Despite most early work on self‐aggregation highlighted the role of nonconvective processes, we conclude that convective self‐aggregation and the global climate state are sensitive to the convective parameterization.