Articles | Volume 17, issue 2
Development and technical paper
26 Jan 2024
Development and technical paper |  | 26 Jan 2024

Computationally efficient parameter estimation for high-dimensional ocean biogeochemical models

Skyler Kern, Mary E. McGuinn, Katherine M. Smith, Nadia Pinardi, Kyle E. Niemeyer, Nicole S. Lovenduski, and Peter E. Hamlington

Data sets

BFM17 Optimization Data and Plotting Scripts (Version 2) S. Kern et al.

Model code and software

BFM17-56 K. M. Smith et al.

BFM17-Opt: Coupling BFM17+POM1D to DAKOTA for Optimization (Updated Work Flow) S. Kern et al.

skylerjk/BFM17-SA-SinglePert: One-at-a-Time Sensitivity Analysis Code for BFM17 S. Kern et al.

Short summary
Computational models are used to simulate the behavior of marine ecosystems. The models often have unknown parameters that need to be calibrated to accurately represent observational data. Here, we propose a novel approach to simultaneously determine a large set of parameters for a one-dimensional model of a marine ecosystem in the surface ocean at two contrasting sites. By utilizing global and local optimization techniques, we estimate many parameters in a computationally efficient manner.