Identification of mixing barriers in chemistry-climate model simulations using Renyi entropy

This study examines how the Renyi entropy statistical measure (RE; a generalization of Shannon entropy) can be applied to long-lived tracer data (e. g. methane), to understand mixing in the stratosphere. In order to show that RE can be used for this task we focus on the southern hemisphere stratosphere and the significant impact of the Antarctic polar vortex on the dynamics in this region. Using methane data from simulations of the chemistry-climate model SOCOL, we find clear patterns, consistent with those identified in previous studies of mixing. RE has the significant benefit that it is data driven and requires considerably less computational effort than other techniques. This initial study suggests that RE has a significant potential as a quantitative measure for analyzing mixing in the atmosphere.