Climate change inspector with intentionally biased bootstrapping (CCIIBB ver. 1.0) &ndash; methodology development

Lee, Taesam

doi:https://doi.org/10.5194/gmd-10-525-2017

Articles | Volume 10, issue 2

https://doi.org/10.5194/gmd-10-525-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/gmd-10-525-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 10, issue 2

Model description paper

|

03 Feb 2017

Model description paper |

| 03 Feb 2017

Climate change inspector with intentionally biased bootstrapping (CCIIBB ver. 1.0) – methodology development

Taesam Lee

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Final revised paper (published on 03 Feb 2017)
Supplement to the final revised paper
Preprint (discussion started on 31 Aug 2016)
Supplement to the preprint

Interactive discussion

Status: closed

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

- Printer-friendly version

- Supplement

SC1: 'Executive Editor Comment on "Simulating climate warming scenarios with intentionally biased bootstrapping and its implications for precipitation"', Astrid Kerkweg, 13 Sep 2016
- AC1: 'Reply to Topical Editor', Taesam Lee, 17 Dec 2016
RC1: 'Review of” Simulating climate warming scenarios with intentionally biased bootstrapping and its implications for precipitation”', Mohammed Ali Ben Alaya, 21 Nov 2016
- AC2: 'Reply to Reviewer 1', Taesam Lee, 17 Dec 2016
RC2: 'Second Review of” Simulating climate warming scenarios with intentionally biased bootstrapping and its implications for precipitation', Dimitri Defrance, 27 Nov 2016
- AC3: 'Reply to Reviewer 2', Taesam Lee, 17 Dec 2016

Peer-review completion

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

AR by Taesam Lee on behalf of the Authors (17 Dec 2016)

ED: Publish as is (05 Jan 2017) by Olivier Marti

AR by Taesam Lee on behalf of the Authors (10 Jan 2017)

Short summary

The paper presents an explicit bias-resampling approach from observations in order to simulate global warming scenarios and to investigate the implications for hydrometeorological variables. The author considers that the suggested approach is easy to implement and to employ in other fields that are influenced by global warming.