Articles | Volume 12, issue 3
Earth Syst. Sci. Data, 12, 1725–1743, 2020
Earth Syst. Sci. Data, 12, 1725–1743, 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.


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Daniel Broullón on behalf of the Authors (18 Jun 2020)  Author's response
ED: Publish as is (02 Jul 2020) by Jens Klump
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.