The ECCO-Darwin Data-Assimilative Global Ocean Biogeochemistry Model: Estimates of Seasonal to Multidecadal Surface Ocean pCO(2) and Air-Sea CO2 Flux
|Author(s)||Carroll D.1, 2, Menemenlis D.2, Adkins J. F.3, Bowman K. W.2, Brix H.4, 5, Dutkiewicz S.6, 7, Fenty I.2, Gierach M. M.2, Hill C.6, Jahn O.6, Landschutzer P.8, Lauderdale J. M.6, Liu J.2, Manizza M.9, Naviaux J. D.3, Roedenbeck C.10, Schimel D. S.2, Van Der Stocken T.2, Zhang H.2|
|Affiliation(s)||1 : San Jose State Univ, Moss Landing Marine Labs, Moss Landing, CA 95039 USA.
2 : CALTECH, Jet Prop Lab, Pasadena, CA 91125 USA.
3 : CALTECH, Div Geol & Planetary Sci, Pasadena, CA 91125 USA.
4 : Helmholtz Zentrum Geesthacht, Inst Coastal Res, Geesthacht, Germany.
5 : Univ Calif Los Angeles, Joint Inst Reg Earth Syst Sci & Engn, Los Angeles, CA USA.
6 : MIT, Dept Earth Atmospher & Planetary Sci, Cambridge, MA USA.
7 : MIT, Ctr Global Change Sci, 77 Massachusetts Ave, Cambridge, MA 02139 USA.
8 : Max Planck Inst Meteorol, Hamburg, Germany.
9 : Univ Calif San Diego, Scripps Inst Oceanog, Geosci Res Div, La Jolla, CA 92093 USA.
10 : Max Planck Inst Biogeochem, Jena, Germany.
|Source||Journal Of Advances In Modeling Earth Systems (Amer Geophysical Union), 2020-10 , Vol. 12 , N. 10 , P. e2019MS001888 (28p.)|
|WOS© Times Cited||9|
|Keyword(s)||ocean modeling, biogeochemistry, ocean carbon cycle, data assimilation, air‐, sea CO2 flux, ecosystem model|
Quantifying variability in the ocean carbon sink remains problematic due to sparse observations and spatiotemporal variability in surface ocean pCO(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 pCO(2) 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.