The stratosphere is connected to tropospheric weather and climate. In particular, extreme stratospheric circulation events are known to exert a dynamical feedback on the troposphere1. However, it is unclear whether the state of the stratosphere also affects the ocean and its circulation. A co-variability of decadal stratospheric flow variations and conditions in the North Atlantic Ocean has been suggested, but such findings are based on short simulations with only one climate model2. Here we assess ocean reanalysis data and find that, over the previous 30 years, the stratosphere and the Atlantic thermohaline circulation experienced low-frequency variations that were similar to each other. Using climate models, we demonstrate that this similarity is consistent with the hypothesis that variations in the sequence of stratospheric circulation anomalies, combined with the persistence of individual anomalies, significantly affect the North Atlantic Ocean. Our analyses identify a previously unknown source for decadal climate variability and suggest that simulations of deep layers of the atmosphere and the ocean are needed for realistic predictions of climate.
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We thank T. Delworth, P. Staten and C. Strong for their comments on an earlier version of this work. We thank the Geophysical Fluid Dynamics Laboratory for making the CM2.1 simulation data available to us. We acknowledge the World Climate Research Programm’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups for producing and making available their model output. For CMIP, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. This research used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231. T.R. and J.K. were supported by the University of Utah. E.M. and J.K. are grateful for partial funding by the European Commission’s 7th Framework Programme, under GA 226520, COMBINE project. Provision of computer infrastructure by the Center for High Performance Computing at the University of Utah is gratefully acknowledged.