Summertime Arctic and North Atlantic–Eurasian circulation regimes under climate change

Abstract. This study explores the projected response of atmospheric circulation regimes, which are preferred and recurrent large-scale circulation patterns, to future climate change scenarios. We focus on the North Atlantic–Eurasian and Arctic regions in the boreal summer season. Using Simulated Annealing and Diversified Randomization (SAN) and K-means (KME) clustering methods, we analyse 20 global climate models from the CMIP6 ensemble to assess shifts in frequency of occurrence of circulation regimes for the end of the century under a high emission scenario. Additionally, storylines of summer Arctic climate change constrained by Barents–Kara Seas warming and Arctic Amplification are incorporated to contextualize potential future atmospheric behaviours. Despite slight differences between the SAN and KME methods in identifying spatial regime structures, the patterns remain largely unchanged under future climate scenarios. Our analysis highlights the changing frequency of atmospheric circulation regimes under climate change. A significant occurrence change is detected for the North Atlantic Oscillation (NAO) regime by both methods, where positive phases are projected to become more frequent, consistent with previous studies. In the Arctic region, both clustering algorithms predict an increase in circulation regimes linked to negative pressure anomalies above the Arctic. This aligns with the projected increased occurrence of the positive NAO regime over the North Atlantic–Eurasian sector. Our analysis underscores that, while storylines provide a nuanced approach to exploring plausible climate futures, no consistent shifts in the occurrence of atmospheric circulation regimes emerge across the two studied storylines, possibly due to the small number of models representing each storyline. Furthermore, influences from regional climate changes such as Barents–Kara seas warming and Arctic Amplification exhibit minimal impact on overarching circulation regimes. These findings contribute to an improved understanding of the sensitivity of atmospheric circulation regimes to climate change, with implications for predicting future extreme weather occurrences across these key regions.