the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Large ensemble assessment of the Arctic stratospheric polar vortex
Abstract. The stratospheric polar vortex (SPV) is a phenomenon comprising strong westerly winds during winter in both hemispheres. Especially in the Northern Hemisphere (NH) the SPV is highly variable and is frequently disrupted by sudden stratospheric warmings (SSWs). SPV dynamics are relevant because of both ozone chemistry and its impact on tropospheric dynamics. In this study, we evaluate the capability of climate models to simulate the NH SPV by comparing large ensembles of historical simulations to the ERA5 reanalysis data. For this, we analyze geometric-based diagnostics at 3 pressure levels that describe SPV morphology. Moreover, we assess the ability of the models to simulate SSWs subdivided into SPV split and displacement events. A rank histogram analysis reveals that no model exactly reproduces ERA5 in all diagnostics at all levels. Concerning SPV aspect ratio and centroid latitude, most models are biased to some extent, but the strongest deviations can be found for the kurtosis. Some models underestimate the variability of the SPV area. Assessing the reliability of the ensembles in distinguishing SPV displacement and split events, we find large differences between the model ensembles. In general, SPV displacements are represented better than splits in the simulation ensembles, and high-top models and models with finer vertical resolution perform better. A good performance in representing the geometric-based diagnostics in rank histograms is found to be not necessarily connected to a good performance in simulating displacements and splits. Understanding the biases and improving the representation of SPV dynamics in climate model simulations can help to improve credibility of climate projections, in particular with focus on polar stratospheric dynamics and ozone.
-
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.
-
Preprint
(630 KB)
-
Supplement
(468 KB)
-
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(630 KB) - Metadata XML
-
Supplement
(468 KB) - BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-1831', Anonymous Referee #1, 03 Oct 2023
Review of “Large ensemble assessment of the Arctic stratospheric polar vortex” by A. Kuchar et al.
The authors present a mostly statistical assessment of CMIP model performance in relation to the geometry of the perturbed polar vortex, plus the frequency of split or displacement SSWs. Their main tool of analysis are rank histograms created with models from the Multi-Model Large Ensemble Archive against ERA5 data.
I find the manuscript well written and the structure has a logical flow. I have only minor comments which I hope will help clarify some of the discussion.
Detailed comments:
- Abstract: I would suggest expanding the second last paragraph to clarify what is meant. I did not understand this until after reading the manuscript. Then, I would suggest to remove the last sentence of the Abstract, or at least clarify: It is somewhat misleading as no attempt at improving the representation of SPV dynamics is made, and there is not enough discussion of what could be the cause for the observed biases.
- Introduction/Methods: It is argued that one has to use large ensembles to assess wintertime NH variability - which is fine. However, ERA5 is assumed the truth, even though it only represents one ensemble member (the one we call “reality”). I am not suggesting that’s a problem, but I would welcome a short discussion on why evaluating large ensembles to one single realisation still makes sense.
- It is not clear - neither from Methods nor Code availability - whether the actual code from Seviour et al (2013) has been used to compute the aspect ratio and centroid lat/lon. Please clarify.
- Section 3:
- It would be helpful to provide a sense of how large the biases are. If one is not accustomed to look at rank histograms, it is difficult to judge whether the the shown biases are small or large - that is, whether they are concerning or within acceptable limits. For instance, what does it mean if in Fig. 1c one of the bars peaks around the number 200 but the adjacent bars are below that value? The authors say on line 147 “such strong biases” but I don’t know if I should consider them strong for the work I would like to do with those models.
- I know it’s not the focus of this paper, but some interpretation of results would be great. For instance, models seem to have similar biases at all three levels in centroid latitude, but they have different biases in aspect ratio at different levels. Is there something we can induce or learn from that?
Citation: https://doi.org/10.5194/egusphere-2023-1831-RC1 -
AC1: 'Reply on RC1', Ales Kuchar, 19 Jan 2024
Dear anonymous referee,
we perceive your constructive reviews of our manuscript. We believe that we can answer the points of criticism satisfactorily. Therefore, we will send detailed responses to both reviewers´ comments and are prepared to submit a revised version where all comments are adequately considered.
With regards on behalf of all authors
Ales Kuchar
Citation: https://doi.org/10.5194/egusphere-2023-1831-AC1
-
AC1: 'Reply on RC1', Ales Kuchar, 19 Jan 2024
-
RC2: 'Comment on egusphere-2023-1831', Anonymous Referee #2, 09 Nov 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1831/egusphere-2023-1831-RC2-supplement.pdf
-
AC2: 'Reply on RC2', Ales Kuchar, 19 Jan 2024
Dear anonymous referee,
we perceive your constructive reviews of our manuscript. We believe that we can answer the points of criticism satisfactorily. Therefore, we will send detailed responses to both reviewers´ comments and are prepared to submit a revised version where all comments are adequately considered.
With regards on behalf of all authors
Ales Kuchar
Citation: https://doi.org/10.5194/egusphere-2023-1831-AC2
-
AC2: 'Reply on RC2', Ales Kuchar, 19 Jan 2024
- AC3: 'Comment on egusphere-2023-1831', Ales Kuchar, 26 Jan 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-1831', Anonymous Referee #1, 03 Oct 2023
Review of “Large ensemble assessment of the Arctic stratospheric polar vortex” by A. Kuchar et al.
The authors present a mostly statistical assessment of CMIP model performance in relation to the geometry of the perturbed polar vortex, plus the frequency of split or displacement SSWs. Their main tool of analysis are rank histograms created with models from the Multi-Model Large Ensemble Archive against ERA5 data.
I find the manuscript well written and the structure has a logical flow. I have only minor comments which I hope will help clarify some of the discussion.
Detailed comments:
- Abstract: I would suggest expanding the second last paragraph to clarify what is meant. I did not understand this until after reading the manuscript. Then, I would suggest to remove the last sentence of the Abstract, or at least clarify: It is somewhat misleading as no attempt at improving the representation of SPV dynamics is made, and there is not enough discussion of what could be the cause for the observed biases.
- Introduction/Methods: It is argued that one has to use large ensembles to assess wintertime NH variability - which is fine. However, ERA5 is assumed the truth, even though it only represents one ensemble member (the one we call “reality”). I am not suggesting that’s a problem, but I would welcome a short discussion on why evaluating large ensembles to one single realisation still makes sense.
- It is not clear - neither from Methods nor Code availability - whether the actual code from Seviour et al (2013) has been used to compute the aspect ratio and centroid lat/lon. Please clarify.
- Section 3:
- It would be helpful to provide a sense of how large the biases are. If one is not accustomed to look at rank histograms, it is difficult to judge whether the the shown biases are small or large - that is, whether they are concerning or within acceptable limits. For instance, what does it mean if in Fig. 1c one of the bars peaks around the number 200 but the adjacent bars are below that value? The authors say on line 147 “such strong biases” but I don’t know if I should consider them strong for the work I would like to do with those models.
- I know it’s not the focus of this paper, but some interpretation of results would be great. For instance, models seem to have similar biases at all three levels in centroid latitude, but they have different biases in aspect ratio at different levels. Is there something we can induce or learn from that?
Citation: https://doi.org/10.5194/egusphere-2023-1831-RC1 -
AC1: 'Reply on RC1', Ales Kuchar, 19 Jan 2024
Dear anonymous referee,
we perceive your constructive reviews of our manuscript. We believe that we can answer the points of criticism satisfactorily. Therefore, we will send detailed responses to both reviewers´ comments and are prepared to submit a revised version where all comments are adequately considered.
With regards on behalf of all authors
Ales Kuchar
Citation: https://doi.org/10.5194/egusphere-2023-1831-AC1
-
AC1: 'Reply on RC1', Ales Kuchar, 19 Jan 2024
-
RC2: 'Comment on egusphere-2023-1831', Anonymous Referee #2, 09 Nov 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1831/egusphere-2023-1831-RC2-supplement.pdf
-
AC2: 'Reply on RC2', Ales Kuchar, 19 Jan 2024
Dear anonymous referee,
we perceive your constructive reviews of our manuscript. We believe that we can answer the points of criticism satisfactorily. Therefore, we will send detailed responses to both reviewers´ comments and are prepared to submit a revised version where all comments are adequately considered.
With regards on behalf of all authors
Ales Kuchar
Citation: https://doi.org/10.5194/egusphere-2023-1831-AC2
-
AC2: 'Reply on RC2', Ales Kuchar, 19 Jan 2024
- AC3: 'Comment on egusphere-2023-1831', Ales Kuchar, 26 Jan 2024
Peer review completion
Journal article(s) based on this preprint
Viewed
HTML | XML | Total | Supplement | BibTeX | EndNote | |
---|---|---|---|---|---|---|
411 | 152 | 32 | 595 | 57 | 23 | 20 |
- HTML: 411
- PDF: 152
- XML: 32
- Total: 595
- Supplement: 57
- BibTeX: 23
- EndNote: 20
Viewed (geographical distribution)
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1
Maurice Öhlert
Roland Eichinger
Christoph Jacobi
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(630 KB) - Metadata XML
-
Supplement
(468 KB) - BibTeX
- EndNote
- Final revised paper