Explaining and predicting the Southern Hemisphere eddy-driven jet

• 成果类型: Article
• 署名作者: Mindlin, Julia; Shepherd, Theodore G.; Osma, Marisol; Vera, Carolina S.; Kretschmer, Marlene; Marengo, Jose A.
• 署名单位: University of Reading; Helmholtz Association; Research Center Julich; University of Buenos Aires; Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET)
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-11699
• DOI: 10.1073/pnas.2500697122
• 发表日期: 2025-07-22
• 关键词: atmospheric circulation response; storylines; emergent; forcings; TRENDS; IMPACT

摘要

The summertime eddy-driven jet (EDJ) in the Southern Hemisphere is a critical mediator between regional climate and large-scale phenomena, guiding synoptic systems that shape weather patterns. Uncertainties in global climate models (GCMs)-particularly in projecting changes in remote drivers like tropical warming, stratospheric polar vortex strengthening, and asymmetric tropical Pacific warming-hinder predictions of EDJ trends and associated regional outcomes. In this study, we develop a causal framework that combines observations, reanalysis datasets, and storylines estimated past EDJ changes and predict plausible future trajectories. Our findings indicate that tropical warming has evolved along the low end of plausible CMIP trajectories, while the stratospheric polar vortex shows robust strengthening, both strongly influencing observed EDJ trends. Our results suggest that 50% of the observed EDJ latitude shift can be directly attributed to global warming (GW), and the remaining 50% to remote drivers whose attribution to GW remains uncertain. Importantly, GCMs appear to accurately estimate the observed latitudinal shifts but underestimate the observed strengthening of the EDJ, while the proposed storylines are able to capture the observed trend. By integrating causal inference with climate storylines, our approach narrows the divide between attribution and prediction, offering a physically grounded method to estimate plausible pathways of future climate change.