Correlations between climate network and relief data

Peron, T. K. D.; Comin, C. H.; Amancio, D. R.; da F. Costa, L.; Rodrigues, F. A.; Kurths, J.

doi:https://doi.org/10.5194/npg-21-1127-2014

Articles | Volume 21, issue 6

https://doi.org/10.5194/npg-21-1127-2014

© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue:

Complex network approaches to analyzing and modeling nonlinear...

https://doi.org/10.5194/npg-21-1127-2014

© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 21, issue 6

Research article

| Highlight paper

|

27 Nov 2014

Research article | Highlight paper |

| 27 Nov 2014

Correlations between climate network and relief data

T. K. D. Peron, C. H. Comin, D. R. Amancio, L. da F. Costa, F. A. Rodrigues, and J. Kurths

Download

Final revised paper (published on 27 Nov 2014)
Preprint (discussion started on 24 Apr 2014)

Interactive discussion

Status: closed

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

- Printer-friendly version

- Supplement

RC C112: 'Report', Anonymous Referee #1, 07 May 2014
- AC C370: 'Response to Anonymous Referee #1', Thomas Peron, 08 Aug 2014
RC C143: 'Referee comment', Anonymous Referee #2, 17 May 2014
- AC C371: 'Response to Anonymous Referee #2', Thomas Peron, 08 Aug 2014

Peer-review completion

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

AR by Thomas Peron on behalf of the Authors (05 Sep 2014) Author's response Manuscript

ED: Publish as is (22 Sep 2014) by Michael Small

AR by Thomas Peron on behalf of the Authors (25 Sep 2014)

Short summary

In the past few years, complex networks have been extensively applied to climate sciences, yielding the new field of climate networks. Here, we generalize climate network analysis by investigating the influence of altitudes in network topology. More precisely, we verified that nodes group into different communities corresponding to geographical areas with similar relief properties. This new approach may contribute to obtaining more complete climate network models.