Dynamics of eddying abyssal mixing layers over sloping rough topography
The abyssal overturning circulation is thought to be primarily driven by small-scale turbulent mixing. Diagnosed watermass transformations are dominated by rough topography "hotspots", where the bottom-enhancement of mixing causes the diffusive buoyancy flux to diverge, driving widespread downwelling in the interior—only to be overwhelmed by an even stronger up-welling in a thin Bottom Boundary Layer (BBL). These watermass transformations are significantly underestimated by one-dimensional (1D) sloping boundary layer solutions, suggesting the importance of three-dimensional physics. Here, we use a hierarchy of models to generalize this 1D boundary layer approach to three-dimensional eddying flows over realistically rough topography. When applied to the Mid-Atlantic Ridge in the Brazil Basin, the idealized simulation results are roughly consistent with available observations. Integral buoyancy budgets isolate the physical processes that contribute to realistically strong BBL upwelling. The downwards diffusion of buoyancy is primarily balanced by upwelling along the sloping canyon sidewalls and the surrounding abyssal hills. These flows are strengthened by the restratifying effects of submesoscale baroclinic eddies and by the blocking of along-ridge thermal wind within the canyon. Major topographic sills block along-thalweg flows from restratifying the canyon trough, resulting in the continual erosion of the trough's stratification. We propose simple modifications to the 1D boundary layer model which approximate each of these three-dimensional effects. These results provide local dynamical insights into mixing-driven abyssal overturning, but a complete theory will also require the non-local coupling to the basin-scale circulation.
Additional Information© 2022 American Meteorological Society. We thank the crews of the BBTRE and DoMORE field campaigns for collecting the observations that motivated this work. We acknowledge funding support from National Science Foundation Awards 1536515, 1736109, and 2149080. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant 174530. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. This research is also supported by the NOAA Climate and Global Change Postdoctoral Fellowship Program, administered by UCAR's Cooperative Programs for the Advancement of Earth System Science (CPAESS) under Award NA18NWS4620043B. Data availability statement. The source code for the MITgcm simulations and all of the Python code necessary to produce the figures are publicly available at github.com/hdrake/sim-bbtre. Our analysis of labeled data arrays is greatly simplified by the xarray package in Python (Hoyer and Hamman 2017).
Published - 1520-0485-JPO-D-22-0009-1.pdf