A novel method for objective identification of 3-D potential vorticity anomalies

Fischer, Christoph; Fink, Andreas H.; Schömer, Elmar; van der Linden, Roderick; Maier-Gerber, Michael; Rautenhaus, Marc; Riemer, Michael

doi:https://doi.org/10.5194/gmd-15-4447-2022

Articles | Volume 15, issue 11

https://doi.org/10.5194/gmd-15-4447-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-15-4447-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 15, issue 11

Methods for assessment of models

|

09 Jun 2022

Methods for assessment of models |

| 09 Jun 2022

A novel method for objective identification of 3-D potential vorticity anomalies

Christoph Fischer, Andreas H. Fink, Elmar Schömer, Roderick van der Linden, Michael Maier-Gerber, Marc Rautenhaus, and Michael Riemer

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Final revised paper (published on 09 Jun 2022)
Preprint (discussion started on 04 Jan 2022)

Interactive discussion

Status: closed

RC1: 'Comment on gmd-2021-424', Anonymous Referee #1, 01 Feb 2022

See PDF supplement for review.

Citation: https://doi.org/10.5194/gmd-2021-424-RC1
RC2: 'Comment on gmd-2021-424', Anonymous Referee #2, 10 Mar 2022

Review of “A novel method for objective identification of 3-D potential vorticity anomalies”

GENERAL COMMENTS:

An automated technique to objectively identify potential vorticity (PV) anomalies in isentropic levels is presented, with the novelty that it can be extended to 3D. The development and testing are focused on the detection of dynamical tropopause anomalies, which are related to extreme weather events. Description vectors are computed to simplify further analysis. The advantages of the 3D analysis are highlighted.

The method is sound and useful. The 3D extensión is original and valuable.

The manuscript is well written and the effort to keep it easy to understand is noteworthy. Still, I have doubts about several things.

SPECIFIC COMMENTS:

- The word anomaly can be misleading. In general, it is easy to understand what it means by the context, but not as much in the abstract.

- Abstract: “The generated feature descriptions are well suited ... for generation of climatologies of feature characteristics”. Lines 534 to 536: “Further research is required on certain aspects of this identification ... for climatologies, automated tracking techniques are required. Ideas for further work ...” I do not think the 3D algorithm is that well suited for climatologies in its current version, feature descriptions or not.

- Looks like the development and testing of this method was restricted to the detection of anomalies in the dynamical tropopause. However, both the title and the abstract suggest a more general use. This is not discussed anywhere. There is just a mention of the problem in the equator due to the projection (lines 165-166), but this doesn’t affect the dynamical tropopause, which is not defined at the lower latitudes. Can the method be used in other heights (i.e. middle troposphere/stratosphere) as it is?

- Line 184: “âs(x_c,y_c) itself can be calculated from the latitude and longitude positions of the pole and its surrounding pixels” This should be explained.

- I have had a lot of problems with “visualizing” the 3D method. The representation of the PVA in Figure 11 b and c (for example) is confusing: it looks like the 3D surface is such that it encompasses a volume (and then Γ₁ and Γ₂ should be surfaces, too). But this is not possible if the represented surface is 2 PVU: how is the surface closed to make it look like the PVA represented in Figure 11c?. It took me some time to realize that the computed surface doesn’t have a thickness, and thus Γ₁ and Γ₂ are lines. Even in the images in the left column of Figure 12, where the structure of the surface is better represented, it looks like the anomaly has a thickness, a volume. In summary: explain what you do to make the PVA look like that (and why) or use a more realistic surface.

- In the left column of Figure 12, it is difficult to see the yellow region as an anomaly, and the right column does not help much. It would be useful to see two cross-sections going through the anomaly (a horizontal one and a vertical one), at least for one of the rows. I know this means losing information but, if the sections are wisely chosen, it will also mean gaining perspective and understanding.

Citation: https://doi.org/10.5194/gmd-2021-424-RC2
AC1:
'Response to the comments from the two anonymous referees', Christoph Fischer, 10 Apr 2022

We would like to thank both reviewers and the editor for their time spent on reviewing our manuscript and their thoughtful comments that helped to improve the article. Most notably, we revised the methodology of the 3-D identification algorithm by introducing a new figure and substantial changes to the text in the according sections. Please find our detailed responses to the comments in the attached PDF file.

Citation: https://doi.org/10.5194/gmd-2021-424-AC1
- AC2: 'Updated line numbers', Christoph Fischer, 11 Apr 2022
  
  We created an updated version of the Final Response to the reviewers, containing updated line numbers with regard to the newly submitted manuscript, but without further changes. The line numbers in the original response refer to the initial submitted manuscript. See the attached file.
  
  Citation: https://doi.org/10.5194/gmd-2021-424-AC2

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

AR by Christoph Fischer on behalf of the Authors (11 Apr 2022) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (12 Apr 2022) by Juan Antonio Añel

RR by Anonymous Referee #1 (18 Apr 2022)

Suggestions for revision or reasons for rejection

Second Review of “A novel method for objective identification of 3-D potential vorticity anomalies,” by Christoph Fisher et al.

General Comments

I appreciate the author’s revision and response to both sets of reviewer questions. I believe the paper is nearly ready for publication. Just a few minor comments and suggested technical corrections are listed below. Figure 10 was a very helpful addition to the paper. As I read this, I wondered whether the algorithm could be extended to 4-D, taking the time-evolution into account? Not sure how the “distance” would be calculated in that case, and how exactly the boundaries would be defined. Probably too complicated, but it would be interesting to know whether one could track individual PV anomalies as they flow through time.

Specific Comments

Lines 127-8: In the erosion exercise in Fig. 1, it looks like the mask is small enough that there would be some part of the extended PV intrusion that would be kept and should show up as a greyed out area in panel (b). Is this true, and if so does the algorithm remove these type of cutoffs during the erosion? Later, lines 261-3, you say “Generally, this inner core may contain multiple disjunct areas. In these cases we pick the biggest one as the core to proceed with, defined by its area.” I assume a similar process is done for this figure. If so, you may want to state that explicitly to avoid any confusion. It might actually be helpful if you greyed out the smaller inner core area (if it does indeed exist) to illustrate this.

Fig. 4h: This is a very minor point, but I’m not sure what the green and red symbols represent. Are they supposed to be funnels? Maybe a green check mark and a red X would make more sense to the reader?

Page 19: When I first read the revision, I wondered why the paragraph starting “Figure 9a...” had been moved from its previous position. In the original submission it was placed after the description of the 3-D algorithm. Now it is before the description, and the new Figure 10 is referred to in the algorithm description. After reading this section several times, I think I understand that you’re trying to orient the reader to the 3-D rendering of the tropopause with this figure. If so, would it make sense to not highlight the PV anomalies in Figure 9, but just show the tropopause, as in Figure 4c? Then later, after describing the algorithm, you could show this figure again with the anomalies identified, as in Figure 4g? Just a suggestion, because it is a bit confusing to see the anomalies in this figure, but then later explain how the anomalies are identified.

Is Figure 9 for 24 July 2015, as in Figure 10? May want to include the date/time in the caption.

Line 467: Was Met.3D used for the previous visualizations? If so, you might want to move this statement above to where you first use this software (Figure 9 description).

Suggested Technical Corrections

These are mainly stylistic suggestions that you can take or leave as you see fit.

Line 44: change to “objective identification of PV structures”

Lines 47,48, 78, etc.: change to “e.g.,” to be consistent with other uses of e.g.

Line 66: change to “Bithell et al. (1999)”

Line 99: change “that base on” to “that are based on”

Line 153: change “south pole” to “South Pole” for consistency

Line 175: does “resp” mean “respectively”?

Line 208: capitalize “Euclidean”

Line 216: change “of a measure” to “of as a measure”

Line 229: Do you want to capitalize Seasonal, since Subseasonal is capitalized?

Line 286: “Depending on the use case”, do you mean “Depending on the case”?

Line 293: change “Besides as filtering” to “Besides a filtering”

Line 380: Do you want “for cutoffs” within parentheses?

Line 398: change “independently on” to “independently of”

Line 405: change to “Bithell et al. (1999)”

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RR by Anonymous Referee #2 (22 Apr 2022)

ED: Publish subject to minor revisions (review by editor) (22 Apr 2022) by Juan Antonio Añel

Dear authors,

The reviewers have recommended minor revisions and acceptance of your work, respectively. Please, check the comments by the Reviewer 1.

Also, I have read with attention your manuscript, and I think that the reviewers have done a great work reviewing it. I think that using a stereographic projection is a very clever idea. My interest comes from the fact that the identification of PV fields is a topic that I researched a few years ago, also related to identifying the tropopause. You can consult it here: https://doi.org/10.1371/journal.pone.0072970

The obligations for editors of GMD state that "Editors themselves should be extra careful in suggesting additional literature." Our publication policy also focuses on avoiding citation malpractice. However, given the topic, I think it is justified to point out my work in this case.

Beyond the PV streamers, in line 38, you mention "cross-equatorial" intrusions. We also found this problem with our algorithm to detect PV fields. In several cases, this happened, and we had to consider it. Somehow, it is similar to the problem of using a longitudinal cartesian projection and dealing with a PV surface cut at a given meridian. We solved it simply by computing surfaces separately and aggregating areas. Our problem was a 2D surface, so simpler than yours.

Also, in lines 145-149, you talk about the discrete nature of algorithms and their impact on the computation. Somehow, this was precisely the problem we addressed with the ROI algorithm instead of piecewise-constant techniques. The improved interpolation and granularity behind the ROI implementation in IDL let us improve the accuracy of the computation of the PV surfaces, independently of the initial horizontal grid, with an increase in precision up to ten times and a computing time up to 9 times faster for a 1,5 degrees grid.

I think that it could be fair and that the point made in your work would benefit from citing our previous results on these two issues, as they show that similar problems have been faced in the past, and that there is room to improve the solutions when computing this kind of structures.

However, I want to clarify that one referee now recommends accepting your paper as is. Another requests only a few minor modifications and does not consider it necessary to review your work again before acceptance. Therefore, independently of your decision on citing or not the work that I point out, your manuscript is almost sure to be accepted for publication if you address the recommendations of Reviewer 1.

Regards,
Juan A. Añel
Geosci. Model Dev. Executive Editor

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AR by Christoph Fischer on behalf of the Authors (27 Apr 2022) Author's response Author's tracked changes Manuscript

ED: Publish as is (28 Apr 2022) by Juan Antonio Añel

AR by Christoph Fischer on behalf of the Authors (02 May 2022)

Short summary

Potential vorticity (PV) analysis plays a central role in studying atmospheric dynamics. For example, anomalies in the PV field near the tropopause are linked to extreme weather events. In this study, an objective strategy to identify these anomalies is presented and evaluated. As a novel concept, it can be applied to three-dimensional (3-D) data sets. Supported by 3-D visualizations, we illustrate advantages of this new analysis over existing studies along a case study.