The Lifecycle and Physical Drivers of Heatwaves in a Hierarchy of Model Simulations

Heatwaves are extreme weather events characterized by extreme near-surface temperature anomalies that persist for several days, which lead to catastrophic impacts on natural ecosystems, agriculture, human health, and economies. Different physical processes can contribute to the increase in temperature associated with heatwaves. Previous studies have shown that adiabatic compression due to subsidence and local land-atmosphere coupling are important drivers of summer heatwaves. However, less is known about the respective roles of these processes for heat extremes occurring in different seasons and latitudes.

By analyzing the different terms of the temperature tendency equation, we quantify the relative importance of horizontal wind advection, adiabatic, and diabatic processes (including radiation and surface fluxes) during the lifecycle of realistic and idealized heatwaves. We identify heatwaves both in reanalysis and in simulations using the ICOsahedral Nonhydrostatic (ICON) climate model. These simulations range from a simple zonally symmetric temperature relaxation and dry dynamics to a simulation using full physics, with coupled land and sea surface temperature forcing. This step-wise inclusion of physical processes and increasing model complexity allows us to identify the key drivers of extreme warm events and the characteristics of these across the different model complexities. In the simplest model configuration, i.e. only dry dynamics and no surface coupling, extreme temperature events are generally shorter but produce more intense temperature anomalies in the midlatitudes, where the horizontal temperature gradient is strongest. These idealized heatwaves are almost entirely driven by a very strong advection of warm air from more equatorward locations and are linked to local amplification of Rossby wave packets and atmospheric blocking. In contrast, in the complex model configuration as well as in reanalysis, summer heatwaves over land areas are mainly driven by adiabatic and diabatic processes, while advection is of secondary importance. On the other hand, extreme warm periods during winter are mainly driven by advection both in the model and reanalysis. Identifying the most relevant processes driving heatwaves can potentially benefit the prediction and representation of extreme events in operational weather and climate forecasts.