Articles | Volume 18, issue 21
https://doi.org/10.5194/amt-18-6371-2025
© Author(s) 2025. This work is distributed under the Creative Commons Attribution 4.0 License.
Advantages of using multiple Doppler radars with different wavelengths for three dimensional wind retrieval
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- Final revised paper (published on 11 Nov 2025)
- Preprint (discussion started on 12 May 2025)
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
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RC1: 'Comment on egusphere-2025-1908', Anonymous Referee #1, 07 Jul 2025
- AC1: 'Reply on RC1', GyuWon Lee, 26 Aug 2025
- AC2: 'Reply on RC1', GyuWon Lee, 26 Aug 2025
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RC2: 'Comment on egusphere-2025-1908', Anonymous Referee #2, 29 Jul 2025
- AC3: 'Reply on RC2', GyuWon Lee, 26 Aug 2025
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AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by GyuWon Lee on behalf of the Authors (26 Aug 2025)
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ED: Referee Nomination & Report Request started (27 Aug 2025) by Gianfranco Vulpiani
RR by Anonymous Referee #1 (29 Sep 2025)
RR by Anonymous Referee #2 (29 Sep 2025)
ED: Publish subject to minor revisions (review by editor) (07 Oct 2025) by Gianfranco Vulpiani
AR by GyuWon Lee on behalf of the Authors (11 Oct 2025)
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ED: Publish as is (14 Oct 2025) by Gianfranco Vulpiani
AR by GyuWon Lee on behalf of the Authors (15 Oct 2025)
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Review of “Advantages of using multiple Doppler radars with different wavelengths for three-dimensional wind retrieval.” By Tsai et al.
This paper provides an overview of multi-Doppler analyses of a bow-echo that passed through South Korea on 2 August 2020. This convective system was sampled by a network of 11 radars of varying wavelengths. The authors conduct experiments where variational wind retrievals are made using only specific wavelength radars for given field experiments. While the authors conduct an exercise that would have potentially useful implications for how wind retrievals are calculated, there are numerous problems that prevent me from recommending this paper for publication.
Fatal flaws:
For one, the results are not placed in the context of the scanning strategies of the radars. Were the radars on a synchronous scan strategy? In addition, The S-band radars are all placed relatively close together, while the C and X band radars are further out, making a more optimal baseline for multiple Doppler retrievals. Could this also be a factor as well?
In the analysis of the updraft cores I found it hard to determine the number of updraft cores simply by eye. Have the authors considered counting these using thresholding techniques (see Varble et al (2014?)). Finally, The MB and RMSD values in the quantitative analysis in Table 4 do not clearly favor the SCX regime, and do not seem to demonstrate any quantitative improvement of using SCX over just S. Do the authors have statistics for earlier and later stages of this storm, or other cases, that would provide a larger amount of data for analysis?
Major comments:
Lines 87: Cha and Bell (2023) also added the IBM method to SAMURAI. Please mention their work in your literature review.
The authors should also mention the 3DVAR work done by Shapiro and Potvin that are now in PyDDA (Jackson et al. 2020). These works should also be mentioned in the literature review.
Minor/technical comments:
Line 100-103: Run on sentence.
Line 104: “lower” should be “coarser”
174: “frozing” should be “freezing”
Figure 2: The station measurements are difficult to read on the figure. I would suggest removing some and making the font size bigger, or removing all of them.
Line 216: Extra “.”
Line 361: “An”
Line 545: “leading edge”
Figure 4: “reflectivity”
References:
Varble, A., E. J. Zipser, A. M. Fridlind, P. Zhu, A. S. Ackerman, J.-P. Chaboureau, S. Collis, J. Fan, A. Hill, and B. Shipway (2014), Evaluation of cloud-resolving and limited area model intercomparison simulations using TWP-ICE observations: 1. Deep convective updraft properties, J. Geophys. Res. Atmos., 119, 13,891–13,918, doi:10.1002/2013JD021371.
Cha, T., and M. M. Bell, 2023: Three-Dimensional Variational Multi-Doppler Wind Retrieval over Complex Terrain. J. Atmos. Oceanic Technol., 40, 1381–1405, https://doi.org/10.1175/JTECH-D-23-0019.1.
Jackson, R., Collis, S., Lang, T., Potvin, C. and Munson, T. (2020) ‘PyDDA: A Pythonic Direct Data Assimilation Framework for Wind Retrievals’, Journal of Open Research Software, 8(1), p. 20. Available at: https://doi.org/10.5334/jors.264.