Climate Process Team on internal wave–driven ocean mixing

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Date
2017-12-01
Authors
MacKinnon, Jennifer A.
Zhao, Zhongxiang
Whalen, Caitlin B.
Waterhouse, Amy F.
Trossman, David S.
Sun, Oliver M.
St. Laurent, Louis C.
Simmons, Harper L.
Polzin, Kurt L.
Pinkel, Robert
Pickering, Andrew I.
Norton, Nancy J.
Nash, Jonathan D.
Musgrave, Ruth C.
Merchant, Lynne M.
Melet, Angelique
Mater, Benjamin D.
Legg, Sonya
Large, William G.
Kunze, Eric
Klymak, Jody M.
Jochum, Markus
Jayne, Steven R.
Hallberg, Robert
Griffies, Stephen M.
Diggs, Stephen
Danabasoglu, Gokhan
Chassignet, Eric P.
Buijsman, Maarten C.
Bryan, Frank O.
Briegleb, Bruce P.
Barna, Andrew
Arbic, Brian K.
Ansong, Joseph
Alford, Matthew H.
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DOI
10.1175/BAMS-D-16-0030.1
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Abstract
Diapycnal mixing plays a primary role in the thermodynamic balance of the ocean and, consequently, in oceanic heat and carbon uptake and storage. Though observed mixing rates are on average consistent with values required by inverse models, recent attention has focused on the dramatic spatial variability, spanning several orders of magnitude, of mixing rates in both the upper and deep ocean. Away from ocean boundaries, the spatiotemporal patterns of mixing are largely driven by the geography of generation, propagation, and dissipation of internal waves, which supply much of the power for turbulent mixing. Over the last 5 years and under the auspices of U.S. Climate Variability and Predictability Program (CLIVAR), a National Science Foundation (NSF)- and National Oceanic and Atmospheric Administration (NOAA)-supported Climate Process Team has been engaged in developing, implementing, and testing dynamics-based parameterizations for internal wave–driven turbulent mixing in global ocean models. The work has primarily focused on turbulence 1) near sites of internal tide generation, 2) in the upper ocean related to wind-generated near inertial motions, 3) due to internal lee waves generated by low-frequency mesoscale flows over topography, and 4) at ocean margins. Here, we review recent progress, describe the tools developed, and discuss future directions.
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Author Posting. © American Meteorological Society, 2017. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 98 (2017): 2429-2454, doi:10.1175/BAMS-D-16-0030.1.
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Bulletin of the American Meteorological Society 98 (2017): 2429-2454
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