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The ECCO‐Darwin Data‐Assimilative Global Ocean Biogeochemistry Model: Estimates of Seasonal to Multidecadal Surface Ocean pCO₂ and Air‐Sea CO₂ Flux

Carroll, D. and Menemenlis, D. and Adkins, J. F. and Bowman, K. W. and Brix, H. and Dutkiewicz, S. and Fenty, I. and Gierach, M. M. and Hill, C. and Jahn, O. and Landschützer, P. and Lauderdale, J. M. and Liu, J. and Manizza, M. and Naviaux, J. D. and Rödenbeck, C. and Schimel, D. S. and Van der Stocken, T. and Zhang, H. (2020) The ECCO‐Darwin Data‐Assimilative Global Ocean Biogeochemistry Model: Estimates of Seasonal to Multidecadal Surface Ocean pCO₂ and Air‐Sea CO₂ Flux. Journal of Advances in Modeling Earth Systems, 12 (10). Art. No. e2019MS001888. ISSN 1942-2466. https://resolver.caltech.edu/CaltechAUTHORS:20200818-132613563

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Abstract

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 multidecadal 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.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1029/2019ms001888DOIArticle
ORCID:
AuthorORCID
Carroll, D.0000-0003-1686-5255
Menemenlis, D.0000-0001-9940-8409
Adkins, J. F.0000-0002-3174-5190
Bowman, K. W.0000-0002-8659-1117
Brix, H.0000-0003-4229-6164
Dutkiewicz, S.0000-0002-0380-9679
Fenty, I.0000-0001-6662-6346
Gierach, M. M.0000-0002-8161-4121
Hill, C.0000-0003-3417-9056
Jahn, O.0000-0002-0130-5186
Landschützer, P.0000-0002-7398-3293
Lauderdale, J. M.0000-0002-2993-7484
Liu, J.0000-0002-7184-6594
Manizza, M.0000-0001-6265-8367
Naviaux, J. D.0000-0002-0681-3163
Rödenbeck, C.0000-0001-6011-6249
Schimel, D. S.0000-0003-3473-8065
Van der Stocken, T.0000-0002-1820-9123
Additional Information:© 2020 The Author(s). This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Accepted manuscript online: 26 July 2020; Manuscript accepted: 23 July 2020; Manuscript revised: 15 July 2020; Manuscript received: 03 September 2019. Research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA. D. C., D. M., and H. Z. were supported by NASA Biological Diversity, Physical Oceanography, and Modeling, Analysis, and Prediction Programs. M. M. G. and D. S. S. were supported by NASA ROSES‐2017 Grant/Cooperative Agreement NNX15AG92G. S. D. was supported by NASA‐IDS Grant 80NSSC17K0561. J. M. L. was supported by U.S. National Science Foundation grant OCE‐1259388. High‐end computing resources were provided by the NASA Advanced Supercomputing (NAS) Division of the Ames Research Center. The authors acknowledge ideas and advice from the participants in the Satellites to the Seafloor workshop organized by the W. M. Keck Institute for Space Studies. Data Availability Statement: ECCO‐Darwin model fields are available at the website (https://data.nas.nasa.gov/ecco). Platform‐independent instructions for running ECCO‐Darwin simulations are available at the website (https://zenodo.org/badge/doi/10.5281/zenodo.3829965.svg). Copyright 2020 California Institute of Technology. U.S. Government sponsorship acknowledged. All rights reserved.
Funders:
Funding AgencyGrant Number
NASA/JPL/CaltechUNSPECIFIED
NASANNX15AG92G
NASA80NSSC17K0561
NSFOCE-1259388
Subject Keywords:ocean modeling; biogeochemistry; ocean carbon cycle; data assimilation; air‐sea CO2 flux; ecosystem model
Issue or Number:10
Record Number:CaltechAUTHORS:20200818-132613563
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20200818-132613563
Official Citation:Carroll, D., Menemenlis, D., Adkins, J. F., Bowman, K. W., Brix, H., Dutkiewicz, S., et al. (2020). The ECCO‐Darwin data‐assimilative global ocean biogeochemistry model: Estimates of seasonal to multidecadal surface ocean pCO2 and air‐sea CO2 flux. Journal of Advances in Modeling Earth Systems, 12, e2019MS001888. https://doi.org/10.1029/2019MS001888
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:105004
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:18 Aug 2020 21:24
Last Modified:21 Oct 2020 16:47

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