Humid heatwaves, characterized by high temperature and humidity combinations, challenge tropical societies. Extreme wet-bulb temperatures (TW) over tropical land are coupled to the warmest sea surface temperatures (SST) by atmospheric convection and wave dynamics. Here, we harness this coupling for seasonal forecasts of the annual maximum of daily maximum TW (TWmax). We develop a multiple linear regression model that explains 80% of variance in tropical mean TWmax and significant regional TWmax variances. The model considers warming trends and El Niño and Southern Oscillation (ENSO) indices. Looking ahead, a moderate-to-strong El Niño with an Oceanic Niño Index (ONI) of 1.5 by the end of 2023 suggests a 42% (11%, 78%) probability of breaking the tropical mean TWmax record in 2024. For an El Niño similar to 2015/2016 (ONI of 2.64), the probability escalates to 90% (50%, 99.5%). This approach also holds promise for regional TWmax predictions.

Global storm-resolving model (GSRM) simulations (kilometer-scale horizontal resolution) of the atmosphere can capture the interaction between the scales of deep cumulus convection and the large-scale dynamics and thermodynamic properties of the atmosphere. Here, we assess the vertical structure of tropical temperature change in the GSRM X-SHiELD, developed by the Geophysical Fluid Dynamics Laboratory, perturbed by a uniform sea surface temperature (SST) warming and/or increased CO2 concentration. The simulated response to SST warming shows weakly amplified warming from the surface through the mid-troposphere before increasing to a factor of about 2.5 near the tropopause. This combination of muted warming in the mid-troposphere and amplified warming aloft is within the range of CMIP6 models at individual pressure levels but, taken together, is distinctive behavior. The response to CO2 increase with unchanged SST is an approximately vertically uniform warming, comparable to CMIP6 models, and is linearly additive with the SST-induced warming in X-SHiELD.

Global warming is expected to increase global mean precipitation by 2-4%/K, but this increase may be very uneven, leading to more flooding but also droughts. Utilizing the Gini index, a metric frequently used in economics, we analyze the unevenness of precipitation distribution locally and globally from daily to annual-mean timescale in CMIP6 global warming simulations. The unevenness of daily precipitation increases in all models over land and ocean, tropics and extratropics. Local-daily precipitation unevenness changes show a complex geographic pattern. However, particularly over land, we show that a simple theoretical scaling explains this complexity to result from increased precipitation intensity scaling at about the Clausius-Clapeyron rate, and a local balance between changes in time-mean precipitation and dry-day fraction. These results provide a novel perspective on the relation between global constraints on hydrological cycle to regional precipitation changes independent of changes in the quasi-stationary atmospheric circulation and geographic distribution of precipitation.

Radiative cooling on the lowest atmospheric levels is of strong importance for modulating atmospheric circulations and organizing convection, but detailed observations and a robust theoretical understanding are lacking. Here we use unprecedented observational constraints from subsidence regimes in the tropical Atlantic to develop a theory for the shape and magnitude of low-level longwave radiative cooling in clear-sky, showing large peaks at the top of the boundary layer. A suite of novel scaling approximations is first developed from simplified spectral theory, in close agreement with the measurements. The radiative cooling peak height is set by the maximum lapse rate in water vapor path, and its magnitude is mainly controlled by the ratio of column relative humidity above and below the peak. We emphasize how elevated intrusions of moist air can reduce low-level cooling, by sporadically shading the spectral range which effectively cools to space. The efficiency of this spectral shading depends both on water content and altitude of moist intrusions; its height dependence cannot be explained by the temperature difference between the emitting and absorbing layers, but by the decrease of water vapor extinction with altitude. This analytical work can help to narrow the search for low-level cloud patterns sensitive to radiative-convective feedbacks: the most organized patterns with largest cloud fractions tend to occur in atmospheres below 10% relative humidity and feel the strongest low-level cooling. This motivates further assessment of these favorable conditions for radiative-convective feedbacks and a robust quantification of corresponding shallow cloud dynamics in current and warmer climates.

Recent advances have allowed for integration of global storm resolving models (GSRMs) to a timescale of several years. These short simulations are sufficient for studying characteristics and statistics of short- and small-scale phenomena; however, it is questionable what we can learn from these integrations about the large-scale climate response to perturbations. To address this question, we use the response of X-SHiELD (a GSRM) to uniform SST warming and CO$_2$ increase in a two-year integration and compare it to similar CMIP6 experiments. Specifically, we assess the statistical meaning of having two years in one model outside the spread of another model or model ensemble. This is of particular interest because X-SHiELD shows a distinct response of the global mean precipitation to uniform warming, and the northern hemisphere jet shift response to isolated CO$_2$ increase. We use the CMIP6 models to estimate the probability of two years in one model being more than one standard deviation away from another model (ensemble) mean, knowing the mean of two models. For example, if two years in one model are more than one standard deviation away from the other model’s mean, we find that the chances for these models’ means to be within one standard deviation are $\sim 25\%$. We find that for some large-scale metrics, there is an important base-state dependence that, when taken into account, can qualitatively change the interpretation of the results. We note that a year-to-year comparison is physically meaningful due to the use of prescribed sea-surface-temperature simulations.

Intense convection (updrafts exceeding 10 m∙s-1) plays an essential role in severe weather and Earth’s energy balance. Despite its importance, how the global pattern of intense convection changes in response to warmed climates remains unclear, as simulations from traditional climate models are too coarse to simulate intense convection. Here we take advantage of a kilometer-scale global storm resolving model and conduct year-long simulations of a control run, forced by analyzed sea surface temperature (SST), and one with a 4-K increase in SST for comparison. Comparisons show that the increased SST enhances the frequency of intense convection globally with large spatial and seasonal variations. Increases in the intense convection frequency do not necessarily reflect increases in convective available potential energy (CAPE). Results are also compared with traditional climate model projections. Changes in the spatial pattern of intense convection are associated with changes in planetary circulation.

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 also needs to be taken into account in order 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 the 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 likely (66 per cent 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.

Mixed phase clouds, consisting of ice particles and super cooled liquid droplets, predominantly found in Arctic, are poorly represented in various climate models. A unique tethered balloon campaign carrying 4π radiometer, a cloud particle imager, and a meteorological package on board was conducted in Ny-Ålesund, Norway, located high in the Arctic at 78.91°N, 11.91°E during May-June 2008. The radiometric and cloud observations at 500nm and 800nm were collected during a month long experimental campaign. A state-of-the-art discrete ordinate radiative transfer model was used to estimate optimal cloud optical properties. These optical properties are contrasted with those of the cloud parameterization in the new NOAA-GFDL AM4 model that is presently being used in the Coupled Model Intercomparison Project 6 (CMIP6). The improved simulation of cloud optical properties will aid in understanding cloud radiation feedbacks and better representation of clouds in global climate model.

The geographic rearrangement of the tropical oceanic and atmospheric circulation during an El Niño event is associated with a well-understood strong surface warming of the climatologically cold eastern equatorial Pacific. However, the concomitant warming of the warmest waters where deep convection occurs - responsible for the tropics-wide free tropospheric warming- is less well understood. Here, we show that in both a coupled atmosphere-ocean climate model and in reanalysis data, El Niño is associated with an increase in evaporation over the colder ~70%, but with a decrease in evaporation over the warmest ~30% of the tropical oceans where atmospheric deep convection connects the surface with the free troposphere. The reduction in evaporation is driven by a weakening of the near-surface winds. We propose that the prominent tropics-wide warming during El Niño is a consequence of the reduction of near-surface winds in regions of deep convection due to the anomalous large-scale circulation.

The linearity of the global-mean outgoing longwave radiation (OLR) with surface temperature has important implications for climate sensitivity. Global climate models robustly produce a 1.9 W/m2/K of global-mean longwave clear-sky (LWCS) feedback. This number is consistent with idealized single-column atmospheric models. However, there is considerable spatial variation in the LWCS feedback including negative values over tropical oceans known as the “super-greenhouse effect” which is compensated by larger values in the subtropics/extratropics. Therefore it is unclear how the idealized model results are relevant for the global-mean LWCS feedback in comprehensive climate models. Here we show with a simple analytical theory and model output that the compensation of this spatial variability to produce a robust global-mean feedback can be explained by two facts: 1) when conditioned upon free-tropospheric column relative humidity (RH), the LWCS feedback is independent of RH, and 2) the global histogram of column RH is largely invariant under warming.

Meridional gradients in CO2 forcing are known to drive increases in poleward heat transport (Huang and Zhang 2014, Huang et al. 2017). However, the climate factors which control these meridional forcing gradients are not well understood. Building upon the work of Wilson (2012), we build a first-principles, analytical model for CO2 forcing which requires as input only the temperatures at the surface and roughly 30 hPa, as well as column relative humidity. This model quantitatively captures global variations in clear-sky CO2 forcing, and shows that the meridional forcing gradient is directly attributable to the meridional surface temperature gradient.

We show that in the tropics, tropical atmospheric dynamics force the subcloud moist static energy (MSE) over land and ocean to be very similar in, and only in, regions of deep convection. Using observed rainfall as a proxy for convection and reanalysis data to calculate MSE, we show that subcloud MSE in the non-convective regions may differ substantially between land and ocean but is uniform across latitudes in convective regions even on a daily timescale. This result holds also in CMIP5 model simulations of past cold and future warm climates. Furthermore, the distribution of rainfall amount in subcloud MSE is very similar over land and ocean with the peak at 343 J/g and a half width at half maximum of 3 J/g. As a result, the annual-maximum subcloud MSE at each location over land and ocean is subject to a common upper bound set by the convective regions.