In the US, extreme heat causes the largest weather-related deaths, and their frequency is projected to increase under global warming. We apply a storyline approach to identify coherent narratives of the spatial patterns of heatwave days in the contiguous United States (CONUS) in a 3 °C warmer climate. We use daily temperature data from the seamless system for prediction and earth system research large-ensemble climate model under the shared socio-economic pathway 5–8.5. We find that CONUS surpasses the 3 °C-warming threshold (relative to 1921–1950) between the mid-2020s and early 2040s across all 30 ensemble members. Despite similar spatial patterns of annual mean surface temperatures over the CONUS in the 3 °C-crossing years, the simulated heatwave days are clustered into four distinct spatial patterns: Southeastern, Mountain-Central, Western-Severe, and Western-Mild. The Western-Mild pattern is the most frequent (19 out of 30 realizations) with the fewest annual heatwave days, while the remaining patterns tend to experience a greater number of annual heatwave days and are less common (3 or 4 out of 30). We present four case studies corresponding to the representative clusters to better understand local extreme heat storylines, highlighting how the maximum annual mean temperature at the local scale might differ from the continental scale. Specifically, we find very severe potential conditions in the 3 °C-passing years with parts of the US potentially experiencing more than 150 cumulative heatwave days. This study implies that careful consideration of local temperature changes will be necessary to provide various climate adaptation policy perspectives.

Read original article

Read original article