A combined globally mapped carbon dioxide (CO2) flux estimate based on the Surface Ocean CO2 Atlas Database (SOCAT) and Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) biogeochemistry floats from 1982 to 2017 (NCEI Accession 0191304)
by Peter Landschützer,1 Seth Bushinsky, 2 Alison R. Gray3
1Max Planck Institute for Meteorology, Hamburg, Germany
2Princeton University, Princeton, NJ and University of Hawai’i – Mānoa, Honolulu, HI, USA
3School of Oceanography, University of Washington, Seattle, WA, USA
The pCO2 fields were created using a 2-step neural network technique. In a first step, the global ocean is divided into 16 biogeochemical provinces using a self-organizing map. In a second step, the non-linear relationship between variables known to drive the surface ocean carbon system and gridded observations from the SOCAT dataset (Bakker et al., 2016) starting in 1982 in various combinations with calculated pCO2 from biogeochemical ARGO floats starting in 2014 from the SOCCOM project (Johnson et al., 2017) is reconstructed using a feed-forward neural network within each province separately. The final product is then produced by projecting these driving variables, i.e., surface temperature, chlorophyll, mixed layer depth, and atmospheric CO2 onto oceanic pCO2 using these non-linear relationships. This results in monthly pCO2 fields at 1°x1° resolution covering the entire globe with the exception of the Arctic Ocean and few marginal seas. The air-sea CO2 flux is then computed using a standard bulk formula. More details regarding the method can be found in Landschützer et al. 2013 and Landschützer et al. 2014.
This product is free to be used. Please cite this data set as:
Landschützer, Peter; Bushinsky, Seth; Gray, Alison R. (2019). A combined globally mapped CO2 flux estimate based on the Surface Ocean CO2 Atlas Database (SOCAT) and Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) biogeochemistry floats from 1982 to 2017 (NCEI Accession 0191304). Version 2.2. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.25921/9hsn-xq82 [2019-07-17].
Please cite the method as:
Bushinsky, S. M., Landschützer, P., Rödenbeck, C., Gray, A. R., Baker, D., Mazloff, M. R., Resplandy, L., Johnson, K. S. and Sarmiento, J. S.: Reassessing Southern Ocean air-sea CO2 flux estimates with the addition of biogeochemical float observations, Global Biogeochemical cycle, in review (to be updated once published)
Bakker, D. C. E. et al.,: An update to the Surface Ocean CO2 Atlas (SOCAT version 2), Earth System Science Data, 6, 69–90, doi:10.5194/essd-6-69-2014, URL: http://www.earth-syst-sci-data.net/6/69/2014/, 2014.
Johnson, K. S., J. N. Plant, L. J. Coletti, and others. 2017. Biogeochemical sensor performance in the SOCCOM profiling float array. J. Geophys. Res. Ocean. 122: 6416–6436. doi:10.1002/2017JC012838
Landschützer, P., Gruber, N., Bakker, D. C. E., Schuster, U.: Recent variability ofthe global ocean carbon sink, Global Biogeochemical Cycles, 28, doi: 10.1002/2014GB004853, 2014.
Landschützer, P., Gruber, N., Bakker, D. C. E., Schuster, U., Nakaoka, S., Payne, M. R., Sasse, T., and Zeng, J.: A neural network-based estimate of the seasonal to inter-annual variability of the Atlantic Ocean carbon sink, Biogeosciences, 10, 7793-7815, doi:10.5194/bg-10-7793-2013, 2013