Carroll, D., Menemenlis, D., Adkins, J.F., Bowman, K.W., Brix, H., Dutkiewicz, S., Fenty, I., Gierach, M.M., Hill, C., Jahn, O., Landschützer, P., Lauderdale, J.M., Liu, J., Manizza, M., Naviaux, J.D.,Rödenbeck, C., Schimel, D.S., Van der Stocken, T., & Zhang, H. (2020): The ECCO‐Darwin Data‐assimilative Global Ocean Biogeochemistry Model: Estimates of Seasonal to Multi‐decadal Surface Ocean pCO2 and Air‐sea CO2 Flux. Journal of Advances in Modeling Earth Systems, 12, e2019MS001888, doi:10.1029/2019MS001888
Quantifying variability in the ocean carbon sink remains problematic due to sparse observations and spatiotemporal variability in surface ocean pCO2. To address this challenge, we have updated and improved ECCO‐Darwin, a global ocean biogeochemistry model that assimilates both physical and biogeochemical observations. The model consists of an adjoint‐based ocean circulation estimate from the Estimating the Circulation and Climate of the Ocean (ECCO) consortium and an ecosystem model developed by the Massachusetts Institute of Technology Darwin Project. In addition to the data‐constrained ECCO physics, a Green’s Function approach is used to optimize the biogeochemistry by adjusting initial conditions and six biogeochemical parameters. Over seasonal to multi‐decadal timescales (1995–2017), ECCO‐Darwin exhibits broad‐scale consistency with observed surface ocean pCO2 and air‐sea CO2 flux reconstructions in most biomes, particularly in the subtropical and equatorial regions. The largest differences between CO2 uptake occur in subpolar, seasonally‐stratified biomes, where ECCO‐Darwin results in stronger winter uptake. Compared to the Global Carbon Project OBMs, ECCO‐Darwin has a time‐mean, global‐ocean CO2 sink (2.47 ± 0.50 Pg C year‐1) and interannual variability that are more consistent with interpolation‐based products. Compared to interpolation‐based methods, ECCO‐Darwin is less sensitive to sparse and irregularly‐sampled observations. Thus, ECCO‐Darwin provides a basis for identifying and predicting the consequences of natural and anthropogenic perturbations to the ocean carbon cycle, as well as the climate‐related sensitivity of marine ecosystems. Our study further highlights the importance of physically‐consistent, property‐conserving reconstructions, as are provided by ECCO, for ocean biogeochemistry studies.
Plain Language Summary:
Data‐driven estimates of how much carbon dioxide the ocean is absorbing (the so‐called „ocean carbon sink“) have improved substantially in recent years. However, computational ocean models that include biogeochemistry continue to play a critical role as they allow us to isolate and understand the individual processes that control ocean carbon sequestration. The ideal scenario is a combination of the above two methods, where data are ingested and then used to improve a model’s fit to the observed ocean, aka, data assimilation. While the physical oceanographic community has made great progress in developing data assimilation systems, for example, the Estimating the Circulation and Climate of the Ocean (ECCO) consortium, the biogeochemical community has generally lagged behind. The ECCO‐Darwin model presented in this paper represents an important technological step forward as it is the first global ocean biogeochemistry model that (1) ingests both physical and biogeochemical observations into the model in a realistic manner and (2) considers how the nature of the ocean carbon sink has changed over multiple decades. As the ECCO ocean circulation estimates become more accurate and lengthen in time, ECCO‐Darwin will become an ever more accurate and useful tool for climate‐related ocean carbon cycle and mitigation studies.