Data assimilation using an ensemble of models:  a hierarchical approach

Rayner, Peter

doi:https://doi.org/10.5194/acp-20-3725-2020

Articles | Volume 20, issue 6

https://doi.org/10.5194/acp-20-3725-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue:

Data assimilation in carbon/biogeochemical cycles: consistent...

https://doi.org/10.5194/acp-20-3725-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 20, issue 6

Research article

|

27 Mar 2020

Research article |

| 27 Mar 2020

Data assimilation using an ensemble of models: a hierarchical approach

Peter Rayner

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Final revised paper (published on 27 Mar 2020)
Preprint (discussion started on 03 Feb 2017)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Initial comments; need clarification in order to proceed.', Amy Braverman, 11 Mar 2017
RC2: 'Overall a worthwhile study but I have reservations on several aspects', Anonymous Referee #2, 26 Apr 2017
AC1: 'Overall response to referees' comments', Peter Rayner, 04 Jul 2017

Peer-review completion

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

AR by Peter Rayner on behalf of the Authors (11 Oct 2018) Author's response Manuscript

ED: Referee Nomination & Report Request started (23 Nov 2018) by Christoph Gerbig

RR by Amy Braverman (25 Dec 2018)

RR by Anonymous Referee #3 (02 Jan 2019)

ED: Reconsider after major revisions (06 Jan 2019) by Christoph Gerbig

AR by Peter Rayner on behalf of the Authors (11 Jul 2019) Author's response

ED: Referee Nomination & Report Request started (05 Aug 2019) by Christoph Gerbig

RR by Anonymous Referee #3 (14 Sep 2019)

RR by Amy Braverman (25 Sep 2019)

ED: Publish subject to technical corrections (25 Sep 2019) by Christoph Gerbig

AR by Peter Rayner on behalf of the Authors (22 Nov 2019) Author's response Manuscript

Short summary

This work extends previous calculations of carbon dioxide sources and sinks to take account of the varying quality of atmospheric models. It uses an extended version of Bayesian statistics which includes the model as one of the unknowns. I performed the work as an example of including the model in the description of the uncertainty.