Robust predictions of changes in evenness of global precipitation under global warming

Global mean precipitation is anticipated to increase by 2-4% per degree Kelvin, with intense events scaling at 7%, driven by boundary layer humidity. The understanding of the change in daily-to-annual precipitation probability density function remains rather incomplete. To address this knowledge gap, we employ Gini index to evaluate spatial unevenness and temporal inequality of precipitation under global warming in CMIP6 models. We observe heightened spatial unevenness of daily precipitation in tropics and extratropics over land and ocean. While the tropics maintain this unevenness over time, indicating large-scale convection aggregation, extratropical precipitation evens out with increasing timescales. This disparity suggests distinct processes governing daily and annual mean precipitation, underscoring the intensification of stronger storms over weaker events.

 

Globally, temporal inequality is on the rise, with more pronounced intensification in regions where projected precipitation deviates significantly from Clausius–Clapeyron scaling. Our hypothesis posits that the shift in precipitation distribution under warming projections stems from an increase in no-rain days coupled with rainfall events scaled by a constant. To assess this proposition, we construct a toy model predicting projected temporal inequality based on local hydroclimate conditions pre-warming, the projected mean precipitation, and a theorem-derived stretching parameter. The toy model demonstrates robust performance overall, except in regions notably influenced by the Hadley cell. Additionally, the model suggests that local precipitation events are scaled by a constant of approximately 1.07. Our analysis establishes meaningful connections among changes in mean precipitation, precipitation distribution, and dry-day number, offering comprehensive insights into hydroclimate transformations under global warming.