Insights on the statistics of extreme Arctic sea ice conditions from the EC-Earth3 climate model

Various studies identified possible drivers of extreme Arctic sea ice reduction, such as observed in the summers of 2007 and 2012, including sea ice-ocean preconditioning, large-scale atmospheric circulation variability and synoptic-scale cyclones. However, a robust quantitative statistical analysis and a better understanding of the predictability of extreme sea ice lows are hindered by the small number of events that can be sampled in observations and numerical simulations. Recent studies tackled the problem of sampling climate extremes by using rare event algorithms, i.e., computational techniques developed in statistical physics to reduce the computational cost required to sample rare events in numerical simulations. Here we apply a rare event algorithm to ensemble simulations with the European community Earth-System-Model version 3 (EC-Earth3) to study extremes of intra seasonal pan-Arctic sea ice area reduction under present-day climate conditions. The rare event simulations produce sea ice area anomalies larger in magnitude than observed in 2012, and we compute statistically significant composite maps of dynamical quantities conditional on the occurrence of extremes with probabilities of less than 1%. We exploit the improved statistics of low sea ice states to study their drivers on synoptic to seasonal time scales, including a sea ice area and sea ice volume budget analysis to disentangle the roles of dynamic vs. thermodynamic forcing on the sea ice. On statistical average over the extremes, enhanced thermodynamic melting accounts for approximately 75% of enhanced sea ice area and volume loss and predominately occurs on the Pacific-North American side, while enhanced dynamic sea ice loss appears on the Eurasian side of the Arctic. Finally, we show that extreme sea ice lows are on average preceded by persistent cyclonic mean sea level pressure anomalies over the central to eastern Arctic during the spring-summer transition. These low-pressure systems promote sea ice loss thermodynamically due to enhanced moisture and heat flux convergence, cloudiness, surface downward longwave radiative fluxes and dynamically through the impact of anomalous winds on the transport of sea ice.