Constraining climate model projections with observations amplifies future runoff declines

Abstract

Climate models are increasingly used to inform water availability projections at regional scales. However, the models’ own runoff sensitivities—the change in runoff per unit change of precipitation or temperature—are often biased, which can degrade their projections of runoff change. Specifically, models tend to underestimate the runoff decline in response to a temperature increase. Here, we conduct a comprehensive analysis with multiple observational datasets, two climate model generations, and large ensemble sampling of internal climate variability to assess these biases and to constrain future runoff projections across major river basins globally. For basins that can be robustly constrained by available observations, the constraint indicates stronger runoff declines than raw model projections. The constrained projections thus indicate more severe impacts of climate change on water resources than indicated by direct climate model output.