SuPerPoV: Score and Evolution of the Stratospheric Polar Vortex via Persistent Homology

Abstract Classifying the stratospheric polar vortex provides predictability for surface weather on extended‐range timescales. However, all definitions of these events proposed in over 60 years of study depend on empirically chosen parameters and yield different results when they change. Moreover, as previous definitions are based on static thresholds, it is not straightforward to use them to study the spatiotemporal evolution of the vortex. Here, we introduce SuPerPoV, a score system that computes height, and displacement and split scores using tools from Topological Data Analysis (TDA). The computation is entirely threshold‐free, open source, and does not require familiarity with TDA. The scores generally recover previous definitions of SSWs and ESV events, and are output for a user‐defined number of days, thus showing the evolution of the event. SuPerPoV offers a paradigm shift in the study of the polar vortex, bringing a deeper understanding of the polar vortex and related extreme events.