the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Vertical profiles of raindrop size distribution parameters of summer rainfall in the eastern Tibetan Plateau: retrieval method and characteristics
Abstract. The eastern Tibetan Plateau has a high elevation, with a cold and dry atmospheric background. The features of the raindrop size distributions (DSD) in this region have notable differences from those in the plains. The general empirical relationships for retrieving parameters of precipitation from radar observations are not applicable in the eastern Tibetan Plateau. In this study, we developed a new method based on optimal estimation theory to retrieve the vertical profiles of N0 and Dm from a Ka-band zenith-pointing Doppler radar. Validation by a field campaign during the summer of 2024 indicate that the average bias in the log10(N0) and Dm derived from the PARSIVEL2 disdrometer and the retrieved values is 0.12 and -0.1 mm, demonstrating the effectiveness of the retrieved DSD parameters in this region. Based on the retrieved vertical profiles of DSD parameters, some unique characteristics are found. The heavy precipitation (the maximum value in the reflectivity profile exceeding 30 dBZ) exhibits a higher particle number concentration above 2 km and larger raindrop size in the bottom of the rainfall on average. The mean values of Dm above 2 km are approximately 0.5 mm, for heavy precipitation, the value increase as the raindrops fall, reaching a peak at around 0.5 km. Precipitation that occurs after the nighttime cooling usually has higher particle concentrations and smaller particle sizes. Based on the above research, empirical relationships for the quantitative precipitation estimates (QPE) and attenuation correction using Ka-band radar in the eastern Tibetan Plateau are established.
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RC1: 'Comment on egusphere-2025-2523', Kwo-Sen Kuo, 14 Aug 2025
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AC1: 'Reply on RC1', Pingyi Dong, 19 Aug 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-2523/egusphere-2025-2523-AC1-supplement.pdf
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RC2: 'Reply on AC1', Kwo-Sen Kuo, 05 Sep 2025
My concerns have been satisfactorily addressed. I would accept the manuscript for publication.
However, I notice that the Preprint has not been updated. For example, Figure 5 still has blue on black.
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EMBED THE SNIPPET BELOW IN YOUR SITEEnable collaborative features and customize widget:Citation: https://doi.org/10.5194/egusphere-2025-2523-RC2 -
AC2: 'Reply on RC2', Pingyi Dong, 15 Sep 2025
We sincerely appreciate the time and effort you devoted to reviewing our manuscript. At present, the figure has not been modified in the submitted version, as it is still under discussion, and the revised manuscript can not be uploaded as  supplement.  We will ensure that the figure is revised accordingly in the final version.Citation: https://doi.org/
10.5194/egusphere-2025-2523-AC2
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AC2: 'Reply on RC2', Pingyi Dong, 15 Sep 2025
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RC2: 'Reply on AC1', Kwo-Sen Kuo, 05 Sep 2025
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AC1: 'Reply on RC1', Pingyi Dong, 19 Aug 2025
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RC3: 'Comment on egusphere-2025-2523', Anonymous Referee #2, 28 Nov 2025
The manuscript by Dong et al. examines rain microphysical properties derived from vertically pointing Ka band radar data on the Tibetan Plateau. Â The authors use an optimal estimation (OE) technique constrained by surface disdrometer data to derive the properties of the rainfall DSD in vertical columns above the radar during a single summer season. Â They show interesting statistical results of the rainfall properties and discuss possible physical processes that explain the results they find. Â The paper is well done. Â I do find that more information regarding the OE algorithm should be provided so that an interested reader could replicate their algorithm and fully understand their method. Â The details that I think should be provided are given in my specific comments following this paragraph. Â Subject to the minor revisions suggested, I find the paper to be a significant contribution to the scientific literature on this topic and worth of publication. Â
Specific Comments:
 Line 100: Should note that the velocity given is the Doppler Velocity since it is weighted by the backscatter cross section.
Line 104: Does the Haynes et al. algorithm account for the flattening of raindrops as they fall? This would certainly influence the details of the retrievals for heavier rain.Â
Line 133:Â It would be useful to see examples of the covarinace matrices or frequency distribution plots of the terms in Sa.Â
Line 133: Is the covariance matrix constant or is there a state dependent Sa? Â Are the terms considered to be correlated?
Line 134: Additional information should be provided regarding the observational error covariance matrix. Are the errors considered correlated or uncorrelated. What is the source of the uncertainty?Â
Line 137: There needs to be more information regarding how the terms of Jacobian, Kx, are calculated and please provide typical examples of the values of Kx. These details are useful because they show the degree to which the quantities to be retrieved are sensitive to the observations used to constrain them.
Figure 3: The authors should comment on the cause and influence of the systematic biases between the forward calculation and the observations that show up in this plot. the explanation given regarding the height difference and wind may be reasonable but how those issues would result in the biases shown should be demonstrated.Â
The fact that the calculated values do not lie on the 1:1 line  suggest that there may be forward model errors that are not accounted for - i.e. the assumption of spherical raindrops versus reality.  Accounting for forward model errors is key in these types of OE inversions.  Very often the forward model errors are larger (usually significantly larger) than the uncertainties in the observations. Â
Figure 4 and 5: Should explain the meaning of the error bars in figures 4 and 5. Â How are they derived?
Line 221: The contention made by the authors that N0 is higher and Dm smaller at the melting layer is not obvious in the data shown. If the authors think this is important, they should devise a way of showing it more clearly.
Line 242: I wonder if it would make sense to separate this into warm rain events versus cold? It seems likely that the Tsukuba results were associated with rain just below the melting layer when drops derived from large aggregate snow would begin to break up. That is not what is implied by Figure 7 of this paper.
Figure 8: Explain the meaning of the box plot. i.e. Median, Interquartile, 90'th, and 10'th percentiles?
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Citation: https://doi.org/10.5194/egusphere-2025-2523-RC3 -
AC3: 'Reply on RC3', Pingyi Dong, 08 Dec 2025
Dear reviewer,
We appreciate the time and effort that you devoted to reviewing our manuscript and are grateful for the insightful comments on improvements to our paper. We have revised the manuscript and added diagrams and descriptions to illustrate the method in detail. In the attached file, we provide a point-by-point response to each comment.
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AC3: 'Reply on RC3', Pingyi Dong, 08 Dec 2025
Data sets
penney1007/Article_Vertical-profiles-of.: code Pingyi Dong https://doi.org/10.5281/zenodo.15827786
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The manuscript is of good scientific quality and is clearly and well written, except for some minor issues, which include, but are not limited to:
Please see the attached PDF for more comprehensive and detailed comments and suggestions.
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