Articles | Volume 12, issue 3
Earth Syst. Sci. Data, 12, 1725–1743, 2020
https://doi.org/10.5194/essd-12-1725-2020
Earth Syst. Sci. Data, 12, 1725–1743, 2020
https://doi.org/10.5194/essd-12-1725-2020

Data description paper 05 Aug 2020

Data description paper | 05 Aug 2020

A global monthly climatology of oceanic total dissolved inorganic carbon: a neural network approach

Daniel Broullón et al.

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Cited articles

Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015. 
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Bates, N., Astor, Y., Church, M., Currie, K., Dore, J., Gonaález-Dávila, M., Lorenzoni, L., Muller-Karger, F., Olafsson, J., and Santa-Casiano, M.: A Time-Series View of Changing Ocean Chemistry Due to Ocean Uptake of Anthropogenic CO2 and Ocean Acidification, Oceanography, 27, 126–141, https://doi.org/10.5670/oceanog.2014.16, 2014. 
Bauer, J. E., Cai, W. J., Raymond, P. A., Bianchi, T. S., Hopkinson, C. S., and Regnier, P. A. G.: The changing carbon cycle of the coastal ocean, Nature, 504, 61–70, https://doi.org/10.1038/nature12857, 2013. 
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Short summary
This work offers a vision of the global ocean regarding the carbon cycle and the implications of ocean acidification through a climatology of a changing variable in the context of climate change: total dissolved inorganic carbon. The climatology was designed through artificial intelligence techniques to represent the mean state of the present ocean. It is very useful to introduce in models to evaluate the state of the ocean from different perspectives.