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Extreme heat under global warming is a concerning issue for the growing tropical population. However, model projections of extreme temperatures, a widely used metric for extreme heat, are uncertain on regional scales. In addition, humidity needs to be taken into account to estimate the health impact of extreme heat. Here we show that an integrated temperature–humidity metric for the health impact of heat, namely, the extreme wet-bulb temperature (TW), is controlled by established atmospheric dynamics and thus can be robustly projected on regional scales. For each 1 °C of tropical mean warming, global climate models project extreme TW (the annual maximum of daily mean or 3-hourly values) to increase roughly uniformly between 20° S and 20° N latitude by about 1 °C. This projection is consistent with theoretical expectation based on tropical atmospheric dynamics, and observations over the past 40 years, which gives confidence to the model projection. For a 1.5 °C warmer world, the probable (66% confidence interval) increase of regional extreme TW is projected to be 1.33–1.49 °C, whereas the uncertainty of projected extreme temperatures is 3.7 times as large. These results suggest that limiting global warming to 1.5 °C will prevent most of the tropics from reaching a TW of 35 °C, the limit of human adaptation. Limiting global warming to 1.5 °C will prevent tropical regions from reaching the limit of human adaptability, according to robust dynamical constraints on projected heat stress.

Despite the complexity of Earth's climate system, the influence of human activities on climate can be identified and predicted. We live in interesting times as we watch diverse effects of human activities on Earth's climate emerge from natural variability. In predicting the outcome of this evolving inadvertent experiment, climate science faces many challenges, some of which have been outlined in this series of Science Perspectives ( 1 – 6 ): reducing the uncertainty in climate sensitivity; explaining the recent slowdown in the rate of warming and its implications for understanding internal variability; uncovering the factors that control how and where the land will become drier as it warms; quantifying the cooling due to anthropogenic aerosols; explaining the curious evolution of atmospheric methane; and predicting changes in extreme weather. In addition to these challenges, the turbulent and chaotic atmospheric and oceanic flows seemingly limit predictability on various time scales. Is the climate system just too complex for useful prediction?

In models of radiative–convective equilibrium it is known that convection can spontaneously aggregate into one single localized moist region if the domain is large enough. The large changes in the mean climate state and radiative fluxes accompanying this self-aggregation raise questions as to what simulations at lower resolutions with parameterized convection, in similar homogeneous geometries, should be expected to produce to be considered successful in mimicking a cloud-resolving model. The authors investigate this self-aggregation in a nonrotating, three-dimensional cloud-resolving model on a square domain without large-scale forcing. It is found that self-aggregation is sensitive not only to the domain size, but also to the horizontal resolution. With horizontally homogeneous initial conditions, convective aggregation only occurs on domains larger than about 200km and with resolutions coarser than about 2km in the model examined. The system exhibits hysteresis, so that with aggregated initial conditions, convection remains aggregated even at our finest resolution, 500m, as long as the domain is greater than 200–300km. The sensitivity of self-aggregation to resolution and domain size in this model is due to the sensitivity of the distribution of low clouds to these two parameters. Indeed, the mechanism responsible for the aggregation of convection is the dynamical response to the longwave radiative cooling from low clouds. Strong longwave cooling near cloud top in dry regions forces downward motion, which by continuity generates inflow near cloud top and near-surface outflow from dry regions. This circulation results in the net export of moist static energy from regions with low moist static energy, yielding a positive feedback.

A diagnostic framework is developed to explain the response of tropical cyclones (TCs) to climate in high-resolution global atmospheric models having different complexity of boundary conditions. The framework uses vortex dynamics to identify the large-scale control on the evolution of TC precursors—first non-rotating convective clusters and then weakly rotating seeds. In experiments with perturbed sea surface temperature (SST) and CO 2 concentration from the historical values, the response of TCs follows the response of seeds. The distribution of seeds is explained by the distribution of the non-rotating convective clusters multiplied by a probability that they transition to seeds. The distribution of convective clusters is constrained by the large-scale vertical velocity and is verified in aquaplanet experiments with shifting Inter tropical Convergence Zones. The probability of transition to seeds is constrained by the large-scale vorticity via an analytical function, representing the relative importance between vortex stretching and vorticity advection, and is verified in aquaplanet experiments with uniform SST. The consistency between seed and TC responses breaks down substantially when the realistic SST is perturbed such that the spatial gradient is significantly enhanced or reduced. In such cases, the difference between the responses is explained by a change in the ventilation index, which influences the fraction of seeds that develop into TCs. The proposed TC-climate relationship serves as a framework to explain the diversity of TC projection across models and forcing scenarios.

Using the climate change experiments generated for the Fourth Assessment of the Intergovernmental Panel on Climate Change, this study examines some aspects of the changes in the hydrological cycle that are robust across the models. These responses include the decrease in convective mass fluxes, the increase in horizontal moisture transport, the associated enhancement of the pattern of evaporation minus precipitation and its temporal variance, and the decrease in the horizontal sensible heat transport in the extratropics. A surprising finding is that a robust decrease in extratropical sensible heat transport is found only in the equilibrium climate response, as estimated in slab ocean responses to the doubling of CO₂, and not in transient climate change scenarios. All of these robust responses are consequences of the increase in lower-tropospheric water vapor.

The climate feedbacks in coupled ocean–atmosphere models are compared using a coordinated set of twenty-first-century climate change experiments. Water vapor is found to provide the largest positive feedback in all models and its strength is consistent with that expected from constant relative humidity changes in the water vapor mixing ratio. The feedbacks from clouds and surface albedo are also found to be positive in all models, while the only stabilizing (negative) feedback comes from the temperature response. Large intermodel differences in the lapse rate feedback are observed and shown to be associated with differing regional patterns of surface warming. Consistent with previous studies, it is found that the vertical changes in temperature and water vapor are tightly coupled in all models and, importantly, demonstrate that intermodel differences in the sum of lapse rate and water vapor feedbacks are small. In contrast, intermodel differences in cloud feedback are found to provide the largest source of uncertainty in current predictions of climate sensitivity.

This article proposes a modification to the standard forcing–feedback diagnostic energy balance model to account for 1) differences between effective and equilibrium climate sensitivities and 2) the variation of effective sensitivity over time in climate change experiments with coupled atmosphere–ocean climate models. In the spirit of Hansen et al. an efficacy factor is applied to the ocean heat uptake. Comparing the time evolution of the surface warming in high and low efficacy models demonstrates the role of this efficacy in the transient response to CO₂ forcing. Abrupt CO₂ increase experiments show that the large efficacy of the Geophysical Fluid Dynamics Laboratory’s Climate Model version 2.1 (CM2.1) sets up in the first two decades following the increase in forcing. The use of an efficacy is necessary to fit this model’s global mean temperature evolution in periods with both increasing and stable forcing. The intermodel correlation of transient climate response with ocean heat uptake efficacy is greater than its correlation with equilibrium climate sensitivity in an ensemble of climate models used for the third and fourth Intergovernmental Panel on Climate Change (IPCC) assessments. When computed at the time of doubling in the standard experiment with 1% yr−1increase in CO₂, the efficacy is variable amongst the models but is generally greater than 1, averages between 1.3 and 1.4, and is as large as 1.75 in several models.

A tropical cyclone–permitting global atmospheric model is used to explore the hurricane frequency response to sea surface temperature (SST) anomalies generated by coupled models for the late-twenty-first century. Results are presented for SST anomalies averaged over 18 models as well as from 8 individual models. For each basin, there exists large intermodel spread in the magnitude and even the sign of the frequency response among the different SST projections. These sizable variations in response are explored to understand features of SST distributions that are important for the basin-wide hurricane responses. In the North Atlantic, the eastern Pacific, and the southern Indian basins, most (72%–86%) of the intermodel variance in storm frequency response can be explained by a simple relative SST index defined as a basin’s storm development region SST minus the tropical mean SST. The explained variance is significantly lower in the South Pacific (48%) and much lower in the western Pacific basin (27%). Several atmospheric parameters are utilized to probe changes in tropical atmospheric circulation and thermodynamical properties relevant to storm genesis in the model. While all present strong correlation to storm response in some basins, a parameter-measuring tropospheric convective mass flux stands out as skillful in explaining the simulated differences for all basins. Globally, in addition to a modest reduction of total storm frequency, the simulations exhibit a small, but robust eastward and poleward migration of genesis frequency in both the North Pacific and the North Atlantic Oceans. This eastward migration of storms can also be explained by changes in convection.

Diffusive theories for the meridional atmospheric energy transport can summarize our understanding of this central aspect of the general circulation. They can also be utilized in simple models of Earth’s energy balance to help interpret the response of the system to perturbations. A theory for this diffusivity of eddy heat transport is described based on Rhines scaling and the global entropy budget, each of which provides a constraint between the kinetic energy dissipation and the diffusivity. An expression for the diffusivity is then obtained by eliminating the dissipation from this set of two constraints. The theory can be thought of as a generalization of the theories of Held–Larichev and Barry–Craig–Thuburn. The theory is compared to simulations of the Held–Suarez idealized dry atmospheric model. Limitations of the theory are emphasized. The form of the theory allows it to be readily generalized to a moist atmosphere.

This study investigates the parameter dependence of eddy heat flux in a homogeneous quasigeostrophic two-layer model on a β plane with imposed environmental vertical wind shear and quadratic frictional drag. We examine the extent to which the results can be explained by a recently proposed diffusivity theory for passive tracers in two-dimensional turbulence. To account for the differences between two-layer and two-dimensional models, we modify the two-dimensional theory according to our two-layer f -plane analyses reported in an earlier study. Specifically, we replace the classic Kolmogorovian spectral slope, −5/3, assumed to predict eddy kinetic energy spectrum in the former with a larger slope, −7/3, suggested by a heuristic argument and fit to the model results in the latter. It is found that the modified theory provides a reasonable estimate within the regime where both and the strength of the frictional drag, , are much smaller than unity (here, c D is the nondimensional drag coefficient divided by the depth of the layer, k d is the wavenumber of deformation radius, and U is the imposed background vertical wind shear). For values of and that are closer to one, the theory works only if the full spectrum shape of the eddy kinetic energy is given. Despite the qualitative, fitting nature of this approach and its failure to explain the full parameter range, we believe its documentation here remains useful as a reference for the future attempt in pursuing a better theory.