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.

Highlights

  • In this paper, we consider the challenges with using observational data products to better inform a data assimilation framework– and, better inform us–about the global distribution of ocean mixing

  • This study evaluated the potential to improve the diapycnal diffusivities in the ECCOv4 ocean parameter and state estimation framework

  • We assessed the fidelity of the inverted field of κρ,ECCO by first comparing the average observed vertical profiles of κρ,ECCO with those inferred from microstructure

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Summary

Introduction

We consider the challenges with using observational data products to better inform a data assimilation framework– and, better inform us–about the global distribution of ocean mixing. Ocean mixing is typically conceptualized in terms of diffusion along and across isopycnal surfaces, and is associated with the transport of isopycnal thickness (or bolus). Ocean models often represent mixing with three parameters: the across-isopycnal mixing parameter (diapycnal diffusivity; Munk and Wunsch (1998)), the along-isopycnal mixing parameter (Redi coefficient; Redi (1982)), and the eddy isopycnal thickness transport parameter (Gent-McWilliams coefficient; Gent and McWilliams (1990)). Diapycnal mixing is an essential component in explaining the observed oceanic stratification

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