Data-driven and physics-constrained estimates of surface temperature upper bounds for the Northern Hemisphere midlatitudes

Music City Center 

The last decade has seen a large number of severe heatwaves that were unprecedented in the observational record, highlighting the challenges associated with accurately quantifying the likelihood and magnitude of future extreme events. An alternative to such probabilistic assessments is identification of upper bounds that quantify the hottest surface air temperatures that can possibly be achieved by the end of the 21st century. Theory, simulations, and observational analyses support the existence of a finite upper bound for surface air temperature; however, estimates for future upper-bound values that are realistic and usable for planning remain unavailable. Here, we use atmospheric theory to constrain statistical estimates of surface air temperature upper bounds in the Northern Hemisphere midlatitudes where convection is the limiting mechanism for surface heating. We find that by incorporating atmospheric dynamics within a flexible spatial extremes copula, we can anticipate the most extreme heatwave events over the last four decades. Furthermore, surface and atmospheric humidity play an important role in modulating best- and worst-case upper bound estimates by accounting for the effect of dry-air entrainment. Ultimately, our results provide an important bridge between data-driven (purely statistical) and data-agnostic (purely theoretical) upper bound estimates of surface air temperature.

Spatial extremes