Abstract
This paper describes a quasi-3D Bayesian inversion of oceanographic tracer data from the South Atlantic Ocean. Initially, one active neutral-density layer is considered with an upper and lower boundary. The available hydrographic data are linked to model parameters (water velocities, diffusion coefficients) via a 3D advection–diffusion equation. A robust solution to the inverse problem can be obtained by introducing prior information about parameters and modeling the observation error. This approach estimates both horizontal and vertical flow as well as diffusion coefficients. A system of alternating zonal jets is found at the depths of the North Atlantic Deep Water, consistent with direct measurements of flow and concentration maps. A uniqueness analysis of the model is performed in terms of the oxygen consumption rate. The vertical mixing coefficient bears some relation to the bottom topography even though the authors do not incorporate topography into their model. The method is extended to a multilayer model, using thermal wind relations weakly in a local fashion (as opposed to integrating the entire water column) to connect layers vertically. Results suggest that the estimated deep zonal jets extend vertically, with a clear depth-dependent structure. The vertical structure of the flow field is modified by the tracer fields relative to the a priori flow field defined by thermal wind. The velocity estimates are consistent with independent observed flow at the depths of the Antarctic Intermediate Water; at still shallower depths, above the layers considered here, the subtropical gyre is a significant feature of the horizontal flow.
Corresponding author address: Radu Herbei, Department of Statistics, The Ohio State University, 1958 Neil Avenue, Columbus, OH 43210. herbei@stat.osu.edu
