Modeling pathways and processes of deep ocean ventilation

In this talk, I will review the current state of numerical methods for modeling processes and pathways of deep ocean ventilation, focusing on the class of comprehensive ocean and climate models that are most appropriate for direct comparison against observations. I will begin by presenting the pros and cons of free-running forward models, data assimilation models, and conservative state estimation models. I will summarize persistent model biases in the deep ocean as well as challenges related to the sparsity of observational validation data and of deep ocean model output. I will review two approaches for high-resolution modeling of climate change: regional refinement of global models and nested regional modeling. I will contrast three complementary methods for analyzing the pathways through which the deep ocean is ventilated: Eulerian passive tracer transport, Lagrangian particle tracking, and quasi-Lagrangian water mass analysis. I will conclude with an outlook on state-dependent parameterizations, which are expected to enable new research into the deep ocean’s intrinsic variability and climate feedbacks.