Future projections of precipitation are uncertain, hampering effective climate adaptation strategies globally. Our understanding of changes across multiple climate model simulations under a warmer climate is limited by this lack of coherence across models. We address this challenge by introducing a novel approach to detect agreement in drier and wetter conditions evaluating continuous time-series with trends across 146 Global Climate Models (GCMs) under elevated greenhouse gas (GHG) emissions.

The approach detected agreement across multiple models in future wetting and drying trends, revealing critical information on how precipitation is projected to change under scenarios associated with continued GHG emissions. By looking into the time-series of individual models with flexible trend detection methods, the approach provides a more robust quantification of change, summarising critical multi-model information.

We show the hotspots of future drier and wetter conditions, including regions already experiencing water scarcity or excess. These patterns are projected to impact a significant portion of the global population, with approximately 3 billion people (38% of the world's current population) affected under an intermediate emissions scenario and 5 billion people (65.6% of the world population) under a high emissions scenario by the century's end. We provide the first country-level analysis quantifying the population exposed to significant changes in precipitation regimes, offering a robust framework for assessing multiple climate projections. These new findings can directly assist with designing ‘fit for purpose’ climate adaptation policies and reduce uncertainty in which direction precipitation is projected to change globally under different emissions pathways.