The manuscript focuses on the processes leading to symmetric instability that is often associated with the descent of a high-impact sting jet. While literature so far focussed on the descent, accompanying mesoscale instabilities and the strong winds, this article is the first (of my knowledge) that looks at the diabatic processes in earlier stages in detail. The approach seems promising, however, while they discuss the limitations of the method, I believe that the authors could reduce some of them to make stronger arguments.

Major concerns

1. While I appreciate the mention of limitations of the methodology throughout the paper, I do not quite understand, why some of them cannot be eliminated by choosing higher resolutions, both temporal and horizontal. In literature, simulations/trajectories with higher temporal resolutions of around 15 minutes showed an improvement in quality/resolving the SJ (e.g. work by the first author himself: Volonté et al., 2018), so it might benefit the study here as well. Same goes for horizontal resolution. What is the benefit of a near-operational simulation here? Having simulations with higher resolution would most likely strengthen your arguments without having to mention the limitations so often.
2. Why do you only focus on one starting time step? You mention the occurrence of SJ activity before and possibly after the chosen time step with separated negative PV regions. Why not look at one or two more time steps to see if they are comparable? Even without showing them in detail in the manuscript, it would be interesting to know if they show similar results.

Minor comments

Abstract

• l.5 I would appreciate adding the month or at least the year of the storm

Introduction

• l. 32ff.: Thinking of their (adapted) schematic, Eisenstein et al. (2022) would be a good reference here as well as they focus on all these different causes of wind gusts and also include convective gusts.
• l. 40-53: While it is nice to have recent examples, this can be shortened.
• Section 1.2.: For a long time, SJ literature focused mostly on CSI, while the importance of other mesoscale instabilities, especially SI, seems to have increased in recent years. Please add some context on the timing of occurrence of different kinds of mesoscale instability and why you focus on SI here.
• Mentioning frontolysis and direct frontal circulation later on, you might consider citing Schultz and Sienkiewicz (2013) and their schematic.

Data and method

• Section 2.1.: What is the motivation to choose a model setup close to the forecast? While I see some benefits, I feel like some mentioned limitations could be better handled using a different setup, i.e. higher temporal resolution for the computation of trajectories as you state this as a limitation but also horizontal resolution (see major comment 1).

Results

• l. 224: Why did you choose such a high wind speed threshold? I am wondering if more trajectories might show less noise as 51 seems quite low.
• Figure 4: I do not see a benefit in showing all time steps as some subfigures seem to be redundant. With the manuscript being quite long and the figure taking up a lot of space, you might consider only showing the important time steps here.
• Figure 4 and discussion: It is really interesting to see separated areas of negative PV possibly associated with SJ activity. It would be nice to see how the other SJ branches behave (see major comment 2)
• l. 338 ff: Especially mentioning the two factors here, I come back to major comment 1: Why not a higher temporal and horizontal resolution?
• Figure 6: Please indicate which tendencies belong together and that some are the sum of others
• l. 361 “median mean”?
• Section 3.3.: How can these results be interpreted so clearly with such large variability?
• Figure 9: It is very difficult to recognise all little details without zooming in a lot. Especially what lays underneath the trajectory points. You could consider showing a smaller area focussing more on the trajectory region or instead of showing single points, encircle the area of trajectory locations.
• Section 3.4.: I am wondering if the location relative to negative/positive areas would look different choosing higher temporal resolution (major comment 1). Please discuss this.

Discussion

• l. 592 and single starting time step for trajectories

Review of “Identifying the diabatic processes driving the evolution of a sting jet: the case of Storm Ciarán” by Ambrogio Volonté, Hanna Joos, Ming Hon Franco Lee, Richard Forbes, and Rémi Bouffet-Klein

The paper discussed the origin of the sting jet that produced extreme winds in intense storm Ciaran using Lagrangian back-trajectories and diabatic tendencies from model parameterizations. It focuses on the ascent period to investigate the processes responsible for the formation of negative potential vorticity, indicative of symmetric instability and which release triggers the descent and acceleration. The results show that condensation of water vapour, followed by evaporation of clouds and melting, is dominant among moist processes but with large variability, while sublimation of snow shows a more consistent pattern but with little contribution. The variability is due the the complex structure of the bent-back front associated with sharp gradients. The paper presents a proof of concept to investigate the contribution of cloud microphysics to sting jet formation, despite limitations in the method due to temporal and spatial resolution that leave large residual in the net change along trajectories.

The paper is interesting, reads well and contributes to the ongoing debate on the origin of sting jets that appears to converge toward the key role of symmetric instability. The diversity of involved physical processes is carefully discussed with help of a combination of Lagrangian and Eulerian diagnostics to disentangle their actual contribution in the complex environment of a bent-back front. The discussion of three-dimensional structures and the contribution of individual moist processes based on numerous subfigures is a bit lengthy but the results are nicely summarized in a schematic. My only concern is about the numerical limitation that is honestly discussed by the authors but questions the validity of the results. General and specific comments are listed below to help improve the paper.

General comments

1. The openly discussed limitation lies in the spatial and temporal resolution (hourly output on a 0.1° grid) that is not sufficient to adequately follow ascent (and even less descent, as mentioned in the text): why not use higher resolution then? This seems particularly relevant for the temporal resolution whereas higher spatial resolution may result in even sharper gradients and larger variability.
2. Somehow related, consistency with Met Office operational forecasts is highlighted a few times as a strength but it is not clear why, as numerical simulations are not restricted by and can explore beyond operational settings.
3. Horizontal and vertical cross-sections in numerous figures and panels (more than 50 in total!) tend to be repetitive and their number could likely be reduced.

Specific comments

l. 5 IFS is not defined yet (and likely not needed)

l. 9 why does it matter the simulation is consistent with forecasts?

l. 12–16 it is surprising to describe limitations before results

l. 29, 38 the UK is geographically part of Europe

l. 81 missing word

l. 97 it would be worth citing the subsequent studies rather than the review paper that cites them

l. 130–138 slightly repetitive; how can latent heating and cooling both lead to increased PV?

l. 170–173 it should be clarified that APV_cloud is decomposed into several terms (Table 1)

l. 182–184 repetition of 1.3

l. 185, 219 citation formatting

l. 207 twice “at low-levels”

l. 192–210 labelling or marking the discussed features on Fig. 1 would be helpful

l. 211–214 it is unclear why consistency with operational forecasts provides confidence, and satellite imagery is not presented here

l. 220 is the area illustrated somewhere?

l. 224–226 where do these number come from?

l. 265 I do not fully get the point: negative PV is a criterion to select trajectories, so why does it prove the SJ is associated with SI?

Fig. 4 the green dots are barely visible; it would be helpful to add the relative time (t-Xh); also consider reducing the number of panels to e.g. each 2h

l. 284 what is “the conceptual model of SJ evolution confirmed in that study”?

l. 298–299 Fig. 2a and 1b

Fig. 5 a horizontal scale would be helpful to estimate the size of the PV bands

l. 332 total change in PV

l. 369 it rather indicates that the large PV decrease is captured for a minority of trajectories only; anyway the vertical bounds must be adapted in Fig. 7a to identify this minority

l. 380 which panel?

l. 397 the them

l. 405–416 Fig. 8 could be used in this discussion; otherwise the Figure should be removed as it is not really discussed

l. 422 at at

Fig. 9 as in Fig. 4, the green dots are barely visible

l. 453–454 the pattern may be clearer than for other processes but is it relevant if the values are much smaller?

l. 500 dashed brown contour (barely visible)

l. 513 missing word

Fig. 13 it should be clarified that the plot shows a composite for all trajectories (if I got it correctly)