Robust intra-model teleconnection patterns for extreme heatwaves

Introduction: The goal of this study is to provide analysis of statistics and dynamics of extreme heatwaves over two areas of Europe, France and Scandinavia, while comparing and contrasting the representation in climate models and reanalysis. Methods: The 1000 year long datasets are generated using respectively two climate models of different complexity. The composite maps of the heatwaves found in these datasets are compared to the ones observed in reanalysis by estimating significance of such patterns. We also employ time series analysis, in particular compare return time plots and use Gaussian stochastic processes to model the temporal correlations for rare events. Results: Our investigation reveals that recurrent wavenumber three teleconnection patterns distinctly underpin heatwaves in France and Scandinavia. These patterns manifest in both surface temperature and mid-tropospheric geopotential height. For heatwaves of return times of 4 years such patterns are robustly represented across diverse models of complexity and reanalysis data. For longer return times, reanalysis records are too short to give statistically significant results, while models confirm the relevance of these large scale patterns for the most extreme heatwaves. Moreover, A time series analysis shows that heatwave indices defined at synoptic scale are fairly well described by Gaussian stochastic processes, and that these Gaussian processes reproduce well return time plots even for very rare events. Discussion: These results suggest that extreme heatwaves over different areas of Europe show recurrent typical behaviours in terms of long-range spatial correlations and subseasonal-scale temporal correlations. These properties are consistently represented among models of different complexity and observations, thus suggesting their relevance for a better understanding of the drivers and causes of the occurrence of extreme midlatitude heatwaves and their predictability.