Natural variability in the surface ocean carbonate ion concentration

Lovenduski, N. S.; Long, M. C.; Lindsay, K.

doi:https://doi.org/10.5194/bg-12-6321-2015

Articles | Volume 12, issue 21

https://doi.org/10.5194/bg-12-6321-2015

© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/bg-12-6321-2015

© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 12, issue 21

Research article

|

05 Nov 2015

Research article |

| 05 Nov 2015

Natural variability in the surface ocean carbonate ion concentration

N. S. Lovenduski, M. C. Long, and K. Lindsay

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Final revised paper (published on 05 Nov 2015)
Preprint (discussion started on 13 Aug 2015)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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RC C5458: 'A highly relevant study with important implications, but lacking some discussion', Anonymous Referee #1, 16 Sep 2015
RC C5460: 'Review of ‘Natural variability in the surface ocean carbonate ion concentration’ by Lovenduski et al.', Anonymous Referee #2, 16 Sep 2015
AC C6390: 'Response to reviewers', Nicole Lovenduski, 09 Oct 2015

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Publish subject to minor revisions (Editor review) (20 Oct 2015) by Christoph Heinze

AR by Nicole Lovenduski on behalf of the Authors (20 Oct 2015) Author's response

ED: Publish as is (23 Oct 2015) by Christoph Heinze

AR by Nicole Lovenduski on behalf of the Authors (23 Oct 2015) Manuscript

Short summary

We investigate variability in surface ocean carbonate chemistry using output from a 1000-year control simulation of an Earth System Model. We find that the detection timescale for trends is strongly influenced by the variability. As the scientific community seeks to detect the anthropogenic influence on ocean carbonate chemistry, these results will aid the interpretation of trends calculated from spatially and temporally sparse observations.