the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 16 Jan 2025
Bridging the polarimetric structure and lightning activity of an isolated thunderstorm during the cloud life cycle
Abstract. Cloud microphysics and dynamics produce lightning flashes, which can be detected as polarimetric structures by radar. Many studies have indicated that differential reflectivity (ZDR) and specific differential phase (KDP) columns, which serve as proxies for updraft strength, are related to lightning activity; moreover, the quantities of ice and supercooled liquid water strongly influence the occurrence of lightning flashes via noninductive charging. However, few studies have focused on clarifying the sequence or interactions among these factors from the perspective of the cloud life cycle. Here, we establish the ‘3D mapping columns’ method, which is based on the Cartesian grid datasets; this method is sensitive for identifying and quantifying the ZDR columns in the early phase of cloud formation. Our study bridges the polarimetric structure and lightning activity within an isolated thunderstorm during the cloud life cycle. The results indicate that i) the parameter most relevant to total flashes/cloud-to-ground flashes is the content of supercooled rainwater/graupel. ii) The onset of the ZDR column can be used to forecast lightning initiation in advance. iii) The signatures of the ZDR and KDP columns should be complementary and used to retrieve dynamic information instead of lightning activity. Notably, the variation in the ZH intensity within ZDR columns has high potential for predicting lightning activity during the cloud life cycle, which is valuable for exploration in the future. Our study improves the overall understanding of cloud microphysics and lightning activity, and suggestions for using these multiple polarimetric signatures to forecast severe weather are provided.
- Preprint
(6192 KB) - Metadata XML
- BibTeX
- EndNote
Status: final response (author comments only)
-
RC1: 'Comment on egusphere-2024-4069', Eric Bruning, 09 Feb 2025
The authors analyze a single case study of an isolated thunderstorm over land to the northeast of Guangzhou, China. Analysis of differential reflectivity and specific differential phase columns over the lifecycle of this storm allows the authors to analyze how the cloud microphysics lead to lightning, and the lead time that polarimetric radar allows in inferring the onset of lightning.
The case study largely repeats previous findings. There are a few valuable advancements in analysis methods (column identification methodology; inferring supercooled rain water content using a method from the late 1990s / early 2000s; lead time calculations by different methods). There are also some process inferences related to different pathways by which lightning might be produced that could be valuable and clarifying, but the universality of which is hard to judge on the basis of a single case study.
The authors have therefore engaged substantively in an ongoing tradition of analysis of polarimetric radar and lightning signals, with fair-to-good scientific significance, and good scientific and presentation quality. Below I note additional areas that could improve the manuscript, adding some missing information and clarifying the interpretation.
Major comments:
The authors do a nice job of reviewing the literature. I wanted to also mention our just-published paper, Bruning et al. (2024, 10.1175/MWR-D-24-0060.1), which pursues a very similar analysis on a large sample of storms. The authors’ detailed look at the time-series perspective here is valuable (and something we did not yet do), and I would be interested to see where this study fits in the distribution of lightning and polarimetry of storms sampled by Bruning et al., which were probably similar small, isolated, subtropical storms.
355-57: It is not clear to me that the Zh signal is better related to lightning. – for instance, the Zh signal is quite noisy, while there is a very clear max in high LWC values just before each of the peaks in lightning that is much less noisy – and the authors conclude later that the LWC signal is the most robust. So this claim confused me.
369: how does the collapse of the column result in an increase in lightning if graupel (which is thought to be necessary for electrification) is inferred as decreasing or absent in the column? Further discussion of the process would be valuable here; there are some hints in the discussion/conclusion section here, but I felt that further information and data was needed to verify the interpretation of the two different pathways to lightning the authors have identified.
393: note, however, that the correlation with Zdr is relatively large and increases (0.6) for about 20 min before the maximum in lightning, but falls off rapidly by 12 min after the lightning increases. From a practical point of view, the timing of the maximum correlation is less important than a trend toward confidence for lightning, and so in that sense the Zdr signal is more helpful.
423-6: These correlation coefficients do not seem different enough to allow the authors to say one is best, especially on the basis of a single case study. Values all >0.8 are quite high for each of these variables.
449: After studying the lead times and identifying and emphasizing a 6 min lead time in their results section, the authors return to quoting the 36 min lead time in their conclusions, which does not seem supported by the detailed analysis the authors undertook. Of course, the 36 min lead is there in the data, but it is not well-correlated to lightning. Many moderately vigorous storms will produce a small Zdr column without going on to produce lightning. Likewise on 476-477, I would be reluctant to forecast lightning on the basis of a 36 min lead - that cell is simply one to keep an eye on for future lightning.
Fig. 12: the authors indicate that no Kdp column was present in their data, but do not show Kdp in Fig. 6. I would like to see further data on this, as it may explain the relatively fewer cases in Bruning et al. (2024) that had Zdr columns and lightning but did not have a Kdp column.
Minor comments:
31: The grammar implies lightning flashes can be detected with polarimetric structures; this is not directly possible. The polarimetric signatures are proxies for lightning with some associated error. Please rephrase.
37: “establish” — this study is not the first to use this method, as many of the authors’ citations show. “Build on” or “improve” would be a better choice, since “establish” implies that the authors have made a pioneering advancement. There are some thoughtful adjustments to past methods here, but they are incremental refinements.
124: “later” - do the authors mean a time scale immediately following the Zdr column (~5 min) or subsequent updraft pulses in a multicellular sequence (~20-30 min per cell)?
125: “attempted to determine the constraints of“ should be “attempted to constrain”
140-141: “therefore the correlation coefficient … was not high.” What does “therefore” mean here? It typically indicates that a conclusion has been reached, so the facts supporting the conclusion need to be stated first. They seem to be in the sentence following “therefore”.
175-181: what Kdp calculation method was used? Kdp is a very noisy measurement, and so is very sensitive to algorithm design and configuration choices.
220: here and throughout the paper, melting level is preferable, since melting always begins at this level for any hydrometeor but freezing might not.
221: What are other parameters (CAPE, etc.) of this sounding? They would be helpful in placing this storm in the context of other environments globally.
227: “automatically” should be “automatic”
271: A new sentence should start after “(Figure 2e,f)”.
281: “resulted by” should be “resulting from”
447: I suggest dropping “inappropriate”. Any algorithm choice requires some judgment, and reflectivity thresholds have a sound physical basis and are in wide use. Of course, using fewer or improved variables and thresholds is also good, and in that way the authors have made a nice methodological contribution, but “inappropriate” is unnecessarily harsh.
Citation: https://doi.org/10.5194/egusphere-2024-4069-RC1 -
RC2: 'Comment on egusphere-2024-4069', Anonymous Referee #2, 14 Apr 2025
General Comments:The authors investigated the relationships between polarimetric radar signatures (ZDR and KDP columns) and lightning activity throughout the lifecycle of an isolated thunderstorm. The authors present a methodology using a “3D mapping columns” approach to analyze radar data in detail. They found that the content of supercooled rainwater/graupel is the most relevant parameter to total flashes/cloud-to-ground flashes. Overall, the manuscript is well structured and easy to follow. However, there are several sections that require clarification and elaboration. The authors need to mention caveats/limitations of using “3D mapping columns” more effectively. Microphysics analysis is weak and lacks justifications for many of their observations. A more conservative approach can be adopted, which is to recommend monitoring parameters such as volume and variations of ZH intensity within ZDR columns, and supercooled liquid water content as a proxy for potential lightning activity development instead of using the term “forecast.” The recommendation is that the manuscript should be reconsidered after major revisions.Specific comments:1. The analysis is based on a single isolated thunderstorm. While this allows detailed examination, it raises questions about the universality of the conclusions. The authors should include enough cases to obtain robust statistical relationships. It is probable that the 6-min lead time might be just due to the temporal resolution (6 min) of radar data used in this study.2. The reported 36-minute lead time is also questionable due to several reasons. Firstly, it is based solely on a single case in this study. Secondly, as mentioned in the abstract (line 42), the authors state that the initial appearance of the ZDR column can be used to forecast lightning initiation in advance. Furthermore, the authors report at least 36 minutes of lead time (line 448) for forecasting the first lightning flash (line 449) in the observed cell. This is based on the very first appearance of the ZDR column at 17:24 CST and the onset of lightning activity at 18:00 CST. Now, considering Figure 7, where each column represents an observed ZDR column, there is a gap of 12 minutes at 17:30 CST and 17:36 CST when no ZDR column was detected. Notably, the manuscript does not provide an explanation for why (17:24 CST) was chosen over the first persistent ZDR observation at 17:42 CST to report the lead time, despite the 12-minute time gap. This explanation is crucial because the reported lead time is significantly larger compared to 4~6 minutes in previous studies (referenced in line 450).3. The authors should discuss whether the uncertainties of retrieval methods, ZDR and KDP thresholds used in the study, spatial and temporal resolution of the radar data, etc. influence the robustness of the conclusions.4. Line 157: Authors claim that their study is sufficient to establish a connection between “four parameters” and lightning using a single isolated storm case. However, despite numerous studies, including Sharma et al., 2024, which have observed a close correlation between these four parameters and lightning activity, they acknowledge the potential influence of other factors on this relationship. For instance, between ZDR or KDP volumes and total lightning flash rates. Therefore, the primary question arises: are these four parameters truly sufficient, and how do the authors substantiate this belief?5. Line 192: Briefly describe “the same method” here.6. Section 2.2: What equations did the authors use to retrieve the cloud microphysical parameters? How large are the uncertainties of these retrieval methods? Are the retrieval methods suitable for the current radar used in this study? How did the authors classify the particle categories, especially the ice particles in the mixed-phase regions?7. Line 205: What definition of “difference reflectivity” here? How is it different from ZDR? Why are the units of ZDP in dB?8. Line 216: Please justify using the assumption of “inverse exponential distribution”.9. Line 219: Please justify using the threshold of 35 dBZ for ZH here.10. Line 223-225: Did the authors use the threshold of “2 mm” for D0 to identify ZDR columns? If so, please justify why using 2 mm. Do the results change if changing this threshold?11. Line 260-263: Are there any other situations associated with KDP columns? Why did the authors ask a question here but did not answer it?12. Lines 332-334: Any evidence supporting this hypothesis?13. Lines 354-357: Quantify the relationship.14. Lines 365-369: Was it influenced by the uncertainties of retrieval methods?15. Lines 394-395, 454-455: If ZDR is assumed as a predictor for lightning then how do you explain variation of lightning before peak ZDR column height? Does it contradict physics?16. Line 394, 406, 415, 422, 424, 425: Reporting 6 minutes as lightning prediction time is ambiguous due to lack of uncertainty quantifications. Simple methods such as implementing confidence intervals (may use bootstrapping) and hypothesis testing are needed for robust analysis of the cross-correlation.17. Lines 440-442: The manuscript lacked any discussion on the concept of “interactions.” Could you please elaborate on how the authors managed to enhance our comprehension of the related cloud microphysics by solely examining the simple relationship between lightning flash frequency and ZDR or KDP column?18. Lines 469-472: The authors should examine whether the uncertainties of the retrieval methods and radar data spatial and temporal resolutions influence these results.19. Lines 480-481: List the four parameters.20. Lines 480-483: Another objective of this study was to clarify the sequence and interactions of the four parameters mentioned for predicting lightning activity during the cloud life cycle (lines 440-442). Consequently, after their analysis, the authors propose the conceptual model presented in Figure 12, which is a key highlight of this article. However, a clear explanation of the processes underlying Figure 12 is lacking and should be included in the manuscript.21. Lines 486-487: “the former” or the latter? Indicate it explicitly.22. Lines 492-493: Between lines 150 and 152 the authors explicitly state their intention to utilize this study for forecasting lightning activity within isolated thunderstorm cells over South China. However, they do not explicitly outline many uncertainties inherent in their study. For instance, one notable uncertainty involves determining the ZDR column height or volume based on an assumed freezing level derived from environmental soundings. The freezing level is frequently elevated within updraft cores due to latent heat release, which is influenced by the strength of updrafts relative to the ambient environment. This phenomenon can lead to biased estimations.23. Figure 4: Considering the goal is to understand and predict lightning activity using ZDR column, why does Figure 4 not show and discuss observed characteristics of the ZDR column at 18:00 hours when the first lightning was detected?24. Figure 6: Explain the representation of colorbar. Fig. 6c should be D0 and Fig. 6d should be LWC.25. Figure 8b: Is the lagged time for flash frequency or ZDR column height? It should be clarified in the figure caption.26. Figures 8b, 9b: Use different colors for total and CG flashes (avoid blue/orange) as it gets confusing later with figures 10 b, c and 11b, c when you use the same colors for below and above freezing levels. Using different line styles would also benefit to differentiate total and CG flashes.27. Figure 11: Choose different colors to show ice and graupel, as they both indicate retrievals above freezing level, using orange and blue is confusing here.Technical Corrections:1. Lines 44, 198: Define ZH, since using it for the first time in abstract and text respectively.2. Line 79: “lighting” -> “lightning”.3. Lines 148-150: Mentioned four parameters at line 147, so either remove 3 bullets or add fourth bullet before word KDP columns.4. Figure 5: Define “AGL” (Above Ground Level) in the caption. Also provide time zone details as [CST] on the x-axis label.5. Figures 6, 7, 8a, 9a, 10a, 11a: Provide time zone details on x-axis, Time [CST].6. Lines 405-406: Do authors mean ZDR column volume? Could be a typo here.Citation: https://doi.org/
10.5194/egusphere-2024-4069-RC2
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 174 | 29 | 8 | 211 | 8 | 4 |
- HTML: 174
- PDF: 29
- XML: 8
- Total: 211
- BibTeX: 8
- EndNote: 4
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1