Extreme temperature indices in Eurasia in a CMIP6 multi‐model ensemble: Evaluation and projection

Abstract

AbstractIt is important to project the changes in extreme temperature in Eurasia, where more than two‐thirds of the world's population reside. Employing Phase 6 of the Coupled Model Intercomparison Project (CMIP6) simulations and extreme temperature indices defined by the expert team on climate change detection and Indices, we firstly evaluate the performance of the CMIP6 models, and then project the spatial patterns of changes in extreme temperature in different periods under shared social‐economic Pathway scenarios and at different global warming levels. The results show that the performance of the CMIP6 models in simulating the indices of the coldest day (TXn), the coldest night (TNn), summer days (SU), tropical nights (TR) and frost days (FD) are good. Therefore, these five indices were selected for projection. Overall, TXn, TNn, SU and TR show an increasing trend and FD a decreasing trend, consistent with global warming in the future. The responses to global warming tend to be strongest in high latitudes for TXn and TNn, in high latitudes and high‐altitude areas for FD, and in some low‐latitude areas for SU and TR. At the local scale over Eurasia, where the change is larger than the regional median level, the changes in extreme temperature indices at 1.5°C of global warming above pre‐industrial levels are projected to be reduced by 30–55% and 55–85%, respectively, compared with the situation at 2.0°C and 3.0 warming. If global warming could be controlled to within 2.0°C, the changes in extreme temperature indices over Eurasia would be reduced by up to 60% compared with the situation at 3.0°C warming. Therefore, if global warming can be controlled to within a low warming target, the risk of extreme temperature change will be greatly reduced in these regions.