Editors’ Highlights are summaries of recent papers by AGU’s journal editors.
Source: Journal of Advances in Modeling Earth Systems
Geochemical tracers can provide important information about physical and biogeochemical processes in the ocean. For example, radiocarbon is a tracer that indicates the time elapsed since waters in the ocean interior were last at the surface. Simulating radiocarbon in an ocean model, therefore, can provide important constraints on the fidelity of a model’s representation of ventilation, which is a critical property relevant to maintaining the ocean’s carbon inventory or regulating distributions of dissolved oxygen.
However, circulation in the deep ocean is slow and it takes a long time for tracers simulated in ocean circulation models to develop distributions that are in balance with the flow. These long “adjustment timescales” present a significant methodological limitation, hampering our ability to generate equilibrated model solutions, which is a requirement for using tracers to effectively validate the models, calibrate uncertain parameters, or provide suitable initial conditions for Earth system model integrations.
Khatiwala [2023] presents a numerical technique for confronting this challenge. The method is based on Anderson Acceleration (AA) and is capable of accelerating tracer spin up by at least a factor of ten. In addition, a significant advantage of the new method is that it is easy to implement. In contrast to previously deployed techniques based on Newton-Krylov methods, the AA approach does not require the creation of custom, model-specific implementations. This improved flexibility has the potential to facilitate broader application. The new technique has thus far been implemented on relatively “simple” geochemical tracers. Additional work is needed to enable its application to more sophisticated suites of tracers, such as those represented by complex biogeochemical models.
Citation: Khatiwala, S. (2023). Fast spin-up of geochemical tracers in ocean circulation and climate models. Journal of Advances in Modeling Earth Systems, 15, e2022MS003447. https://doi.org/10.1029/2022MS003447
—Matthew Long, Associate Editor, JAMES