PNNL

Abstract

Reliable regional temperature projections including heat extremes are essential for climate change adaptation and mitigation. Taking China as an example, simple averages from CMIP6 (Coupled Model Intercomparison Project Phase 6) models project high warming due to sampling many high climate sensitivities in the ensemble. Here, we develop an emergent constraint framework to obtain constrained mean and daily maximum temperature (TXx) warming over China by using observed global warming and local residual warming. The constrained annual mean and TXx warming over China (2.33? [1.61?~3.05?] and 2.31? [1.21?~2.99?]) are 0.65? [0.04?~1.76?] and 0.63? [–0.50?~2.39?], respectively, lower than raw projections (2.98? [1.85?~4.22?] and 2.94? [2.04?~4.39?]) for 2080~2099 under the intermediate-emission scenario. Approximately half model uncertainty is reduced after constraint. The land area (population) experiencing temperature extremes in our metric is 73% (85%) of the raw projections. Our results imply a lower impact of extreme heat than implied by current raw CMIP6 projections.