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.

Heatwaves damage societies globally and are intensifying with global warming. Several mechanistic drivers of heatwaves, such as atmospheric blocking and soil moisture-atmosphere feedback, are well-known for their ability to raise surface air temperature. However, what limits the maximum surface air temperature in heatwaves remains unknown; this became evident during recent Northern Hemisphere heatwaves which achieved temperatures far beyond the upper tail of the observed statistical distribution. Here, we present the hypothesis, with corroborating evidence, that convective instability limits annual maximum surface air temperatures (TXx) over midlatitude land. We provide a theory for the upper bound of midlatitude temperatures, which accurately describes the observed relationship between temperatures at the surface and in the mid-troposphere. Known heatwave drivers shift the position of the atmospheric state in the phase space described by the theory, changing its proximity to the upper bound.Our theory suggests that the upper bound for midlatitude TXx should increase 1.9 times as fast as 500-hPa temperatures. Using empirical 500-hPa warming, we project that the upper bound of TXx over Northern Hemisphere midlatitude land (40°N-65°N) will increase about twice as fast as global mean surface air temperature, and TXx will increase faster than this bound over regions that dry on the hottest days.

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.

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.

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.