Retrospectively comparing future model projections to observations provides a robust and independent test of model skill. Here we analyze the performance of climate models published between 1970 and 2007 in projecting future global mean surface temperature (GMST) changes. Models are compared to observations based on both the change in GMST over time and the change in GMST over the change in external forcing. The latter approach accounts for mismatches in model forcings, a potential source of error in model projections independent of the accuracy of model physics. We find that climate models published over the past five decades were skillful in predicting subsequent GMST changes, with most models examined showing warming consistent with observations, particularly when mismatches between model‐projected and observationally estimated forcings were taken into account.

Cloud-aerosol interactions remain a major obstacle to understanding climate and severe weather. Observations suggest that aerosols enhance tropical thunderstorm activity; past research, motivated by the importance of understanding aerosol impacts on clouds, has proposed several mechanisms that could explain that observed link. We find that high-resolution atmospheric simulations can reproduce the observed link between aerosols and convection. However, we also show that previously proposed mechanisms are unable to explain the invigoration. Examining underlying processes reveals that, in our simulations, high aerosol concentrations increase environmental humidity by producing clouds that mix more condensed water into the surrounding air. In turn, higher humidity favors large-scale ascent and stronger convection. Our results provide a physical reason to expect invigorated thunderstorms in high-aerosol regions of the tropics.

Tropical precipitation extremes are expected to strengthen with warming, but quantitative estimates remain uncertain because of a poor understanding of changes in convective dynamics. This uncertainty is addressed here by analyzing idealized convection-permitting simulations of radiative–convective equilibrium in long-channel geometry. Across a wide range of climates, the thermodynamic contribution to changes in instantaneous precipitation extremes follows near-surface moisture, and the dynamic contribution is positive and small but is sensitive to domain size. The shapes of mass flux profiles associated with precipitation extremes are determined by conditional sampling that favors strong vertical motion at levels where the vertical saturation specific humidity gradient is large, and mass flux profiles collapse to a common shape across climates when plotted in a moisture-based vertical coordinate. The collapse, robust to changes in microphysics and turbulence schemes, implies a thermodynamic contribution that scales with near-surface moisture despite substantial convergence aloft and allows the dynamic contribution to be defined by the pressure velocity at a single level. Linking the simplified dynamic mode to vertical velocities from entraining plume models reveals that the small dynamic mode in channel simulations (≲2% K−1) is caused by opposing height dependences of vertical velocity and density, together with the buffering influence of cloud-base buoyancies that vary little with surface temperature. These results reinforce an emerging picture of the response of extreme tropical precipitation rates to warming: a thermodynamic mode of about 7% K−1 dominates, with a minor contribution from changes in dynamics.

Idealized convection‐permitting simulations of radiative‐convective equilibrium have become a popular tool for understanding the physical processes leading to horizontal variability of tropical water vapor and rainfall. However, the applicability of idealized simulations to nature is still unclear given that important processes are typically neglected, such as lateral water vapor advection by extratropical intrusions, or interactive ocean coupling. Here, we exploit spectral analysis to compactly summarize the multiscale processes supporting convective aggregation. By applying this framework to high‐resolution reanalysis data and satellite observations in addition to idealized simulations, we compare convective‐aggregation processes across horizontal scales and data sets. The results affirm the validity of the radiative‐convective equilibrium simulations as an analogy to the real world. Column moist static energy tendencies share similar signs and scale selectivity in convection‐permitting models and observations: Radiation increases variance at wavelengths above 1,000 km, while advection damps variance across wavelengths, and surface fluxes mostly reduce variance between 1,000 and 10,000 km.

Temporal precipitation autocorrelations drop slower than exponentially at long lags, and there is a range from tens to thousands of minutes where it is relevant to ask if a scale‐free process might underlie the long autocorrelations. A simple stochastic model in which precipitation appears as variable‐length spikes provides a reasonable prototype for this behavior. In both observations and the model, separating the component of the autocorrelation within wet events from the interevent contribution suggests long autocorrelation behavior is primarily associated with the latter. When precipitation spikes are short compared to dry events, a true power law is obtained with analytical exponent −0.5 and precipitation autocorrelation is determined by dry‐spell model parameters. In more realistic cases, wet‐spell termination is also important. Although a variety of apparent power law exponents can be obtained for different parameters, the fundamental long‐lag process appears to be that of the interevent correlation.