the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 23 Feb 2026
An Improved Method for Raindrop Size Distribution Retrieval Using Combined Dual-frequency Radar DFR
Abstract. Accurate retrieval of raindrop size distributions (DSDs) is essential for understanding cloud and precipitation microphysics. The dual-frequency ratio (DFR) measured by dual-frequency radars is independent of the normalized intercept parameter (Nw) and depends solely on the mass-weighted mean diameter (Dm). This characteristic makes DFR a powerful parameter for DSD retrieval. However, the DFR-Dm relationship is subject to a dual-solution ambiguity, particularly for smaller particles. In this study, W-band reflectivity is synthetically incorporated through scattering simulations based on measured DSDs, and retrieval relationships are established among X/Ka-band DFR, Ka/W-band DFR, and Dm. The results show that the ambiguity in the DFR-Dm relationship is substantially reduced, and the proposed method demonstrates clear advantages over conventional approaches, especially when retrieving DSDs of weak echoes. This advancement effectively addresses a key gap in the measurement and analysis of light precipitation processes.
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Status: open (until 25 May 2026)
- RC1: 'Comment on egusphere-2026-174', Anonymous Referee #1, 27 Apr 2026 reply
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CC1: 'Comment on egusphere-2026-174', Yichen Chen, 11 May 2026
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This manuscript addresses a key challenge in dual-frequency radar retrievals of raindrop size distributions (DSD) — the dual-solution ambiguity in the DFR-Dm relationship. The authors propose a novel solution by incorporating Ka/W-band DFR as an additional constraint, combined with T-matrix scattering simulations. The research is well-structured, the experimental design is sound, and the validation using ground-based disdrometer data is rigorous. The proposed method demonstrates clear improvements, particularly for weak echo regions. Overall, The manuscript is well suited for Atmospheric Measurement Techniques and will be valuable to the community. Accordingly, I recommend this manuscript for publication; however, you may consider the minor comments as follows:
- The manuscript's central assumption is the availability of W-band (93.75 GHz) data. However, W-band radar suffers from extreme attenuation in rainfall, potentially losing signal within hundreds of meters during moderate to heavy rain. It appears from Section 3.6 that Z_W was simulated using T-matrix calculations based on measured DSDs, rather than being directly observed. If true, this manuscript presents a proof-of-concept simulation study rather than a retrieval algorithm ready for operational radar data. The authors must clarify this point explicitly in the abstract, introduction, and conclusions. A more accurate framing would be "simulation-based retrieval framework" rather than simply "retrieval method."
- When DFR(X,Ka) ≤ 0, the algorithm switches to DFR(Ka,W). However, Table 6 shows that 12.5% of data points still fall within the ambiguous zone of DFR(Ka,W) (i.e., DFR(Ka,W) ≤ 0). The authors do not specify how these remaining ambiguous cases are handled. Are they discarded? Assigned a default Dm value? Or constrained by another relationship (e.g., Z_Ka-LWC)? The authors should provide a complete decision tree or flow chart (as an enhancement to Figure 1) that explicitly states the retrieval strategy for all possible combinations of DFR(X,Ka) and DFR(Ka,W). Additionally, the retrieval performance for these "doubly ambiguous" cases should be highlighted in Figure 17.
- In Section 3.1 (Instruments), the authors provide detailed specifications for the X/Ka-band radar and the 2DVD disdrometer. However, there is no mention of any W-band radar or the source of W-band reflectivity data. This is a critical omission for understanding the experimental setup. Please add a clear statement at the end of Section 3.1 or at the beginning of Section 3.3: "W-band reflectivities used in this study are simulated using the T-matrix method based on measured DSDs."
- Figure 6 shows dense scatterplots for Z_X-DFR(X,Ka) and Z_Ka-DFR(Ka,W). The 6th-order polynomial fitting curves are barely visible despite being provided in equation form. Please increase the line width or color contrast of the fitting curves. Also, add a note in the caption stating "The black curve represents the 6th-order polynomial fit."
- Several sentences could be clarified for better readability. For example, on Page 12, the sentence "...the corrected reflectivities were validated against those derived from ground-based raindrop size distributions measurements" — the word "those" is ambiguous. It should read "...validated against the theoretical reflectivity values derived from ground-based DSD measurements." Similarly, on Page 17, "This characteristic underpins the interpretation..." would be more accurate as "This characteristic guides the choice of retrieval algorithms..."
- In Table 1, the unit for Antenna Gain is listed as "dB". While this is common, the formal unit should be "dBi" (decibels relative to isotropic). Please consider this correction.
Citation: https://doi.org/10.5194/egusphere-2026-174-CC1 -
CC2: 'Comment on egusphere-2026-174', Li Luo, 15 May 2026
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This manuscript addresses the DFR-Dm dual-solution ambiguity in dual-frequency radar DSD retrievals by incorporating Ka/W-band DFR as an additional constraint. The method is well-designed and shows clear improvements, particularly for weak echoes. The following three key issues should be addressed prior to publication.
1. Clarify that W-band data are simulated, not observed
The manuscript's central innovation relies on Ka/W-band DFR, but it appears from Section 3.6 that W-band reflectivities are simulated using T-matrix calculations based on measured DSDs, rather than directly observed. Given that W-band radar suffers from extreme attenuation in rainfall, this distinction is critical. The authors must explicitly state in the abstract, introduction, and Section 3.1 that this is a simulation-based retrieval framework, and add a clear statement: "W-band reflectivities used in this study are simulated using the T-matrix method based on measured DSDs."
2. Specify handling of remaining ambiguous cases (DFR(Ka,W) ≤ 0)
Table 6 shows that 12.5% of data points still fall within the ambiguous zone of DFR(Ka,W) (i.e., DFR(Ka,W) ≤ 0). The authors do not specify how these "doubly ambiguous" cases are handled (discarded? default value? constrained by Z_Ka-LWC?). Please provide a complete decision tree or flow chart (as an enhancement to Figure 1) and evaluate the retrieval performance for these cases.
3. Quantitative assessment of the inversion errors caused by temperature variations
Provide quantitative error analysis (e.g., Dm bias) for 0°C, 10°C, and 30°C, not just state that errors are small.
Citation: https://doi.org/10.5194/egusphere-2026-174-CC2 -
CC3: 'Comment on egusphere-2026-174', Tiantian Yu, 20 May 2026
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This manuscript proposes an improved method for raindrop size distribution retrieval by combining dual-frequency radar DFR information, with the aim of reducing the well-known dual-solution ambiguity in the DFR–Dm relationship. The topic is relevant to radar meteorology and precipitation microphysics, and the manuscript addresses an important limitation of conventional DFR-based DSD retrieval methods, especially under weak-echo and light-precipitation conditions.
The proposed approach appears promising, and the reported improvement in the proportion of uniquely retrievable Dm values is encouraging. However, several key methodological issues need to be clarified before the manuscript can be considered for publication. In particular, the source and practical role of the W-band reflectivity require much clearer explanation, and the novelty of the proposed method should be more explicitly distinguished from previous studies.
1. The source and practical role of the W-band reflectivity must be clarified
The most important issue in the manuscript concerns the use of W-band reflectivity and DFR(Ka,W). The abstract states that W-band reflectivity is synthetically incorporated through scattering simulations based on measured DSDs. However, the instrument section only describes an X/Ka dual-frequency vertically pointing radar and a 2DVD disdrometer. No actual W-band radar measurement appears to be available.
2. The novelty of the proposed method should be more clearly distinguished from previous studies
The manuscript reviews several previous approaches for addressing the DFR–Dm ambiguity, including generalized DFR methods and differential dual-frequency radar equation methods. However, the distinction between the present method and previous work is not yet sufficiently clear.
3. The English language and grammar require careful revision
The manuscript contains a number of grammatical and stylistic issues that should be corrected before publication. For example, the section title “Compression the Ambiguous zone of DFR-Dm” is grammatically incorrect and could be revised to:
“Reduction of the Ambiguous Zone in the DFR–Dm Relationship.”
Similarly, the conclusion begins with “A improved raindrop size distribution retrieval method,” which should be corrected to:
“An improved raindrop size distribution retrieval method.”
4. The figures should be improved for clarity and interpretation
Several figures are central to the manuscript but could be made clearer.
For example, Fig. 1 should explicitly distinguish between observed variables, simulated variables, intermediate retrieval products, and final outputs. This is especially important because the role of the W-band reflectivity is currently ambiguous.
Fig. 11 is one of the most important figures in the manuscript because it demonstrates the reduction of the ambiguous DFR–Dm region. The ambiguous zones, thresholds, and physical interpretation should be labeled more clearly.
Fig. 17 contains many panels and is somewhat difficult to read. The authors may consider separating the Dm and Nw results into different figures or improving the layout.
For Figs. 18 and 19, the number of samples in each reflectivity interval should be reported, either in the figure panels or in the caption.
5. Terminology and notation should be standardized
The manuscript should use consistent terminology and notation throughout. For example: Dm, Nw, and LWC should follow a uniform notation style.
Clear and consistent notation will make the retrieval procedure easier to follow.
Citation: https://doi.org/10.5194/egusphere-2026-174-CC3
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Retrieving raindrop size distribution (DSD) using disdrometers has become a research hotspot in the field of weather radar in recent years, as DSD is crucial for understanding cloud and precipitation microphysical processes. This study combines disdrometer measurements with X-Ka band vertically pointing radar to perform DSD retrieval. To address the ambiguity problem in X-Ka band retrieval, the Ka-W band is further introduced as a joint constraint to reduce the ambiguous region between the dual-frequency ratio (DFR) and the mass-weighted diameter (Dm), thereby improving DSD retrieval accuracy. Multi-frequency radar retrieval is an important research direction, and the DFR-Dm ambiguity is a key issue in DSD retrieval. Although this study has practical significance, the methodology section suffers from unclear descriptions and logical issues related to circular reasoning.
Major issues:
Specific comments: