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@ARTICLE{Mindlin:1048120,
author = {Mindlin, Julia and Shepherd, Theodore G. and Osman, Marisol
and Vera, Carolina S. and Kretschmer, Marlene},
title = {{E}xplaining and predicting the {S}outhern {H}emisphere
eddy-driven jet},
journal = {Proceedings of the National Academy of Sciences of the
United States of America},
volume = {122},
number = {29},
issn = {0027-8424},
address = {Washington, DC},
publisher = {National Acad. of Sciences},
reportid = {FZJ-2025-04511},
pages = {e2500697122},
year = {2025},
abstract = {The summertime eddy-driven jet (EDJ) in the Southern
Hemisphere is a critical mediatorbetween regional climate
and large-scale phenomena, guiding synoptic systems
thatshape weather patterns. Uncertainties in global climate
models (GCMs)-particularlyin projecting changes in remote
drivers like tropical warming, stratospheric polarvortex
strengthening, and asymmetric tropical Pacific
warming-hinder predictions ofEDJ trends and associated
regional outcomes. In this study, we develop a
causalframework that combines observations, reanalysis
datasets, and storylines estimatedfrom the Coupled Model
Intercomparison Project (CMIP) projections to attributepast
EDJ changes and predict plausible future trajectories. Our
findings indicate thattropical warming has evolved along the
low end of plausible CMIP trajectories, whilethe
stratospheric polar vortex shows robust strengthening, both
strongly influencingobserved EDJ trends. Our results suggest
that $50\%$ of the observed EDJ latitudeshift can be
directly attributed to global warming (GW), and the
remaining $50\%$ toremote drivers whose attribution
toGWremains uncertain. Importantly,GCMsappearto accurately
estimate the observed latitudinal shifts but underestimate
the observedstrengthening of the EDJ, while the proposed
storylines are able to capture the observedtrend. By
integrating causal inference with climate storylines, our
approach narrowsthe divide between attribution and
prediction, offering a physically grounded methodto estimate
plausible pathways of future climate change.},
cin = {JSC},
ddc = {500},
cid = {I:(DE-Juel1)JSC-20090406},
pnm = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
(SDLs) and Research Groups (POF4-511)},
pid = {G:(DE-HGF)POF4-5111},
typ = {PUB:(DE-HGF)16},
doi = {10.1073/pnas.2500697122},
url = {https://juser.fz-juelich.de/record/1048120},
}