Internal Variability as Drivers of Compound Events in a Large Ensemble

The drivers of observed multivariate (compound) extreme events, such as compound heat and drought, have most often been explored through individual case studies. Additionally, there has been increased attention on how the frequency and intensity of extreme events will be impacted by anthropogenic climate change. Much less research has been conducted on compound extreme events at the global and decadal scale driven only by internal climate variability. We investigate globally hot and dry compound extremes due to internal variability in the CESM2 100-member large ensemble. We first investigate the presence of hot and dry compound events due to internal variability from 1850-2000 using monthly temperature and precipitation data. We then use sea-surface temperature composite maps to analyze conditions under which these events occur, and thus identify drivers. In particular, we explore how several, prominent large-scale climate modes affect the frequency of compound events. We also look into patterns from ERA5 Reanalysis data to demonstrate how well the CESM2 relationships translate to observations. Understanding the role of internal climate variability on compound events at the global scale has the potential to improve the skill of future predictions of these events.