The ECCO‐Darwin Data‐Assimilative Global Ocean Biogeochemistry Model: Estimates of Seasonal to Multidecadal Surface Ocean p CO 2 and Air‐Sea CO 2 Flux

• Published in: Journal of advances in modeling earth systems 2020-10, Vol.12 (10)
• Main Authors: 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.
• Format: Article
• Language: English
• Subjects: Anthropogenic factors; Biogeochemistry; Carbon cycle; Carbon dioxide; Carbon dioxide flux; Carbon sinks; Climate; Climate change; Consortia; Ecosystem models; Estimates; General circulation models; Green's function; Interannual variability; Interpolation; Marine ecosystems; Ocean circulation; Oceans; Physics; Salinity; Time series; Trends; Uptake; Variability; Water circulation
• ISSN: 1942-2466; 1942-2466
• DOI: 10.1029/2019MS001888

Quantifying variability in the ocean carbon sink remains problematic due to sparse observations and spatiotemporal variability in surface ocean p CO 2 . 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 multidecadal timescales (1995–2017), ECCO‐Darwin exhibits broad‐scale consistency with observed surface ocean p CO 2 and air‐sea CO 2 flux reconstructions in most biomes, particularly in the subtropical and equatorial regions. The largest differences between CO 2 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 CO 2 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. 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, also known as, data assimilation. While the physical oceanographic community has made great progress in developing data assimilation systems,