Reduced Order Biogeochemical Flux Model For Use In High-Resolution Multi-Scale Biophysical Simulations
Katherine Smith, University of Cambridge, Department of Applied Mathematics and Theoretical Physics, Cambridge, United Kingdom, Peter Hamlington, Univ of Colorado, Boulder, CO, United States, Skyler Kern, University of Alaska Anchorage, Mechanical Engineering, Anchorage, United States, Nadia Pinardi, University of Bologna, Physics and Astronomy, Bologna, Italy, Marco Zavatarelli, University of Bologna, Bologna, Italy, Kyle Niemeyer, Oregon State University, Department of Mechanical, Industrial, and Manufacturing Engineering, Corvallis, OR, United States and Emily Klee, Oregon State University, Department of Mechanical, Industrial, and Manufacturing Engineering, Corvallis, United States
Abstract:
Biogeochemical tracers and their interactions with upper ocean physical processes such as submesoscale circulations and small-scale turbulence are critical for understanding the role of the ocean in the global carbon cycle. These interactions can cause small-scale spatial and temporal heterogeneity in tracer distributions which can, in turn, greatly affect carbon exchange rates between the atmosphere and interior ocean. For this reason, it is important to take into account small-scale biophysical interactions when modeling the global carbon cycle. However, explicitly resolving these interactions in an Earth system model (ESM) is currently infeasible due to the enormous associated computational cost. As a result, understanding and subsequently parametrizing how these small-scale heterogeneous distributions develop and how they relate to larger resolved scales is critical for obtaining improved predictions of carbon exchange rates in ESMs.
In order to address this need, we have developed the reduced-order, 17 state variable Biogeochemical Flux Model (BFM17), which has been derived from the full BFM for the purpose of coupling with fully three-dimensional, non-hydrostatic large eddy simulation (LES) models. BFM17 is complex enough to capture behavior of open ocean biogeochemical systems, but reduced enough to integrate within high resolution LES simulations without unreasonable growth in computation time and data storage. When coupled with the 1D Princeton Ocean Model, BFM17 shows good agreement between predicted monthly-averaged results and Bermuda testbed area field data (including the Bermuda-Atlantic Time Series and Bermuda Testbed Mooring). In this talk, we discuss the use of BFM17 within a LES model of submesoscale circulations and outline how this will further our understanding of turbulent biophysical interactions in the upper ocean.
