The growing demand for water presents a significant sustainability challenge. Understanding vegetation changes is crucial, as plants significantly influence water exchange through transpiration. However, global climate models show considerable uncertainty in predicting future vegetation trends ranging from −0.007 to 0.083 m2 m⁻2 decade⁻1, impacting water management. Here, we apply an emergent constraint method to reduce uncertainty in global vegetation projections for the period 2015–2100 from a climate model ensemble (Coupled Model Intercomparison Project Phase 6 [CMIP6]), focusing on the leaf area index (LAI). Our approach reduces uncertainty in global LAI projections by 37.7%–53.1%. We find that this uncertainty is primarily due to incomplete representations of the CO
Elsevier, One Earth, Volume 8, 21 February 2025