the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 Oct 2023
Global variable-resolution simulations of extreme precipitation over Henan, China in 2021
Abstract. A historic rainstorm occurred over Henan, China in July 2021 ("7.20" extreme precipitation event), resulting in significant human casualties and socio-economic losses. A global variable-resolution model (MPAS-Atmosphere v7.3) was employed to simulate this extreme precipitation event, by bridging the hydrostatic and non-hydrostatic scales together. A series of simulations have been done at both quasi-uniform (60 km and 15 km) and variable-resolution meshes (60–15 km and 60–3 km). For the 48-hour peak precipitation duration (07/20–07/22), the 60–3 km variable-resolution simulation coupled with the scale-aware convection-permitting parameterization scheme suite stands out predominately among other simulation experiments as it reproduces this extreme precipitation event most accurately, in terms of both the intensity and location of the peak precipitation. At 15-km resolution, the 60–15 km variable-resolution simulation achieves comparable forecasting skills as the 15-km quasi-uniform simulation, but at a much reduced computing cost. In addition, at 15-km resolution, we found that the default mesoscale suite generally outperforms the convection-permitting suite at 15-km resolution as simulations coupled with convection-permitting suite missed the 3rd peak of this extreme precipitation event while the mesoscale suite did not. This implies that, when the resolution of the refined region is coarser than the cloud-resolving scale, the convection-permitting parameterization scheme suite does not necessarily work better than the default mesoscale suite, but once the refined mesh is close to the cloud-resolving scale, the convection-permitting suite becomes scale aware such that it can intelligently distinguish the convective precipitation and grid-scale precipitation, respectively. Finally, it is found that the large-scale wind field plays a vital role in affecting extreme precipitation simulations since it primarily influences the transport of the water vapor flux thereby altering the prediction of the precise peak precipitation location.
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Status: final response (author comments only)
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CEC1: 'Executive Editor comment on gmd-2023-193', Astrid Kerkweg, 23 Oct 2023
Dear authors,
in my role as Executive editor of GMD, I would like to bring to your attention our Editorial version 1.2:
https://www.geosci-model-dev.net/12/2215/2019/
This highlights some requirements of papers published in GMD, which is also available on the GMD website in the ‘Manuscript Types’ section:
http://www.geoscientific-model-development.net/submission/manuscript_types.html
In particular, please note that for your paper, the following requirements have not been met in the Discussions paper:
- "The main paper must give the model name and version number (or other unique identifier) in the title."
- "If the model development relates to a single model then the model name and the version number must be included in the title of the paper. If the main intention of an article is to make a general (i.e. model independent) statement about the usefulness of a new development, but the usefulness is shown with the help of one specific model,the model name and version number must be stated in the title. The title could have a form such as, “Title outlining amazing generic advance: a case study with Model XXX (version Y)”.''
- "Code must be published on a persistent public archive with a unique identifier for the exact model version described in the paper or uploaded to the supplement, unless this is impossible for reasons beyond the control of authors. All papers must include a section, at the end of the paper, entitled "Code availability". Here, either instructions for obtaining the code, or the reasons why the code is not available should be clearly stated. It is preferred for the code to be uploaded as a supplement or to be made available at a data repository with an associated DOI (digital object identifier) for the exact model version described in the paper. Alternatively, for established models, there may be an existing means of accessing the code through a particular system. In this case, there must exist a means of permanently accessing the precise model version described in the paper. In some cases, authors may prefer to put models on their own website, or to act as a point of contact for obtaining the code. Given the impermanence of websites and email addresses, this is not encouraged, and authors should consider improving the availability with a more permanent arrangement. Making code available through personal websites or via email contact to the authors is not sufficient. After the paper is accepted the model archive should be updated to include a link to the GMD paper."
Thus the title of your article should be expanded by a statement like : ".. a case study with MPAS 7.3". Additionally, the data and the exact version of the code used needs to be made available in permanent archives (e.g. zenodo).
Yours, Astrid Kerkweg
Citation: https://doi.org/10.5194/gmd-2023-193-CEC1 -
CC1: 'Reply on CEC1', Zijun Liu, 26 Oct 2023
Dear Dr. Astrid Kerkweg,
We want to express our sincere gratitude for your prompt and insightful feedback on our paper submitted to GMD. Your comments are constructive, and we appreciate your guidance on ensuring that our paper aligns with the journal's requirements.
We will incorporate the suggested changes in the final manuscript, including expanding the title to include the specific model name and version, and ensuring the data and code version are made available in permanent archives such as Zenodo.
Best,
Zijun
Citation: https://doi.org/10.5194/gmd-2023-193-CC1
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RC1: 'Comment on gmd-2023-193', Anonymous Referee #1, 05 Nov 2023
This study indicates higher resolution and scale-aware parameterization greatly enhance simulation accuracy for extreme weather events, and considerations of computational efficiency and appropriate scale selection remain essential through a case study based on extreme precipitation over Henan. The manuscript is articulated with commendable clarity, and the modeling methodology exhibits a high degree of rigor. However, I remain uncertain about the potential implications of this study.
(1) Concerns revolve around how representative the model's results are, considering the unique characteristics of the "7.20" event and possible influences of local features like terrain. It would be beneficial for the authors to compare their findings with existing research in their discussion to offer a more complete view of the impact of using scale-aware parameterization in their models.
Citation: https://doi.org/10.5194/gmd-2023-193-RC1 -
AC1: 'Reply on RC1', Zijun Liu, 06 Nov 2023
Dear Referee,
We sincerely appreciate your thoughtful review of our manuscript. Thanks for your insightful suggestion to compare our findings with existing research for a more comprehensive perspective on the implications of scale-aware parameterization.
However, we are double checking if the comments are complete and seeking your kind assistance in clarifying the completeness of your review.
Best regards,
Authors
Citation: https://doi.org/10.5194/gmd-2023-193-AC1 -
RC2: 'Reply on AC1', Anonymous Referee #1, 06 Nov 2023
My apologies for any previous ambiguity in my feedback. Upon review of the manuscript, I commend the rigorous methodological approach. However, the applicability of the results and conclusions beyond this specific incident to other geographical locales potentially affected by extreme weather events remains unclear.
Research should go beyond reacting to one-time events and aim to create a strong framework for future studies, especially in predictive modeling. Regrettably, the manuscript falls short in addressing its findings' broader applicability, as outlined in lines 42 and 60, and the discussion from line 298 lacks depth, raising concerns about the study's relevance beyond the specific case examined.
Therefore, I recommend the manuscript could be strengthened by demonstrating how its conclusions might be applied to similar events in other regions. Such an expansion of scope would not only clarify the transferability of the study's insights for future predictive efforts and mitigation strategies for extreme precipitation but also enhance the manuscript's utility for a wider audience. This paper is impressive, and this revision would improve the manuscript's suitability for publication.
Citation: https://doi.org/10.5194/gmd-2023-193-RC2
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RC2: 'Reply on AC1', Anonymous Referee #1, 06 Nov 2023
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AC1: 'Reply on RC1', Zijun Liu, 06 Nov 2023
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RC3: 'Comment on gmd-2023-193', Anonymous Referee #2, 07 Dec 2023
General Comments
This study presents a comprehensive look at the performance of the Model for Prediction Across Scales (MPAS-atmosphere) across both hydrostatic and non-hydrostatic scales (e.g., 60km to 3km), uniform and variable-resolution grid-spacing, and two sets of built-in physical parameterization schemes (mesoscale suite and convection-permitting suite). The authors assess MPAS skill compared with CMA observations and ERA5 reanalysis in Henan province and tersely compare results to GFS forecasts over a single-member, sub-weekly simulation period.
Overall, I think the paper is well written and fits within the scope of GMD and could be, given a bit more work, a valuable contribution to the scientific community, particularly due to its emphasis on evaluating the use of new variable-resolution global climate models for extreme event recreation and sub-weekly weather forecasting. However, I think there are still several major revisions that need to happen prior to this paper being accepted. I would suggest that the editor assign major revisions to this manuscript.
Major Comments
- Given that this paper centers around the recreation of one weather event, why did the authors not perform an ensemble of simulations with slightly perturbed initial conditions to highlight internal variability impacts on precipitation intensity and spatial distribution? Was the computational demand too high to do so? If so, as mentioned below, it would benefit the reader to know this type of information explicitly. If not, why not perform, at least, a small ensemble of simulations. Related to this, it does concern me that all of the conclusions in this manuscript are based on single-member ensembles of a single event. Would these results hold if the authors simulated another event, perhaps in another season? The authors should at least acknowledge this limitation of their study, and at best run a few additional simulations to explore whether new simulations qualitatively alter their conclusions.
- Lack of discussion of physical meaning of results: Overall, the manuscript reads more like a technical report than a scientific manuscript; it focuses much more on questions of 'what' than questions of 'why'. In my opinion, this severely limits the usefulness of the paper. In its current form, I suspect that the only readers who might find the manuscript interesting would be users of the MPAS-Atmosphere model, since it essentially only focuses on describing how precipitation depend on resolution and parameterization schemes suite. Instead, if the manuscript had a stronger emphasis on why, the manuscript might be of interest to other model users facing similar questions about the effects of resolution and parameterization. For example, all of the figures basically focus on the precipitation itself, and while there are some references to the effects of large-scale circulation, but their analysis of this is somewhat superficial. Adding more analysis of how resolution or parameterization schemes lead to differences in large-scale circulation and precipitation will improve the paper.
- What is the basis for dividing the extreme precipitation event into two separate periods and analyzing them separately?
- Lines 166-172: the authors emphasize the relationship between the precipitation and atmospheric wind field. In Figure 3c, the wind filed predicted by GFS is very close to the ERA5 reanalysis, but the location and intensity of precipitation is still poorly forecasted. In addition to the wind field, other factors affecting precipitation can be discussed.
- Lines 258-267: Although the V3km.CP reproduced the third precipitation peak compared to 15km.CP, the authors should be note that the magnitude of the third precipitation peak simulated by V3km.CP is much smaller than the observation, rather than just praising the V3km.CP simulation.
- Some conclusion statements are “common sense”. For example, “This implies that, when the resolution of the refined region is coarser than the cloud-resolving scale, the convection-permitting parameterization scheme suite does not necessarily work better than the default mesoscale suite, but once the refined mesh is close to the cloud-resolving scale, the convection-permitting suite becomes scale aware such that it can intelligently distinguish the convective precipitation and grid-scale precipitation, respectively.” This kind of statements should be deleted. This is the purpose of designing these suites in this model, and cannot be the findings of this study.
- In addition, some conclusions are not supported by the analysis. For example, line 295, “Consequently, the latent heat release from the simulated peak precipitation would further feed back to the large-scale wind field such that the impact of the wind field upon the simulated peak precipitation is amplified.” I cannot find the results to support this conclusion. So is the line 302, “This implies that the seamless mesh transition of the global variable-resolution model is superior in simulating the extreme precipitation event.” Please add more analysis and discussion before drawing these conclusions.
Minor Comments
- Line 21: “(Jinfang et al., 2021)” maybe “(Yin et al. 2021)”.
- The nine-dash line is missing from all the maps.
- Line 213: “westerly wind” maybe “easterly wind”.
- The authors mention in Lines 259-260 and Lines 271-272 that “the forecast performance of the CP suite and MS suite at 15km is comparable”, but in fact all the CP simulations clearly miss the third precipitation peak, the differences are significant. I suggest rewording this statement.
- In addition to the correlation coefficients, I suggest that the authors add root-mean-square error or mean deviation characterizing the forecasted precipitation intensity.
Citation: https://doi.org/10.5194/gmd-2023-193-RC3
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