Projections and uncertainty decomposition in CMIP6 models for extreme precipitation scaling rates

• Climate models are the main source of uncertainty in projecting future scaling rates. • Use at least nine models for reliable scaling rate projections. • Regional uncertainty varies between CMIP5 and CMIP6, with small global-scale variations. As temperatures rise, extreme precipitation is expected to intensify, following the Clausius–Clapeyron relation, which indicates a 7 % increase in extreme precipitation for every 1 °C rise in temperature. However, recent studies reveal considerable uncertainty in estimating the rate of change in extreme precipitation (scaling rate), especially in future projections. This study aims to quantify the contribution to scaling rate projections by focusing on three primary factors: Global Circulation Models (GCMs), future emission scenarios, and scaling methods. Additionally, we examine the minimum number of GCMs required for robust analysis and compare the uncertainty contributions between CMIP5 and CMIP6 to assess differences between the two CMIP generations. Our findings reveal substantial variations in the projected global and regional scaling rates, along with significant temporal changes. While GCMs are the primary source of uncertainty in scaling rates, using fewer GCMs tends to underestimate their influence on uncertainty and overestimate the impact of other sources. Furthermore, to ensure robust results, we recommend using at least nine GCMs in scaling rate projections, though some regional variations may still occur. Lastly, our evaluation reveals that while both CMIP5 and CMIP6 show comparable spatial distributions, CMIP5 exhibits greater uncertainty. Although global averages reveal only minor differences in uncertainty contributions from each source between the two generations, significant regional variations, particularly in the northeastern Eurasian region, have been identified. We believe that this comprehensive understanding of uncertainty in scaling rates will enhance future projections and support the development of effective strategies for managing extreme precipitation in future water policy planning.