Quantifying variability in the ocean CO2 sink remains problematic due to sparse observations and large spatiotemporal variability in surface-ocean p CO2. To address this challenge, we have developed a global ocean biogeochemistry model called ECCO-Darwin that is constrained by both physical and biogeochemical observations. The model is based on a physical ocean data synthesis provided by the Estimating the Circulation and Climate of the Ocean (ECCO) and on an ecological model provided by the Darwin project. A Green’s Function approach is used to adjust a small number (six) of empirical parameters and initial conditions for the biogeochemical component of the model. We compare ECCO-Darwin global and biome-scale air-sea CO2 fluxes to a suite of interpolation-based products over seasonal to multi-decadal timescales (1995–2017). ECCO-Darwin produces air-sea CO2 fluxes that exhibit broad-scale consistency with the interpolation-based products in many biomes, particularly in the subtropical and equatorial regions. The largest differences between estimates in long-term ocean CO2 uptake occur in subpolar seasonally-stratified biomes, where ECCO-Darwin produces stronger winter uptake. Compared to the Global Carbon Project (GCP) ocean biogeochemistry models, ECCO-Darwin has global CO2 sink (time-mean of -2.52 +/- 0.49 Pg C / yr) and interannual variability that is more consistent with the interpolation-based products. Contrary to interpolation-based products, ECCO-Darwin is less sensitive to sparse and uneven observational sampling and it permits full attribution of the inferred air-sea CO2 flux spatiotemporal variability.
Dr. Dimitris Menemenlis is a research scientist at the Jet Propulsion Laboratory, California Institute of Technology with over 25 years of experience working with ocean circulation models and state estimation technology. He is a developer of the Massachusetts Institute of Technology general circulation model (MITgcm) and a contributor to the Estimating the Circulation and Climate of the Oceans (ECCO) and Carbon Monitoring System Flux (CMS-Flux) projects.