the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 14 Jun 2022
Evaluation of Global Teleconnections in CMIP6 Climate Projections using Complex Networks
Abstract. In climatological research, the evaluation of climate models is one of the central research subjects. As an expression of large-scale dynamical processes, global teleconnections play a major role in interannual to decadal climate variability. Their realistic representation is an indispensable requirement for the simulation of climate change, both natural and anthropogenic. Therefore, the evaluation of global teleconnections is of utmost importance when assessing the physical plausibility of climate projections.
We present an application of the graph-theoretical analysis tool δ-MAPS, which constructs complex networks on the basis of spatio-temporal gridded data sets, here sea surface temperature and geopotential height in 500 hPa. Complex networks complement more traditional methods in the analysis of climate variability, like the classification of circulation regimes or empirical orthogonal functions, assuming a new non-linear perspective.
In the first place, δ-MAPS assembles grid cells with highly coherent temporal evolution into so-called domains. In a second step, the teleconnections between the domains are inferred by means of the non-linear distance correlation. We construct two unipartite and a bipartite network for 22 historical CMIP6 climate projections and two century-long coupled reanalyses (CERA-20C and 20CRv3). The networks derived from projection data are compared to those from reanalyses using a similarity criterion borrowed from image processing.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
(1116 KB)
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Supplement
(13390 KB)
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(1116 KB) - Metadata XML
-
Supplement
(13390 KB) - BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2022-433', Anonymous Referee #1, 04 Aug 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-433/egusphere-2022-433-RC1-supplement.pdf
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AC1: 'Reply on RC1', Clementine Dalelane, 22 Aug 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-433/egusphere-2022-433-AC1-supplement.pdf
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AC1: 'Reply on RC1', Clementine Dalelane, 22 Aug 2022
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RC2: 'Comment on egusphere-2022-433', Anonymous Referee #2, 05 Oct 2022
The authors have used the complex network framework to evaluate climate models. By combining several new metrics with the existing d-MAPS methodology, they have widened its applications. The work highlights complex networks as powerful tools to evaluate the realistic representation of the global teleconnections by various models, which the authors use to investigate the biases in CMIP6 models. The authors have also taken into account non-stationarity of the teleconnections have addressed the problem using evolving networks constructed over sliding time windows, showing that this approach could add a new perspective to our understanding of climate change. A very detailed study has been conducted to not only evaluate connectivity in individual SST and Z500 networks but also linkages in the cross-networks between the SST and Z500 domains to take into account the coupled ocean-atmosphere variability.
The manuscript is well-written, the methodology well-explained and the findings are presented in a concise manner with clear evidences. I believe the manuscript is suitable for publication in ESD following only one minor revision. While reading the abstract, it was not clear that the authors have taken into account non-stationarity of the teleconnections, as they only mention that they construct networks for two century-long coupled reanalyses. After reading into much detail, long way into the paper (section 3.2.2), one realises that indeed the authors have already addressed this point. I suggest this to be highlighted by adding a sentence in abstract to avoid confusion, as this is an important point when looking at climate projections in the context of climate change.
Citation: https://doi.org/10.5194/egusphere-2022-433-RC2 -
AC2: 'Reply on RC2', Clementine Dalelane, 09 Oct 2022
We would like to thank reviewer 2 for his comments on our article.
Following his suggestion, we have inserted the following sentence into the abstract: “Potential non-stationarity is taken into account by the use of moving time windows.”
Citation: https://doi.org/10.5194/egusphere-2022-433-AC2
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AC2: 'Reply on RC2', Clementine Dalelane, 09 Oct 2022
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2022-433', Anonymous Referee #1, 04 Aug 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-433/egusphere-2022-433-RC1-supplement.pdf
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AC1: 'Reply on RC1', Clementine Dalelane, 22 Aug 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-433/egusphere-2022-433-AC1-supplement.pdf
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AC1: 'Reply on RC1', Clementine Dalelane, 22 Aug 2022
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RC2: 'Comment on egusphere-2022-433', Anonymous Referee #2, 05 Oct 2022
The authors have used the complex network framework to evaluate climate models. By combining several new metrics with the existing d-MAPS methodology, they have widened its applications. The work highlights complex networks as powerful tools to evaluate the realistic representation of the global teleconnections by various models, which the authors use to investigate the biases in CMIP6 models. The authors have also taken into account non-stationarity of the teleconnections have addressed the problem using evolving networks constructed over sliding time windows, showing that this approach could add a new perspective to our understanding of climate change. A very detailed study has been conducted to not only evaluate connectivity in individual SST and Z500 networks but also linkages in the cross-networks between the SST and Z500 domains to take into account the coupled ocean-atmosphere variability.
The manuscript is well-written, the methodology well-explained and the findings are presented in a concise manner with clear evidences. I believe the manuscript is suitable for publication in ESD following only one minor revision. While reading the abstract, it was not clear that the authors have taken into account non-stationarity of the teleconnections, as they only mention that they construct networks for two century-long coupled reanalyses. After reading into much detail, long way into the paper (section 3.2.2), one realises that indeed the authors have already addressed this point. I suggest this to be highlighted by adding a sentence in abstract to avoid confusion, as this is an important point when looking at climate projections in the context of climate change.
Citation: https://doi.org/10.5194/egusphere-2022-433-RC2 -
AC2: 'Reply on RC2', Clementine Dalelane, 09 Oct 2022
We would like to thank reviewer 2 for his comments on our article.
Following his suggestion, we have inserted the following sentence into the abstract: “Potential non-stationarity is taken into account by the use of moving time windows.”
Citation: https://doi.org/10.5194/egusphere-2022-433-AC2
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AC2: 'Reply on RC2', Clementine Dalelane, 09 Oct 2022
Peer review completion
Journal article(s) based on this preprint
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Clementine Dalelane
Kristina Winderlich
Andreas Walter
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(1116 KB) - Metadata XML
-
Supplement
(13390 KB) - BibTeX
- EndNote
- Final revised paper