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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Jan 2021	42	17	0	59
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Cumulative views and downloads (calculated since 03 Feb 2017)

Month	HTML	PDF	XML	Total
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Mar 2017	39	8	14	61
Apr 2017	56	8	12	76
May 2017	42	3	9	54
Jun 2017	39	6	6	51
Jul 2017	19	6	0	25
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Mar 2020	167	44	4	215
Apr 2020	116	36	0	152
May 2020	39	12	4	55
Jun 2020	21	16	0	37
Jul 2020	33	36	5	74
Aug 2020	29	31	3	63
Sep 2020	24	9	1	34
Oct 2020	13	7	1	21
Nov 2020	12	9	0	21
Dec 2020	30	18	0	48
Jan 2021	42	17	0	59
Feb 2021	40	8	1	49
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Oct 2023	46	6	1	53
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Dec 2023	25	7	3	35
Jan 2024	33	24	0	57
Feb 2024	15	18	0	33
Mar 2024	18	12	3	33
Apr 2024	9	10	6	25
May 2024	25	6	5	36
Jun 2024	65	11	4	80
Jul 2024	149	6	2	157
Aug 2024	35	6	5	46
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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.

Data assimilation using an ensemble of models: a hierarchical approach

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4 citations as recorded by crossref.

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