Tracer and Observationally-Derived Constraints on Diapycnal Diffusivities in an Ocean State Estimate

Abstract. Use of an ocean parameter and state estimation framework–such as the Estimating the Circulation & Climate of the Ocean (ECCO) framework–could provide an opportunity to learn about the spatial distribution of the diapycnal diffusivity parameter (κρ) that observations alone cannot due to gaps in coverage. However, we show that the assimilation of existing in situ temperature, salinity, and pressure observations is not sufficient to constrain κρ estimated with ECCO, as κρ from ECCO does not agree closely with observations–specifically, κρ inferred from microstructure measurements. We investigate whether there are observations with more global coverage and well-understood measurement uncertainties that can be assimilated by ECCO to improve its representation of κρ. Argo-derived κρ using a strain-based parameterization of finescale hydrographic structure is one potential source of information. Argo-derived κρ agrees well with microstructure. However, because Argo- derived κρ has both measurement and structural uncertainties, we propose dissolved oxygen concentrations as a candidate for future data assimilation with ECCO. We perform sensitivity analyses with ECCO to test whether oxygen concentrations provide information about κρ. We compare two adjoint sensitivity calculations: one that uses misfits to Argo-derived κρ and the other uses misfits to dissolved oxygen concentrations. We show that adjoint sensitivities of dissolved oxygen concentration misfits to the state estimate's control space typically direct κρ to improve relative to the Argo-derived and microstructure-inferred values. However, assimilation of dissolved oxygen concentrations would likely not serve as a substitute for assimilating accurately measured κρ.