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https://doi.org/10.5194/egusphere-2023-664
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/egusphere-2023-664
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
11 Apr 2023
| 11 Apr 2023
Divergent convective outflow in ICON deep convection-permitting and parameterised deep convection simulations
Abstract. Upper-tropospheric deep convective outflows during an event on 10th–11th of June 2019 over Central Europe are analysed from simulation output of the operational numerical weather prediction model ICON. Both, a parameterised and an explicit representation of deep convective systems are studied. Near-linear response of deep convective outflow strength to net latent heating is found for parameterised convection, while coherent patterns in variability are found in convection-permitting simulations at 1 km horizontal grid spacing. Furthermore, three hypotheses on factors that may affect the magnitude of the convective outflow are tested in the convection-permitting configuration: organisation of convection through dimensionality of the systems, organisation of convection through aggregation and convective momentum transport.
Convective organisation and aggregation induce a non-linear increase in the magnitude of deep convective outflows with increasing net latent heating, as shown by the confidence interval of the best fit between power transformed net latent heating and detected magnitude of outflows. However, mixed and weaker than expected signals are found in an attempt to detect the representation of dimensionality of the convection and its consequences for the divergent outflows with an ellipse fitting algorithm that describes the elongation of the intense (convective) precipitation systems. As opposed to expectations, convective momentum transport is identified to slightly increase the magnitude of divergent outflows in this case study.
How to cite. Groot, E., Kuntze, P., Miltenberger, A. K., and Tost, H.: Divergent convective outflow in ICON deep convection-permitting and parameterised deep convection simulations, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-664, 2023.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
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Journal article(s) based on this preprint
31 May 2024
Divergent convective outflow in ICON deep-convection-permitting and parameterised deep convection simulations
Edward Groot, Patrick Kuntze, Annette Miltenberger, and Holger Tost
Weather Clim. Dynam., 5, 779–803, https://doi.org/10.5194/wcd-5-779-2024, https://doi.org/10.5194/wcd-5-779-2024, 2024
Short summary
Short summary
Deep convective clouds (thunderstorms), which may cause severe weather, tend to coherently organise into structured cloud systems. Accurate representation of these systems in models is difficult due to their complex dynamics and, in numerical simulations, the dependence of their dynamics on resolution. Here, the effect of convective organisation and geometry on their outflow winds (altitudes of 7–14 km) is investigated. Representation of their dynamics and outflows improves at higher resolution.
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
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RC1: 'Comment on egusphere-2023-664', Anonymous Referee #1, 17 Apr 2023
- The authors examine convective outflows in ICON convection permitting simulations and with parametrized convection over Germany. Overall, the authors have made a substantial effort in applying and explaining their interesting method and also made good efforts in statistically evaluating the significance of their work. However, at the end, especially concerning the 2nd half of the manuscript, the reader is still uncertain of what is the main outcome of the paper, are the results robust (small sample, noisy divergence fields, need to apply to situations with larger systems), what is the main difference between explicit and parametrized convection and why should momentum transport effect divergent outflow. Therfore I would suggest some major revisions along the following lines:
- pleae make sure from the beginning, already in the Abstract that you are dealing with Ensembles (otherwise reader, seeing just one case would think this is not significant)
- your sample size is still very small. From the modelling point of view it should not be much work to add more days - but dont know how much additonal work it is for your classification method. If you can do so, please add at least a few days with larger systems, this would be easily achievable for US systems or African squall lines with large and long-lived systems, but you can also add more days over Europe with prefrontal convection. You can still keep your main figures for Germany but for the scatter plots this would be extremely helpful. As it is I dont think you can quntitively talk about cMT or divergence in unorganized vs 2D squall line or Derecho type convection
- instead of using precipitation, could it be more useful to use low values of OLR or BT to charcaterize outflow, this might produce smoother results and better identify the upper level circulation?
- I am unsure it is helpful to normalize momentum transport by precipitation, yes it is natural to normalize divergence by heating but moemntum transport should be normalized by shear
- I found section 6 of your manuscript not convincing and not well written, please redo
- also in Figure 6a the divergence is so scattered, in the explicit run, corresponding to small scale systems="noise" in Figure 5b that I dont think it makes sense to discuss linear regressions (couloured lines) as a function of lead time or system evolution. In that sense it would even make more sense to discuss better the parametrized runs with larger outflow
Specific points:
- l12-13 "as opposed to expectations, CMT". I think this part also in result section should be revised or could be dropped in absence of sufficient cases/samples with shear
- l19 "initial condition flow variability". In you manuscript you actually use physics perturbation ensembles but never talk about it in the introduction
- l76-86 you formulate here 3 hypotheses. you might drop some of these in absence of larger samples and systems, as the main (also expected outcome) is a broadly linear relationship of divergent outflow and precipitation or better mass flux which should the also hold for laregr are (opposed to individual system)
- l188 "satellite systems" avoid this expression as "satellitee" misleading here
- l195 "vertical integral of CMT over all levels below". Not sure this is intended as over the whole troposphere cMT integrates to zero so in that case if you decide to keep CMT you might need to consider upper and lower troposphere separately
- l195-200 normalize CMT with precipiattion, see main comments
- l227 you migth add reference to https://doi.org/10.1002/qj.4185 here as actually the organisation is not so simple and sometimes too spotty in explicit compared to parametrized convection
- Also you might add refernce in the text to studies that explained that the convective outflow only has an effect to the circulation and subsequent predictability if the outflow occurs in the vicinity of the jet
- l297 "increase over time" this looks like the diurnal cycle evolution
- Figure 5: add (a), use same legend bar for (b) as for (c) and (d). Here and in Figure use everywhere units of [1/s] for divergence (not multiplied by density in some places, eg Figure 6) and scale legend bars by 1.e5
- Figure 6a, coloured slopes not convincing. Figure 6 b more convincing, but why is in Figure 6b shallow (magenta) so different form no convection run (organge)?
- l439-440 Why do you say "larger-scale flow feedbeck in PAR likely not accurately represented"? Isn't supported by anything in manuscript and how do you know that PER effect is not overestimated etc?
- As said above best would be to add more samples (days in Europe US or Africa) and also to rewite section 6 and adapt all Figure from Figure 6
Citation: https://doi.org/10.5194/egusphere-2023-664-RC1 -
RC2: 'Comment on egusphere-2023-664', Anonymous Referee #2, 12 May 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-664/egusphere-2023-664-RC2-supplement.pdf
- AC1: 'Comment on egusphere-2023-664', Edward Groot, 26 Jun 2023
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
-
RC1: 'Comment on egusphere-2023-664', Anonymous Referee #1, 17 Apr 2023
- The authors examine convective outflows in ICON convection permitting simulations and with parametrized convection over Germany. Overall, the authors have made a substantial effort in applying and explaining their interesting method and also made good efforts in statistically evaluating the significance of their work. However, at the end, especially concerning the 2nd half of the manuscript, the reader is still uncertain of what is the main outcome of the paper, are the results robust (small sample, noisy divergence fields, need to apply to situations with larger systems), what is the main difference between explicit and parametrized convection and why should momentum transport effect divergent outflow. Therfore I would suggest some major revisions along the following lines:
- pleae make sure from the beginning, already in the Abstract that you are dealing with Ensembles (otherwise reader, seeing just one case would think this is not significant)
- your sample size is still very small. From the modelling point of view it should not be much work to add more days - but dont know how much additonal work it is for your classification method. If you can do so, please add at least a few days with larger systems, this would be easily achievable for US systems or African squall lines with large and long-lived systems, but you can also add more days over Europe with prefrontal convection. You can still keep your main figures for Germany but for the scatter plots this would be extremely helpful. As it is I dont think you can quntitively talk about cMT or divergence in unorganized vs 2D squall line or Derecho type convection
- instead of using precipitation, could it be more useful to use low values of OLR or BT to charcaterize outflow, this might produce smoother results and better identify the upper level circulation?
- I am unsure it is helpful to normalize momentum transport by precipitation, yes it is natural to normalize divergence by heating but moemntum transport should be normalized by shear
- I found section 6 of your manuscript not convincing and not well written, please redo
- also in Figure 6a the divergence is so scattered, in the explicit run, corresponding to small scale systems="noise" in Figure 5b that I dont think it makes sense to discuss linear regressions (couloured lines) as a function of lead time or system evolution. In that sense it would even make more sense to discuss better the parametrized runs with larger outflow
Specific points:
- l12-13 "as opposed to expectations, CMT". I think this part also in result section should be revised or could be dropped in absence of sufficient cases/samples with shear
- l19 "initial condition flow variability". In you manuscript you actually use physics perturbation ensembles but never talk about it in the introduction
- l76-86 you formulate here 3 hypotheses. you might drop some of these in absence of larger samples and systems, as the main (also expected outcome) is a broadly linear relationship of divergent outflow and precipitation or better mass flux which should the also hold for laregr are (opposed to individual system)
- l188 "satellite systems" avoid this expression as "satellitee" misleading here
- l195 "vertical integral of CMT over all levels below". Not sure this is intended as over the whole troposphere cMT integrates to zero so in that case if you decide to keep CMT you might need to consider upper and lower troposphere separately
- l195-200 normalize CMT with precipiattion, see main comments
- l227 you migth add reference to https://doi.org/10.1002/qj.4185 here as actually the organisation is not so simple and sometimes too spotty in explicit compared to parametrized convection
- Also you might add refernce in the text to studies that explained that the convective outflow only has an effect to the circulation and subsequent predictability if the outflow occurs in the vicinity of the jet
- l297 "increase over time" this looks like the diurnal cycle evolution
- Figure 5: add (a), use same legend bar for (b) as for (c) and (d). Here and in Figure use everywhere units of [1/s] for divergence (not multiplied by density in some places, eg Figure 6) and scale legend bars by 1.e5
- Figure 6a, coloured slopes not convincing. Figure 6 b more convincing, but why is in Figure 6b shallow (magenta) so different form no convection run (organge)?
- l439-440 Why do you say "larger-scale flow feedbeck in PAR likely not accurately represented"? Isn't supported by anything in manuscript and how do you know that PER effect is not overestimated etc?
- As said above best would be to add more samples (days in Europe US or Africa) and also to rewite section 6 and adapt all Figure from Figure 6
Citation: https://doi.org/10.5194/egusphere-2023-664-RC1 -
RC2: 'Comment on egusphere-2023-664', Anonymous Referee #2, 12 May 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-664/egusphere-2023-664-RC2-supplement.pdf
- AC1: 'Comment on egusphere-2023-664', Edward Groot, 26 Jun 2023
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Edward Groot on behalf of the Authors (15 Nov 2023)
Author's response
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Manuscript
ED: Referee Nomination & Report Request started (27 Nov 2023) by Juerg Schmidli
RR by Anonymous Referee #1 (01 Dec 2023)
RR by Anonymous Referee #3 (09 Jan 2024)
ED: Publish subject to revisions (further review by editor and referees) (16 Jan 2024) by Juerg Schmidli
AR by Edward Groot on behalf of the Authors (06 Feb 2024)
Author's response
Author's tracked changes
Manuscript
ED: Referee Nomination & Report Request started (20 Feb 2024) by Juerg Schmidli
RR by Anonymous Referee #3 (05 Mar 2024)
ED: Publish subject to revisions (further review by editor and referees) (11 Mar 2024) by Juerg Schmidli
AR by Edward Groot on behalf of the Authors (27 Mar 2024)
Author's response
Author's tracked changes
Manuscript
ED: Publish as is (10 Apr 2024) by Juerg Schmidli
AR by Edward Groot on behalf of the Authors (10 Apr 2024)
Author's response
Manuscript
Journal article(s) based on this preprint
31 May 2024
Divergent convective outflow in ICON deep-convection-permitting and parameterised deep convection simulations
Edward Groot, Patrick Kuntze, Annette Miltenberger, and Holger Tost
Weather Clim. Dynam., 5, 779–803, https://doi.org/10.5194/wcd-5-779-2024, https://doi.org/10.5194/wcd-5-779-2024, 2024
Short summary
Short summary
Deep convective clouds (thunderstorms), which may cause severe weather, tend to coherently organise into structured cloud systems. Accurate representation of these systems in models is difficult due to their complex dynamics and, in numerical simulations, the dependence of their dynamics on resolution. Here, the effect of convective organisation and geometry on their outflow winds (altitudes of 7–14 km) is investigated. Representation of their dynamics and outflows improves at higher resolution.
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Latest update: 18 Sep 2024
Institut für Physik der Atmosphäre, Johannes Gutenberg Universität, Johannes-Joachim-Becher-Weg 21, Mainz, Germany
Patrick Kuntze
Institut für Physik der Atmosphäre, Johannes Gutenberg Universität, Johannes-Joachim-Becher-Weg 21, Mainz, Germany
Annette Katharina Miltenberger
Institut für Physik der Atmosphäre, Johannes Gutenberg Universität, Johannes-Joachim-Becher-Weg 21, Mainz, Germany
Holger Tost
Institut für Physik der Atmosphäre, Johannes Gutenberg Universität, Johannes-Joachim-Becher-Weg 21, Mainz, Germany
Download
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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- Final revised paper
Short summary
Deep convective clouds systems are often associated with severe weather conditions. They can organise into coherent convective cloud systems. Accurate representation in numerical weather prediction is challenging due to the dynamics of the systems and its dependency on resolution. Here, the effect of convective organisation and geometry on outflow winds (altitudes of 7–14 km) is investigated. The divergent outflow originating from these systems is represented in more detail at higher resolution.
Deep convective clouds systems are often associated with severe weather conditions. They can...