The physical basis for increases in precipitation extremes in simulations of 21st-century climate change

TLDR

Global warming is expected to increase atmospheric water vapor and intensify precipitation extremes, a relationship widely assumed to be proportional. The study provides a physical basis for how precipitation extremes change with climate, showing that their changes depend on moist‑adiabatic lapse rate, upward velocity, and temperature at extreme events. The authors derive a theory linking precipitation extremes to moist‑adiabatic lapse rate, upward velocity, and temperature at extreme events. Simulations show that tropical precipitation extremes are poorly simulated and vary across models, whereas extratropical extremes increase more slowly than atmospheric water vapor, underscoring the need to improve upward velocity representation in tropics while supporting robust extratropical predictions.

Abstract

Global warming is expected to lead to a large increase in atmospheric water vapor content and to changes in the hydrological cycle, which include an intensification of precipitation extremes. The intensity of precipitation extremes is widely held to increase proportionately to the increase in atmospheric water vapor content. Here, we show that this is not the case in 21st-century climate change scenarios simulated with climate models. In the tropics, precipitation extremes are not simulated reliably and do not change consistently among climate models; in the extratropics, they consistently increase more slowly than atmospheric water vapor content. We give a physical basis for how precipitation extremes change with climate and show that their changes depend on changes in the moist-adiabatic temperature lapse rate, in the upward velocity, and in the temperature when precipitation extremes occur. For the tropics, the theory suggests that improving the simulation of upward velocities in climate models is essential for improving predictions of precipitation extremes; for the extratropics, agreement with theory and the consistency among climate models increase confidence in the robustness of predictions of precipitation extremes under climate change.