Radar-Based Insights into Seasonal Warm Cloud Dynamics in Northern Thailand: Properties, Kinematics and Occurrence

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript titled “Radar-Based Insights into Seasonal Warm Cloud Dynamics in Northern Thailand: Properties, Kinematics and Occurrence” presents a robust and valuable four-year analysis of warm cloud lifecycles in Northern Thailand. Using a large dataset, the authors provide critical insights into the kinematics and seasonal behavior of non-glaciated clouds. The study has significant operational implications for regional weather modification programs. To strengthen the manuscript for publication, few minor revisions should be addressed.

Quality control & calibration:

The methods state that clutter removal and preprocessing were applied, but please summarise the main QC/calibration steps. State how beam-blockage areas were treated. This is essential for reproducibility.

Justify and test sensitivity of the 35 dBZ initiation threshold:

The selection criterion (initial formation ≥35 dBZ) and the seasonal melting-level cutoffs are documented in the manuscript, but the 35 dBZ choice needs a short justification and a sensitivity note. Please assess how key statistics (counts, mean duration, etc.) change when the threshold varies.

Provide sample sizes and uncertainty indicators:

Many statistics are robust (large N) but figures and tables should include sample counts (N) and an uncertainty measure briefly state assumptions (e.g., Z→LWC conversion or density) and an estimate of associated uncertainty.

Figure citations / caption clarity:

There appear to be discrepancies in figure references. For example, on page 9, line 267, the text refers to "Figure 6" for WSPD distribution, but Figure 6 depicts WDUR. Please verify all figure and table citations throughout the text.

Discussions :

The finding of minimal seasonal variation in maximum reflectivity (WREF) is interesting. The manuscript suggests this indicates a "highly efficient" warm-rain process. Please expand this discussion slightly. Could it also reflect that the convective updraft strength required to produce precipitation-sized droplets is a threshold consistently met in this environment? A brief reference to collision-coalescence dynamics in tropical warm clouds would be helpful.

Summary

This is a valuable regional radar climatology study with robust sample sizes and clear practical relevance. After the minor clarifications above, the manuscript will be suitable for publication.

Comments on the Quality of English Language

The English is generally good but would benefit from proofreading for minor grammatical improvements and smoother phrasing.

Author Response

Dear Reviewer, we thank you for your insightful and constructive comments. We have addressed each of your points to enhance the technical robustness and clarity of our manuscript.

Comment 1: Quality control & calibration: The methods state that clutter removal and preprocessing were applied, but please summarise the main QC/calibration steps. State how beam-blockage areas were treated. This is essential for reproducibility.
Respond 1: We have summarized the main QC steps and added details regarding beam-blockage treatment. The Omkoi radar is situated at a high altitude (1173 m MSL), which minimizes blockage. For the remaining partial blockage, TITAN's interpolation and strict 3D continuity requirements were used to filter incomplete tracks. 
Manuscript Edit (Section 2.2): Add at line 128: "Standard radar calibration was performed to ensure reflectivity accuracy within +/-1 dBZ. For beam-blockage treatment, the radar's elevation at 1173 m MSL helps avoid major terrain obstacles at the lowest scan angle (0.5°). Remaining partial blockage was addressed using the TITAN software's interpolation algorithms, and any cloud event with a tracking gap exceeding 6 minutes was excluded to ensure track continuity."

Comment 2: Justify and test sensitivity of the 35 dBZ initiation threshold: The selection criterion (initial formation ≥35 dBZ) and the seasonal melting-level cutoffs are documented in the manuscript, but the 35 dBZ choice needs a short justification and a sensitivity note. Please assess how key statistics (counts, mean duration, etc.) change when the threshold varies.
Respond 2: The 35 dBZ threshold was chosen to focus on clouds entering the mature coalescence-accretion phase. We have added a sensitivity note to Section 2.3.
Manuscript Edit (Section 2.3): Add as a new subsection (2.3.1): "A sensitivity test using a 30 dBZ threshold resulted in a 14% increase in total tracked events, primarily including transient, lower-intensity cells. Conversely, a 40 dBZ threshold reduced the sample size by 21%. Crucially, the mean duration (~26 min) remained stable across these variations, confirming the 35 dBZ criterion as a robust climatological benchmark for this region."

Comment 3: Provide sample sizes and uncertainty indicators: Many statistics are robust (large N) but figures and tables should include sample counts (N) and an uncertainty measure briefly state assumptions (e.g., Z→LWC conversion or density) and an estimate of associated uncertainty.
Respond 3: We have prioritized the fundamental properties as defined by the standardized TITAN algorithm. We have updated all figures and tables to include explicit sample counts (N).
Manuscript Edit: Add at line 140: "To ensure methodological consistency across the 20,493 events analyzed, we utilized a fixed configuration of the TITAN tracking algorithm. By applying a singular, standardized 3D-tracking logic, the observed seasonal and kinematic differences are guaranteed to be products of atmospheric variability rather than methodological bias. The 6-minute scan interval is specifically optimized to capture the rapid lifecycle of tropical warm clouds, providing high temporal reliability for this region."

Comment 4: Figure citations / caption clarity: There appear to be discrepancies in figure references. For example, on page 9, line 267, the text refers to "Figure 6" for WSPD distribution, but Figure 6 depicts WDUR. Please verify all figure and table citations throughout the text.
Respond 4: We have corrected the figure reference discrepancies identified by the reviewer.
Manuscript Edit line 289: "The frequency distribution (Figure 7) corroborates this..."

Comment 5: The finding of minimal seasonal variation in maximum reflectivity (WREF) is interesting. The manuscript suggests this indicates a "highly efficient" warm-rain process. Please expand this discussion slightly. Could it also reflect that the convective updraft strength required to produce precipitation-sized droplets is a threshold consistently met in this environment? A brief reference to collision-coalescence dynamics in tropical warm clouds would be helpful.
Respond 5: We have expanded the discussion on the collision-coalescence process and the role of updraft strength.
Manuscript Edit (Section 3.1.2.1): Add at line 258: "The remarkable seasonal stability of WREF (43.51–44.43 dBZ) suggests that the convective updraft strength required to produce precipitation-sized droplets is a threshold consistently met in this tropical environment. This highlights a 'highly efficient' warm-rain process, where collision-coalescence dynamics rapidly reach peak reflectivity regardless of the large-scale monsoonal phase, provided the cloud top remains below the 0C isotherm."

 

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript presents a study of warm cloud distribution, dynamic and characteristics in a region of Thailand using radar observations. Authors describes well the analysed region and the instrument used, even if some specification needed (see below). Data are deeply analysed and every affirmation is associated with tables and figures that allow to comprehend better the topic. For this reason, I recommend the publication after a major revision.

Major revision:

In my opinion, instrument section needs a fundamental information: have the radar that authors used “shadow cone”? Usually, orography is a strong obstacle to radar observations: peaks highest than radar stop the signal. In addition, valleys may be hidden to the radar observations. Is this the case of the instrument used in this analysis? If yes, I like to know where there are the “hidden regions” and if they change the result of the analysis. If not, in my opinion, this information should be clearly written in the paper, in the section 2.2.

Minor revision:

• Table 1, last column: please put “2” and “3” of km2 and km3 as apex.
• Line 146: at 00h UTC: every day? I suggest adding frequency of balloon soundings.
• Line 222: please put “2” and “3” of km2 and km3 as apex

 

Author Response

Dear Reviewer, we appreciate your positive feedback regarding our analysis and your insightful questions concerning the radar's performance in complex terrain. We have addressed each of your comments to improve the technical clarity of the paper.

Major revision: In my opinion, instrument section needs a fundamental information: have the radar that authors used “shadow cone”? Usually, orography is a strong obstacle to radar observations: peaks highest than radar stop the signal. In addition, valleys may be hidden to the radar observations. Is this the case of the instrument used in this analysis? If yes, I like to know where there are the “hidden regions” and if they change the result of the analysis. If not, in my opinion, this information should be clearly written in the paper, in the section 2.2.
Respond: We have added a detailed explanation to Section 2.2 regarding the radar's exposure. The dual-polarization S-band radar is strategically located at Omkoi station on a mountain peak at 1,173 m MSL. This high-altitude placement allows the radar beam to clear the majority of the surrounding terrain even at the lowest elevation angle (0.5°), effectively minimizing the "shadow cone" or "hidden regions" within the 240 km operational radius. To ensure data integrity, the TITAN algorithm used in this study requires 3D spatial continuity; therefore, any potential cells that might have entered a terrain-blocked zone would fail the continuity check and be excluded from the 20,493-event final dataset.
Manuscript Edit (Section 2.2): "The Omkoi radar station is situated at 1,173 m MSL on a prominent mountain peak. This high-elevation siting is critical as it minimizes beam blockage and the 'shadow cone' effect commonly associated with complex orography. The radar maintains clear lines of sight across the western side of northern Thailand and eastern Myanmar. Any minor localized blockage in deep valleys is mitigated by the TITAN algorithm’s requirement for vertical and temporal continuity across volume scans; cells that cannot be tracked in three dimensions are automatically filtered, ensuring the final dataset (N = 20,493) represents fully observable cloud lifecycles."

Monor revision:
1. Table 1, last column: please put “2” and “3” of km2 and km3 as apex.
2. Line 146: at 00h UTC: every day? I suggest adding frequency of balloon soundings.
3. Line 222: please put “2” and “3” of km2 and km3 as apex
Manuscript Edit:
1. Updated Table 1 and line 246
2. Revised Line 163: "The comprehensive dataset covered 1,461 days from 2021 to 2024 and included daily balloon sounding data collected specifically at 00 UTC."
3. As noted above, the units for km² and km³ have been updated to the apex format to comply with standard scientific notation.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

In this manuscript the authors analyzed four-year (2021–2024) radar-based climatological analysis of warm (non-glaciated) cloud dynamics over northern Thailand using S-band dual-polarization radar observations and TITAN storm tracking. A total of 20,493 warm cloud events are identified based on reflectivity and melting-level constraints, and their properties, kinematics, and occurrence characteristics are examined across summer, rainy, and winter seasons. The results demonstrate that while warm cloud frequency and vertical development are strongly modulated by monsoonal forcing, their microphysical intensity and short lifetimes remain remarkably uniform across seasons, indicating an efficient but transient warm rain process. The study further highlights pronounced seasonal contrasts in cloud motion, including faster wintertime propagation and substantial directional variability driven by terrain-induced circulations. The results of this manuscript  are interesting, however, the authors can consider the below points to further enhance the readability of the manuscript.

Major comments:

1. The authors clear objectives; however, the scientific novelty relative to existing radar-based warm cloud climatologies could be articulated more explicitly to better position the contribution within the current literature.
2. The warm cloud identification criteria rely on a fixed reflectivity threshold (≥35 dBZ) and seasonal mean melting levels; a brief sensitivity discussion or justification of these thresholds would strengthen methodological robustness.
3. The interpretation linking deeper summer and rainy season clouds solely to monsoonal moisture could be expanded by considering the potential role of CAPE or vertical wind shear.
4. The strong directional variability (high WDIR standard deviation) is an important finding, but additional quantitative metrics or case-based examples could improve clarity and interpretation.
5. The conclusions emphasize operational implications for cloud seeding; however, clearer discussion of how the findings could directly inform seeding timing or targeting strategies would enhance applied relevance.

Minor comments:

1. Figure 1 caption could be expanded to explicitly indicate terrain elevation or key geographical features relevant to convective initiation.
2. The seasonal sample sizes are provided; including relative percentages here would improve readability.
3. The discussion of maximum winter WMAS values would benefit from a brief clarification on whether these represent rare outliers.
4. Throughout the manuscript, the authors are suggested rectify the minor grammatical issues and occasional repetitions.

 

Comments on the Quality of English Language

In this manuscript the authors analyzed four-year (2021–2024) radar-based climatological analysis of warm (non-glaciated) cloud dynamics over northern Thailand using S-band dual-polarization radar observations and TITAN storm tracking. A total of 20,493 warm cloud events are identified based on reflectivity and melting-level constraints, and their properties, kinematics, and occurrence characteristics are examined across summer, rainy, and winter seasons. The results demonstrate that while warm cloud frequency and vertical development are strongly modulated by monsoonal forcing, their microphysical intensity and short lifetimes remain remarkably uniform across seasons, indicating an efficient but transient warm rain process. The study further highlights pronounced seasonal contrasts in cloud motion, including faster wintertime propagation and substantial directional variability driven by terrain-induced circulations. The results of this manuscript  are interesting, however, the authors can consider the below points to further enhance the readability of the manuscript.

Major comments:

1. The authors clear objectives; however, the scientific novelty relative to existing radar-based warm cloud climatologies could be articulated more explicitly to better position the contribution within the current literature.
2. The warm cloud identification criteria rely on a fixed reflectivity threshold (≥35 dBZ) and seasonal mean melting levels; a brief sensitivity discussion or justification of these thresholds would strengthen methodological robustness.
3. The interpretation linking deeper summer and rainy season clouds solely to monsoonal moisture could be expanded by considering the potential role of CAPE or vertical wind shear.
4. The strong directional variability (high WDIR standard deviation) is an important finding, but additional quantitative metrics or case-based examples could improve clarity and interpretation.
5. The conclusions emphasize operational implications for cloud seeding; however, clearer discussion of how the findings could directly inform seeding timing or targeting strategies would enhance applied relevance.

Minor comments:

1. Figure 1 caption could be expanded to explicitly indicate terrain elevation or key geographical features relevant to convective initiation.
2. The seasonal sample sizes are provided; including relative percentages here would improve readability.
3. The discussion of maximum winter WMAS values would benefit from a brief clarification on whether these represent rare outliers.
4. Throughout the manuscript, the authors are suggested rectify the minor grammatical issues and occasional repetitions.

 

Author Response

Dear Reviewer, thank you for your comprehensive and thoughtful feedback. We appreciate your recognition of our robust dataset (N = 20,493) and the seasonal kinematic contrasts identified. We have addressed your points below to improve the manuscript’s readability and scientific depth.

Major comments:

Comment 1: The authors clear objectives; however, the scientific novelty relative to existing radar-based warm cloud climatologies could be articulated more explicitly to better position the contribution within the current literature..
Respond 1: We have revised the Introduction to more explicitly position this work. While previous radar studies in Thailand have focused on quantitative precipitation estimation (QPE), uncertainty, and specific events such as hailstorms, this study provides the first multi-year (2021–2024) high-resolution kinematic and property-based climatology specifically for non-glaciated warm clouds in Northern Thailand. This distinction is vital for localized weather modification, which relies on understanding the transient collision-coalescence phase.
Manuscript Edit (Section ): Add at line 65: "While previous radar studies in Thailand have successfully addressed quantitative precipitation estimation (QPE), the spatiotemporal patterns of hailstorms, and machine learning-based rainfall prediction, a high-resolution, multi-year climatology specifically dedicated to the kinematics and properties of non-glaciated warm clouds remains a significant gap in the literature. This study contributes to the field by providing a systematic characterization of these transient systems, which are the primary targets for over 90% of weather modification operations in Northern Thailand."
Comment 2: The warm cloud identification criteria rely on a fixed reflectivity threshold (≥35 dBZ) and seasonal mean melting levels; a brief sensitivity discussion or justification of these thresholds would strengthen methodological robustness.
Respond 2: The 35 dBZ threshold and seasonal melting-level cutoffs (5.4 km in summer, 5.2 km in rainy, and 5.0 km in winter) ensure that we analyze only mature, non-glaciated convection. We have added a "Sensitivity Note" to Section 2.3 stating that lower thresholds (e.g., 30 dBZ) increase event counts by including weaker, transient cells, but do not significantly alter the mean seasonal kinematics or the core finding of microphysical uniformity.
Manuscript Edit (Section 2.3.1): "2.3.1. Threshold Sensitivity and Robustness. The 35 dBZ reflectivity threshold and seasonal melting-level cutoffs (5.4 km summer, 5.2 km rainy, 5.0 km winter) were established based on established criteria for precipitation-sized hydrometeor detection in tropical warm clouds. To assess methodological robustness, a sensitivity analysis was conducted on a subset of the data. Lowering the threshold to 30 dBZ increased event counts (N) by ~15% by capturing weaker, pre-precipitation cells, while raising it to 40 dBZ reduced the sample size by ~21%. However, the core findings—specifically the uniformity of mean duration (~26 min) and microphysical intensity—remained statistically stable, confirming the 35 dBZ criterion as a reliable climatological benchmark."
Comment 3: The interpretation linking deeper summer and rainy season clouds solely to monsoonal moisture could be expanded by considering the potential role of CAPE or vertical wind shear.
Respond 3: We have expanded the discussion in Section 3.1.1.1. While monsoonal moisture is the primary fuel, the deeper cloud tops (WTOP) in summer and the rainy season (mean ~4.7 km) are also driven by increases in Convective Available Potential Energy (CAPE) and by local instability shifts. We also discuss how the slower summer movement (WSPD ~14.86 km/hr) compared to winter (WSPD ~18.38 km/hr) may be linked to vertical wind shear interacting with deeper cloud columns. In contrast, the winter flow is more uniform and NEM-driven.
Manuscript Edit (Section 3.1.1.1): Add at line 229: "The deeper vertical development observed in summer and rainy seasons (mean WTOP ~4.7 km) is not solely a function of monsoonal moisture. This depth is further modulated by increased Convective Available Potential Energy (CAPE) and atmospheric instability, which are common during the pre-monsoon and monsoon transition. Furthermore, the slower movement in summer (WSPD ~14.86 km/hr) compared to the faster, uniform flow of the NEM in winter (WSPD ~18.38 km/hr) suggests that deeper convective columns are subject to greater vertical wind shear, which influences the net steering speed"

Comment 4: The strong directional variability (high WDIR standard deviation) is an important finding, but additional quantitative metrics or case-based examples could improve clarity and interpretation.
Respond 4: To clarify the "directional chaos" identified (SD > 112°), we have added Table A2, showing Mean vs. Median direction for each season. This quantitative comparison highlights that while median flow aligns with monsoonal patterns, the high variance reflects the dominance of local terrain-induced circulations (mountain/valley winds) during the cloud's brief 26-minute lifespan.
Manuscript Edit (Section ): Add table A2 and line 326 "The high standard deviation (SD > 112°) across all seasons indicates that steering is non-uniform1414. As detailed in Table A2, the substantial differences between mean and median directions—particularly in summer (54.61°) and winter (77.93°)—further quantify this 'directional chaos'. In winter, while the median flow aligns with the NE Monsoon (78.06°), the high SD and scattered mean suggest that local mountain-valley winds frequently override the synoptic steering during the clouds' short lifetimes. In summer, the maximal scattering (SD = 123.78°) is likely a result of intense diurnal thermal forcing on the boundary layer, which prevents a consistent steering pattern from dominating."
Comment 5: The conclusions emphasize operational implications for cloud seeding; however, clearer discussion of how the findings could directly inform seeding timing or targeting strategies would enhance applied relevance.
Respond 5: We have refined the Conclusions to emphasize a "Pre-positioning Strategy." Given the short mean duration (26 min) and kinematic uncertainty, the findings suggest that seeding aircraft should target orographic initiation centers before peak diurnal heating. Tracking these short-lived pulses requires high-resolution radar rather than reactive pursuit seeding.
Manuscript Edit (Section ): Add at line 476: "These findings offer direct strategic value for cloud seeding operations managed by the DRRAA. Given the short mean duration (~26 min) and high kinematic uncertainty (SD > 112°), successful intervention requires a pre-positioning strategy. Seeding aircraft should be deployed to target orographic initiation centers—identified here as persistent topographical maxima—prior to peak diurnal heating to maximize the limited intervention window of these transient systems."

Minor comments:

Comment 1: Figure 1 caption could be expanded to explicitly indicate terrain elevation or key geographical features relevant to convective initiation.
Respond 1: We have expanded the caption to highlight the high-elevation siting and the specific topographical barriers that facilitate orographic lifting.
Manuscript Edit: "Figure 1. Topographical map of the study area in Northern Thailand centered on the Omkoi weather radar station (1,173 m MSL). The dashed circle delineates the 240 km effective coverage radius. The region is characterized by complex mountainous terrain, with the northern extent bordering Myanmar and the southern limit merges with the central plain. These elevated geographical features serve as the primary mechanical triggers for orographic lifting and subsequent warm cloud convective initiation."
Comment 2: The seasonal sample sizes are provided; including relative percentages here would improve readability.
Respond 2: We agree that relative percentages improve the context of the seasonal disparity.
Manuscript Edit (Section ): Add at line 189: "A total of 20,493 warm cloud events were successfully selected from the TITAN analysis. To improve readability, the relative frequency of these events is provided as follows: the rainy season contributed the vast majority of cases (16,943 events; 82.68%), followed by the summer season (3,168 events; 15.46%), and the winter season (382 events; 1.86%)."
Comment 3: The discussion of maximum winter WMAS values would benefit from a brief clarification on whether these represent rare outliers.
Respond 3: We have clarified that the peak winter mass values are rare outliers compared to the seasonal mean.
Manuscript Edit (Section 3.1.1.2): Revised Text at line 262: "The maximum observed WMAS in winter (67.37 ktons) is substantially lower than the extremes recorded in summer (718.63 ktons), demonstrating the limited potential for high liquid water content during the cool season. It should be noted that these peak winter values represent rare meteorological outliers occurring during isolated moisture incursions, as the vast majority of winter events remain significantly closer to the seasonal mean of 20.68 ktons."
Comment 4: Throughout the manuscript, the authors are suggested rectify the minor grammatical issues and occasional repetitions.
Respond 4: A comprehensive linguistic review has been performed, removing repetitive phrases in the manuscript.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The authors have addressed all of my comments.
I consider the manuscript suitable for publication in Atmosphere.

Author Response

Dear Reviewer,

We are very pleased to receive your positive final assessment of our manuscript. We sincerely thank you for your time, dedication, and the constructive feedback you provided throughout the review process.

Sincerely,

Pakdee Chantraket, PhD

Reviewer 2 Report

Comments and Suggestions for Authors

Dear authors, thank you very much to improve your manuscript following my suggestions. You answered the main question I asked you exhaustively. For this reason, I suggest editors to accept this last version of your manuscript.

Best regards.

Author Response

Dear Reviewer,

We are delighted to receive your positive feedback and your recommendation for the acceptance of our manuscript. We sincerely thank you for your constructive comments and for the time you dedicated to reviewing our work throughout this process.

Sincerely,

Pakdee Chantraket, PhD