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Abstract
Across the stable density stratification of the abyssal ocean, deep dense water is slowly propelled upward by sustained, though irregular, turbulent mixing. The resulting mean upwelling determines large-scale oceanic circulation properties like heat and carbon transport. In the ocean interior, this turbulent mixing is caused mainly by breaking internal waves: generated predominantly by winds and tides, these waves interact nonlinearly, transferring energy downscale, and finally become unstable, break and mix the water column. This paradigm, long parameterized heuristically, still lacks full theoretical explanation. Here, we close this gap using wave-wave interaction theory with input from both localized and global observations. We find near-ubiquitous agreement between first-principle predictions and observed mixing patterns in the global ocean interior. Our findings lay the foundations for a wave-driven mixing parameterization for ocean general circulation models that is entirely physics-based, which is key to reliably represent future climate states that could differ substantially from today’s.
The authors use interacting internal wave theory and global observational databases to calculate the turbulent energy rate available for ocean mixing, which is a critical metric for climate prediction that is still lacking rigorous understanding.
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1 Università degli Studi di Torino, Dipartimento di Fisica, Torino, Italy (GRID:grid.7605.4) (ISNI:0000 0001 2336 6580); Woods Hole Oceanographic Institution, Physical Oceanography Department, Woods Hole, USA (GRID:grid.56466.37) (ISNI:0000 0004 0504 7510)
2 University of California San Diego, Scripps Institution of Oceanography, La Jolla, USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242)
3 Universität Hamburg, Institut für Meereskunde, Hamburg, Germany (GRID:grid.9026.d) (ISNI:0000 0001 2287 2617)
4 Woods Hole Oceanographic Institution, Physical Oceanography Department, Woods Hole, USA (GRID:grid.56466.37) (ISNI:0000 0004 0504 7510)
5 University of Washington, Applied Physics Laboratory, Seattle, USA (GRID:grid.34477.33) (ISNI:0000 0001 2298 6657)
6 Rensselaer Polytechnic Institute, Department of Mathematical Sciences, Troy, USA (GRID:grid.33647.35) (ISNI:0000 0001 2160 9198)