I would like to congratulate to the authors for this work that contributes with data analsysis for plume analsysis in real time in real scenarios for decision-making support.

The article proposes a sounding methodology to characterize fire plumes during wildfire events. Although it does not provide a detailed protocol, it clearly emphasizes the importance of in-situ data collection using a feasible and affordable approach to better understand and assess plume behavior and atmospheric dynamics during a fire. I find this work highly valuable, as fire analyses are often based solely on forecast data. This study offers a practical method for estimating fire plume dynamics in areas where radar systems are prohibitively expensive. Additionally, the real-time data collection and analysis performed during the fire enhance its value for emergency management, moving beyond the traditional post-event analysis approach.

The article presents very useful information and includes clear application examples. It is well-written and well-structured. However, readers should be familiar with fire and atmospheric terminology, and ideally be up to date with the current state of research on fire plume dynamics and fire typologies.

The article outlines a method for obtaining atmospheric soundings from an ongoing fire, including measurements not only of the ambient atmosphere but also of the head, flank, and rear of the fire. While the work does not go into detail about the balloon sounding launch procedure or the success rate—points also raised by an anonymous reviewer-it focuses on the sounding data collected from different locations and their use for analyzing plume state and potential, which is useful for operational decision-making.

The authors acknowledge the limitations of their approach and provide recommendations for how to work with the data presented.

This article makes an important contribution to operational practices and this research field by characterizing fire plumes and assess transitions between different fire plume behaviors.

I would recomment to the authors to apply at least minor comments when they apply.

The article focuses on integrating sounding data to characterize fire plumes, as stated in the title, and the content aligns well with this aim. The authors address the inherent uncertainty in the sounding data, particularly due to the balloons moving within the plume's indraft and temperature peaks, which affects the success rate of non-ambient soundings. However, there is no quantitative assessment of the uncertainty for each variable derived from the sounding methodology, nor an analysis of how sensitive the plume top estimation is to those uncertainties—beyond potential temperature and rising speed. I understand this could be the focus of a separate study, which would require a large number of soundings and additional instruments for validation in different contexts with prescibed fires. Still, the article highlights the importance of potential temperature and vertical velocity as key factors in plume-top estimation, with other variables being more relevant when using the parcel method for potential plume-top prediction.

Minor Comments:

Update model name and cite missing reference: MESO-NH/Forefire – Jean-Baptiste Filippi.

There is no need to justify the balloon radiosounding method beyond its affordability and operational simplicity. Other technologies like high-altitude atmospheric balloons, Doppler radar, UAVs, and helicopter-mounted sensors are capable of real-time data collection as well.

Table 1 may be unnecessary, but I understand that in real-world field campaigns, time constraints, costs, and complexity support the value of the information presented.

It would be helpful to use a consistent temperature unit throughout the article.

"S parcel increase by3°C" → should be "S parcel increases by 3°C" (missing space and verb correction).

"estimating the dilution plume height, is adequate" → remove the comma: "estimating the dilution plume height is adequate."

In Section 3.3.3, regarding the Casablanca III fire in Chile: it states the fire grew to 12,073 ha between February 8–10, 2023, but also says it had already blown up on February 2, reaching 363,000 ha. Including fire spread metrics would help readers better understand the relationship between plume dynamics and fire spread behavior.

"Fire behavior was initially expected to calm in the early evening, but there was a 60% chance of intensification during the day-to-night transition due to the advection of drier air from the SW" — I assume this is for context, and the 60% probability comes from a weather forecast ensemble.

This is an impressive paper which presents a comprehensive and timely study of pyroconvective fire-atmosphere coupling. It is based on a novel practical methodology and a very detailed and accurate dataset assessment, to obtain a precise characterization of fire plumes during pyroconvective events.

The main highlight of this study is the design and demonstration of an original and sound inductive methodology to reduce incertainty and improve efficiency of emergency systems at extreme wildfire events. This is a badly needed contribution to the effects of climate change on wildfire risk that are creating the most complex and critical emergency scenarios.   

On the basis of an updated and complete state-of the art, the first strenght of this study is to design and test a novel data-gathering method of pyroconvection dynamics in-situ and in real-time. Furthermore, the global dimension and multi-scalar approach of the research design enhances its consistency in the context of global climate change. Another strenght of this study is to define and to apply an accurate pyroconvention prototype system.

The obtained results provide a completely innovative understanding and modeling of pyroconvection dynamics. This contribution has a strong potential to build-up a powerful tool of information management enabling to anticipate defense actions to control the most challenging wildfire events and to mitigate firefighters and civil population vulnerability.   

The realistic and critical approach of the discussion section is also outstanding. The authors acknowledge the limitations of the methodology and consider the importance of contextual factors for a right assessment of measurements.

The conclussions on fire-atmosphere interaction are a badly needed contribution for a climate change adapted new model of proactive wildfire risk management beyond the current paradigm of existing fuel models and fire weather indexes.

It’s an excellent scientific paper that could have a huge scientific and operational impact. I don’t have any concrete suggestion for improvement further than those already done by previous reviewers. I congratulate the authors on this magnificent research.

This paper presents a valuable contribution to wildfire science by integrating fireline observations to enhance the understanding of fire plume behavior during pyroconvective extreme wildfire events. The authors effectively highlight the importance of detailed, real-time observational data in characterizing complex fire-induced phenomena, which has significant implications for improving plume modeling accuracy. The study's focus on firefighter safety underscores the practical relevance of accurately predicting plume dynamics to inform operational decision-making. Overall, the work advances both the scientific understanding of extreme wildfire behavior and its application to emergency response and safety management, offering meaningful insights for researchers, practitioners, and policymakers involved in wildfire mitigation and response efforts.

Having atmospheric profile data in the environment and inside the convective plume is of undeniable value, especially since it is emphasized that the indices proposed in recent years to classify pyroconvective activity do not seem entirely satisfactory. It is also important to highlight the significant contribution of integrating numerical weather prediction model data, as these can help to underscore the models' own limitations. Would it be interesting to incorporate atmospheric profiles from models with higher vertical and/or horizontal resolution, such as AROME? On the other hand, meteorological radar measurements also hold great relevance, as they allow for validation the estimates of plume tops. In summary, this is a substantial work that sheds light on research in such a critical field, given the key role that pyroconvective activity plays in the escalation of megafires.

 Review

This paper is an ambitious and very timely study that introduces a novel methodology for

in-plume radiosonde profiling during wildfires. The paper offers new insights into

fire–atmosphere interactions and pyroconvection dynamics, which is an active area of research

that needs further exploring. The indicators of potential transitions to extreme behavior help

identify plume top heights and characterize pyroconvection prototypes, which are notable

contributions that will help fire management better understand fire behavior. The authors also

provide one of the most extensive datasets of simultaneous ambient and in-plume profiles to

date. While the paper offers key contributions and advancements, the authors must refine the

write-up to be more consistent and coherent, improve the visualization of figures, and clarify

ambiguous points in the text to enhance readability. Please find comments and suggestions

below:

Clarify/highlight key contributions:

● I suggest restructuring the early stages of the paper to highlight key contributions and

advancements more clearly in the beginning. For example, line 466: “Observing the

plume top dilution just below the Lifting Condensation Level (LCL) in real-time is a

unique and valuable aspect of this methodology.”

● The title and abstract imply that the paper holds important implications for firefighter

safety. This is also foreshadowed in Lines 79-80 but not directly addressed in the paper.

Currently, it seems that safety is only discussed in terms of data collection. I recommend

including a sub-section or paragraph that discusses how the paper’s methods and

results can be used for firefighter safety.

Improving the visualization of main figures:

● Figure 1: The proportion of the observations are difficult to differentiate. I suggest adding

a text label denoting the relative proportion for each country/region (e.g., ME, 44.73%,

AE, 3.29%, SA, 51.98%). Also, since the symbols are difficult to see, it would help to see

the distribution of observations by fire type and by country/region (e.g., additional

stacked bar plots)

● Figure 3: Please update the horizontal axis labels so that they are consistent (i.e., Panel

a): θ (K) and Panel e): Temperature (oC))

● Figure 4: Please update the bottom table of the figure. I suggest to rename the contents

of “Fire event”, expand “Reg” (i.e., region), and write the fuel model code instead of as a

number. Also, under “Ambient Hour”, there are two times for Granja d’Escarp.

● Figure 8: I suggest updating the legend for plot a). First, I suggest using the full names of

the prototypes. Second, I suggest changing the font formatting of the legend and axis

labels to be more visible. Please also edit the x-axis label. Third, I suggest

re-ordering/modifying the visibility of the symbols (e.g., Re-order so symbols appear on

top or change the transparency). Fourth, for plot b), please edit the typo in the legend to

“radar echotop”

● Figures 9-12: Please edit the spacing of the plots in a) and b). Currently, the x-axis labels

are overlapping. Also, please edit the “Fire event” names,

● Figure 12: In the legend, the time formatting is incorrect (Check AM and PM) and the line

symbol for “Fire spread 19pm to 2am” is missing.

Clarification

● In Line 171, why should the soundings be taken “no more than 1 hour apart”? Is there

any supporting citation or any reasoning?

● Line 424: Why was the estimated plume top defined as the maximum height where radar

reflectivity was equal or higher than 12 dBz?

● Line 449: It is difficult to recognize the “excess of 7K”. I suggest explaining the surface

temperature values or labeling them to make this observation clearer

● Line 454: The authors claim that “the theoretical undiluted updraft height, estimated

using the MU parcel method (black dashed arrow), is located at 980 m AGL”. However,

Figure 9A shows that the black dashed arrow lies above 1000 m AGL. There are many

lines and colors in the plots which make the figure difficult to understand. While the

figure captions seem well-explained, the authors should clearly define each line and

color as well as provide ample reasoning for deciding on specific values (e.g., 980m

AGL) in the text to enhance readability.

Minor Comments

● Explicitly refer to ICON-EU as the atmospheric model

● Please add the short-form abbreviations of each prototype in Table 3. I suggest adding

them inside brackets below each prototype under the column “Pyroconvective Prototype”

● Please explain the state variables recorded by the in-plume (updraft) sonde or explicitly

refer to Table 2. The authors state that the in-plume sonde is classified based on its

position (head, flank, rear). Does this imply that, ideally, users should launch individual

sondes at each position to address turbulence experienced near the head direction of

the fire?

● Please use consistent terminology in the paper. For instance, in Figure 7, I suggest using

“Ambient” and “In-plume” (instead of “Environment”).

● Please provide a citation or reference to “the previous analysis” on Line 420