Articles | Volume 20, issue 6
Atmos. Chem. Phys., 20, 3725–3737, 2020
https://doi.org/10.5194/acp-20-3725-2020

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

Atmos. Chem. Phys., 20, 3725–3737, 2020
https://doi.org/10.5194/acp-20-3725-2020

Research article 27 Mar 2020

Research article | 27 Mar 2020

Data assimilation using an ensemble of models: a hierarchical approach

Peter Rayner

Download

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 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
Download
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.
Altmetrics
Final-revised paper
Preprint