Biased Estimates of Changes in Climate Extremes From Prescribed SST Simulations

Abstract

Abstract Large climate model ensembles are widely used to quantify changes in climate extremes. Here we demonstrate that model‐based estimates of changes in the probability of temperature extremes at 1.5 °C global warming regionally differ if quantified using prescribed sea surface temperatures (SSTs) instead of using a fully coupled climate model. Based on the identical climate model used in two experimental setups, we demonstrate that particularly over the tropics and Australia estimates of the changes in the odds of annual temperature extremes can be up to more than a factor of 5 to 10 larger using prescribed SSTs rather than a fully coupled model configuration. The two experimental designs imply a different perspective on framing projections. If experiments conditional on prescribed observed SSTs are interpreted as unconditional real‐world projections, they project changes in extremes that are systematically biased high and overconfident. Our results illustrate the importance of carefully considering experimental design when interpreting projections of extremes.

Keywords

• extremes
• climate variability
• attribution
• climate model