Enhanced risk of hotextremes unveiled by observation-constrained scenario projections

The ever-increasing frequency of extremely hot events poses significant
societal and scientific challenges due to their adverse impacts on humans
and natural systems, compounded by their unpredictable nature. Climate
models are primary tools for investigating root causes and anticipating
future changes, conveying vital information for decision-making. However,
inherent model uncertainties and errors hinder the accuracy of future
projections, particularly in extreme events. While observational
constraint theories show promise in addressing model issues, their
application often relies on empirical, regionally relevant relationships.
Here, we show that the future intensification of hot extremes and their
uneven spread critically depend on historical properties of thermal
distributions, with variability playing a key role. We devise universal
analytical relations that combine real-world observations with climate
model information, aiming for more reliable projections. Results reveal
that hot extremes may grow faster than models imply across much of the
global land. In vulnerable regions, expected increases could exceed
model-based predictions by 40% to more than twice as much, even at low
global warming levels. These findings provide a foundation for realistic
assessments of future risks due to deadly heat and underscore the need for
strengthened climate-change adaptation and mitigation efforts.