Synthetic weather diaries: concept and application to Swiss weather in 1816

Brönnimann, Stefan

doi:https://doi.org/10.5194/cp-16-1937-2020

Articles | Volume 16, issue 5

https://doi.org/10.5194/cp-16-1937-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

International methods and comparisons in climate reconstruction...

https://doi.org/10.5194/cp-16-1937-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 16, issue 5

Research article

|

21 Oct 2020

Research article |

| 21 Oct 2020

Synthetic weather diaries: concept and application to Swiss weather in 1816

Stefan Brönnimann

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Final revised paper (published on 21 Oct 2020)
Supplement to the final revised paper
Preprint (discussion started on 09 Jun 2020)
Supplement to the preprint

Interactive discussion

Status: closed

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

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RC1: 'Synthetic Weather Diaries: Concept and Application to Swiss Weather in 1816', Anonymous Referee #1, 07 Jul 2020
- AC1: 'Reply', Stefan Bronnimann, 05 Aug 2020
RC2: 'Synthetic Weather Diaries: Concept and Application to Swiss Weather in 1816', Anonymous Referee #2, 29 Jul 2020
- AC2: 'Reply', Stefan Bronnimann, 05 Aug 2020

Peer-review completion

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

ED: Publish subject to minor revisions (review by editor) (19 Aug 2020) by Sam White

AR by Stefan Bronnimann on behalf of the Authors (21 Aug 2020) Author's response Manuscript

ED: Publish as is (31 Aug 2020) by Sam White

Short summary

Scientists often reconstruct climate from proxy data such as tree rings or historical documents. Here, I do the reverse and produce a weather diary from historical numerical weather data. Such "synthetic weather diaries" may be useful for historians, e.g. to compare with other sources or to study the weather experienced during a journey or a military operation. They could also help train machine-learning approaches, which could then be used to reconstruct weather from historical diaries.