Key points are not available for this paper at this time.
This study examines the influence of large-scale atmospheric circulation patterns, specifically the Pacific-North American (PNA), Asian-Bering-North American (ABNA), and North Atlantic Oscillation (NAO) climate indices, on the likelihood of cold extremes across Canada, utilizing ERA5 data and CMIP6 model simulations. The analysis reveals that PNA is closely linked to cold anomalies in western Canada, ABNA influences the west and central regions, and NAO impacts eastern Canada. A decrease in the likelihood of cold extremes is attributed to human-induced climate change, using both unconditional event attribution and event attribution conditioned on the observed circulation patterns. Under similar atmospheric circulation patterns as observed, human-induced climate change reduced the likelihood of recent cold extremes by 3 to 10 times across Canadian regions in the current climate compared to the pre-industrial climate. Under both the current and pre-industrial climates, negative PNA/ABNA phases and positive NAO phases can increase the likelihood of regular cold extremes, with synergies between indices significantly amplifying risks. Conversely, the opposite phases can reinforce the climate signal, further reducing the probability of cold extremes. These findings highlight the critical role of natural variability in cold extreme dynamics, offering valuable insights for improved climate prediction, attribution, and regional adaptation strategies in Canada.
Liang et al. (Tue,) studied this question.