Although application of inverse methods and automatic optimization methods to global ocean biogeochemistry models has been quite successful, the steady-state approach fails to capture the essential time-varying seasonality of the ocean. The main limitation of extending automatic optimization to seasonally varying models is the formidable computational costs. In this research, two young PIs from the University of California - Irvine will adapt a state-of-the-art Newton-Krylov method to greatly reduce the computational time needed to spin-up global biogeochemistry models. The resulting fast solver will make it possible to explore parameter space more efficiently and make it feasible to tune uncertain model parameters using automatic optimization methods. They will apply the solver to a hierarchy of global ocean-biogeochemistry models with an increasing level of complexity. In the simplest model, biological uptake will be parameterized diagnostically by restoring surface nutrients to their observed value. In models of intermediate complexity, biological uptake will have a prognostic representation with an explicit treatment of light, temperature, phosphate and iron limitations. The most complex model will be a full ecosystem model that includes representations of the major functional groups involved in ocean biogeochemical cycling. The anticipated outcomes of this research include the fast solver for obtaining the seasonally varying periodic steady states of ocean biogeochemistry models that can be used by the community to greatly reduce the computational costs associated with spinning up global biogeochemistry models for different climate states or with altered parameter values. In addition, their efforts will yield optimized biogeochemistry model parameters that are consistent with climatological and seasonally varying chemical tracer data.
In terms of broader impacts, a graduate student and a postdoctoral researcher will obtain training in ocean biogeochemistry and advanced numerical and optimization methods. Undergraduate students will also be exposed to scientific research as part of the NSF-sponsored REU program at UCI. Both PIs will continue participating in outreach programs to provide training in the Earth sciences to elementary teachers from three heavily minority, high-need Southern California school districts (Santa Ana, Costa Mesa, and Compton). The new online biogeochemistry models compatible with the NCAR CCSM ocean-grid, the fast Newton-Krylov solver and parameter optimization routines will be made publicly available to the community.
