Projections of climate change and its impacts based on CMIP6 models—calling attention to quantifying and constraining uncertainty

Abstract Accurately projecting climate change and its impact is crucial for quantifying the risk of extreme events and developing effective adaptation strategies. However, future projections exhibit substantial uncertainties among Earth system models (ESMs). Notably, the latest phase of the Coupled Model Intercomparison Project includes some ‘hot’ ESMs with high climate sensitivity that exceed the likely range inferred from multiple lines of evidence, leading to a broader uncertainty range compared to previous CMIP phases. Although various uncertainty quantification and constraint methods have been proposed, they are not yet widely adopted. The approach of using an equal-weighted ensemble average for projections remains prevalent. Here we examine commonly used uncertainty quantification methods and constraint projection methods, describing their characteristics. Subsequently, taking extreme precipitation as a case, we constrain the range of projection uncertainty employing two weighing constraint methods and two emergent constraint methods. The results demonstrate that all methods effectively reduce the uncertainty in extreme precipitation projections. Specifically, the comprehensive constraints reduce the projection uncertainty by 26%–31% at the long-term future (2081–2100) under different scenarios. Therefore, we strongly recommend that attention should be paid to quantifying and constraining uncertainty when undertaking future projections of climate change and its impacts.