Detecting changes in forced climate attractors with Wasserstein distance

Robin, Yoann; Yiou, Pascal; Naveau, Philippe

doi:https://doi.org/10.5194/npg-24-393-2017

Articles | Volume 24, issue 3

https://doi.org/10.5194/npg-24-393-2017

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

https://doi.org/10.5194/npg-24-393-2017

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

Articles | Volume 24, issue 3

Research article

|

31 Jul 2017

Research article |

| 31 Jul 2017

Detecting changes in forced climate attractors with Wasserstein distance

Yoann Robin, Pascal Yiou, and Philippe Naveau

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Final revised paper (published on 31 Jul 2017)
Preprint (discussion started on 20 Feb 2017)

Interactive discussion

Status: closed

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

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RC1: 'Review of the manuscript doi:10.5194/npg-2017-5, 2017 entitled: “Detecting Changes in Forced Climate Attractors with Wasserstein Distance” by Yoann Robin, Pascal Yiou, and Philippe Naveau.', Anonymous Referee #1, 08 Mar 2017
- AC1: 'Response Anonymous Referee 1', Yoann Robin, 08 Jun 2017
RC2: 'Review of the paper', Valerio Lucarini, 06 May 2017
- AC2: 'Response V. Lucarini', Yoann Robin, 08 Jun 2017

Peer-review completion

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

AR by Yoann Robin on behalf of the Authors (08 Jun 2017) Author's response Manuscript

ED: Publish as is (12 Jun 2017) by Vicente Perez-Munuzuri

AR by Yoann Robin on behalf of the Authors (26 Jun 2017)

Short summary

If climate is viewed as a chaotic dynamical system, its trajectories yield on an object called an attractor. Being perturbed by an external forcing, this attractor could be modified. With Wasserstein distance, we estimate on a derived Lorenz model the impact of a forcing similar to climate change. Our approach appears to work with small data sizes. We have obtained a methodology quantifying the deformation of well-known attractors, coherent with the size of data available.