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Published November 2016 | Published
Journal Article Open

A Theory of the Wind-Driven Beaufort Gyre Variability

Abstract

The halocline of the Beaufort Gyre varies significantly on interannual to decadal time scales, affecting the freshwater content (FWC) of the Arctic Ocean. This study explores the role of eddies in the Ekman-driven gyre variability. Following the transformed Eulerian-mean paradigm, the authors develop a theory that links the FWC variability to the stability of the large-scale gyre, defined as the inverse of its equilibration time. The theory, verified with eddy-resolving numerical simulations, demonstrates that the gyre stability is explicitly controlled by the mesoscale eddy diffusivity. An accurate representation of the halocline dynamics requires the eddy diffusivity of 300 ± 200 m2 s−1, which is lower than what is used in most low-resolution climate models. In particular, on interannual and longer time scales the eddy fluxes and the Ekman pumping provide equally important contributions to the FWC variability. However, only large-scale Ekman pumping patterns can significantly alter the FWC, with spatially localized perturbations being an order of magnitude less efficient. Lastly, the authors introduce a novel FWC tendency diagnostic—the Gyre Index—that can be conveniently calculated using observations located only along the gyre boundaries. Its strong predictive capabilities, assessed in the eddy-resolving model forced by stochastic winds, suggest that the Gyre Index would be of use in interpreting FWC evolution in observations as well as in numerical models.

Additional Information

© 2016 American Meteorological Society. Manuscript received 11 April 2016, in final form 22 July 2016, Published online 20 October 2016. The authors acknowledge the high-performance computing support from Yellowstone provided by NCAR's CIS Laboratory, sponsored by the NSF. GEM acknowledges the support from the Howland Postdoctoral Program Fund at WHOI and the Stanback Fellowship Fund at Caltech. MAS was supported by NSF Grants PLR-1415489 and OCE-1232389. AFT acknowledges support from NASA Award NNN12AA01C. The authors thank Prof. John Marshall and an anonymous reviewer for helpful comments and suggestions. The manuscript also benefited from discussions at the annual Forum for Arctic Modeling and Observing Synthesis (FAMOS) funded by the NSF OPP Awards PLR-1313614 and PLR-1203720.

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