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A reference or “no‐feedback” radiative response to warming is fundamental to understanding how much global warming will occur for a given change in greenhouse gases or solar radiation incident on the Earth. The simplest estimate of this radiative response is given by the Stefan‐Boltzmann law as W m⁻² K⁻¹for Earth's present climate, whereis a global effective emission temperature. The comparable radiative response in climate models, widely called the “Planck feedback,” averages −3.3 W m⁻² K⁻¹. This difference of 0.5 W m⁻² K⁻¹is large compared to the uncertainty in the net climate feedback, yet it has not been studied carefully. We use radiative transfer models to analyze these two radiative feedbacks to warming, and find that the difference arises primarily from the lack of stratospheric warming assumed in calculations of the Planck feedback (traditionally justified by differing constraints on and time scales of stratospheric adjustment relative to surface and tropospheric warming). The Planck feedback is thus masked for wavelengths with non‐negligible stratospheric opacity, and this effect implicitly acts to amplify warming in current feedback analysis of climate change. Other differences between Planck and Stefan‐Boltzmann feedbacks arise from temperature‐dependent gas opacities, and several artifacts of nonlinear averaging across wavelengths, heights, and different locations; these effects partly cancel but as a whole slightly destabilize the Planck feedback. Our results point to an important role played by stratospheric opacity in Earth's climate sensitivity, and clarify a long‐overlooked but notable gap in our understanding of Earth's reference radiative response to warming.

 

Abstract The spectroscopic characterization of terrestrial exoplanets over a wide spectral range from the near- to the mid-infrared will be made possible for the first time with the JWST. One challenge is that it is not known a priori whether such planets possess optically thick atmospheres or even any atmospheres altogether. However, this challenge also presents an opportunity, the potential to detect the surface of an extrasolar world. This study explores the feasibility of characterizing with the JWST the atmosphere and surface of LHS 3844b, the highest signal-to-noise rocky thermal emission target among planets that are cool enough to have nonmolten surfaces. We model the planetary emission, including the spectral signal of both the atmosphere and surface, and we explore all scenarios that are consistent with the existing Spitzer 4.5 μ m measurement of LHS 3844b from Kreidberg et al. In summary, we find a range of plausible surfaces and atmospheres that are within 3 σ of the observationless reflective metal-rich, iron-oxidized, and basaltic compositions are allowed, and atmospheres are restricted to a maximum thickness of 1 bar, if near-infrared absorbers at ≳100 ppm are included. We further make predictions on the observability of surfaces and atmospheres and find that a small number (∼3) of eclipse observations should suffice to differentiate between surface and atmospheric features. We also perform a Bayesian retrieval analysis on simulated JWST data and find that the surface signal may make it harder to precisely constrain the abundance of atmospheric species and may falsely induce a weak H 2 O detection. 

Abstract Matsuno–Gill circulations have been widely studied in tropical meteorology, but their impact on stratospheric chemistry has seldom been explicitly evaluated. This study demonstrates that, in a model nudged to reanalysis, anticyclonic Rossby wave gyres that form near the tropopause as a result of equatorially symmetric heating in the troposphere provide a dynamical mechanism to influence tropical and subtropical atmospheric chemistry during near-equinox months. The anticyclonic flow entrains extratropical air from higher latitudes into the deep tropics of both hemispheres and induces cooling in the already cold upper-troposphere/lower-stratosphere (UTLS) region. Both of these aspects of the circulation allow heterogeneous chlorine activation on sulfuric acid aerosols to proceed rapidly, primarily via the HCl + ClONO 2 reaction. Precipitation rates and heating rates from reanalysis are shown to be consistent with these heating and circulation response patterns in the months of interest. This study analyzes specified dynamics simulations from the Whole Atmosphere Community Climate Model (SD-WACCM) with and without tropical heterogeneous chemistry to demonstrate that these circulations influence substantially the distributions of, for example, NO 2 and ClO in the UTLS tropics and subtropics of both hemispheres. This provides a previously unrecognized dynamical influence on the spatial structures of atmospheric composition changes in the UTLS during near-equinox months. 

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 ([Formula: see text]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⁻¹dominates, with a minor contribution from changes in dynamics.

 

The precipitation efficiency of convection (ε) plays an important role in simple models of the tropical atmosphere as well as in global climate models' projections of future climate changes, but remains poorly understood and poorly constrained. A particularly urgent question is howεwill change in warmer climates. To address these issues, this study investigates the precipitation efficiency in simulations of radiative‐convective equilibrium with a cloud‐resolving model forced by a wide range of sea surface temperatures (SSTs). Two different domains are considered: a small, doubly periodic domain, and a 2‐D (x‐z) “mock‐Walker” domain with a sinusoidal SST profile that resembles the equatorial Pacific, and the sensitivities of the results to the microphysical scheme and to the horizontal resolution are also explored. It is found thatεgenerally increases with warming in the small domain simulations because of increases in the efficiency with which cloud condensate is converted into precipitation, with changes in the re‐evaporation of falling precipitation playing a secondary role. This picture is complicated in the 2‐D simulations by substantial changes in the degree of convective organization as the underlying SSTs are varied.εis found to decrease as convection becomes more organized, because convective organization results in relatively more low clouds, which have small (≤0.1) precipitation efficiencies, and relatively less high clouds, which have larger (∼0.4) precipitation efficiencies.

 

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.