Exploring Sudden Stratospheric Warming Dynamics: A Data-Driven Analysis Using a Low-Dimensional Stochastic Model

Sudden Stratospheric Warmings (SSWs) are extreme atmospheric events characterized by a rapid weakening or breakdown of the polar vortex, often followed by profound impacts on surface weather. These include abrupt temperature anomalies, shifts in large-scale circulation patterns, modulation of jet streams, and an increased likelihood of cold-air outbreaks and altered storm tracks at mid-latitudes. As a result, SSWs play a pivotal role in shaping the occurrence and intensity of extreme weather events across the Northern Hemisphere. Although low-dimensional models have proven instrumental in elucidating the fundamental wave–mean flow interactions underlying SSWs, their ability to faithfully reproduce the full complexity, variability, and predictability of real atmospheric dynamics remains limited.

In this study, developed within the framework of the VORTEX project, we introduce a novel data-driven methodology to systematically assess the realism and predictive skill of low-dimensional models in simulating SSW dynamics. Our approach is based on two complementary metrics, dimension and persistence, which quantify, respectively, the effective dynamical complexity and the temporal coherence of the system. Together, these metrics provide a robust framework to evaluate how well simplified models capture the essential features of observed stratospheric variability.

Using this methodology, we investigate the sensitivity of SSW dynamics to large-scale tropospheric forcing and stochastic variability, both of which are known to be key contributors to vortex destabilization. To this end, we propose a stochastic low-order model that couples the Holton–Mass equations, representing wave–mean flow interactions, with a Langevin formulation that accounts for the bistable nature of the polar vortex.

Our results demonstrate that both the frequency and dynamical characteristics of SSWs exhibit a pronounced sensitivity to changes in tropospheric wave forcing and noise intensity. We identify critical thresholds beyond which the probability of vortex breakdown increases sharply, offering a mechanistic interpretation of the observed intermittency and variability of SSW events. These findings provide new insight into stratosphere–troposphere coupling and highlight the potential of data-driven diagnostics to bridge the gap between conceptual models and the complexity of the real atmosphere.