Optimizing Global Ocean Circulation with Transient Ocean Tracers

We present a data assimilative multi-tracer circulation optimization framework to refine the Ocean Circulation Inverse Model (OCIM) by jointly assimilating radiocarbon, CFCs (chlorofluorocarbons), and SF6 (sulfur hexafluoride). The framework uses a newly compiled global radiocarbon data set that combines dissolved inorganic carbon measurements with coral and mollusk shell records, together with CFC and SF6 observations from GLODAPv2. These tracers provide complementary constraints on ocean ventilation from centennial to decadal timescales. In a steady-state OCIM formulation, mixing and advection parameters are optimized by minimizing a global tracer misfit cost function using gradient information and Bayesian inverse techniques. Joint optimization combines tracers with different temporal sensitivities and improves constraints on large-scale transport pathways and diapycnal mixing compared to single-tracer approaches. The optimized steady-state circulation provides an observationally constrained baseline for studies of ocean heat uptake, carbon storage, and marine biogeochemistry, and offers a flexible framework for multi-tracer data assimilation in climate-relevant ocean modeling.