Articles | Volume 15, issue 16
© Author(s) 2022. This work is distributed underthe Creative Commons Attribution 4.0 License.
Detection and analysis of cloud boundary in Xi'an, China, employing 35 GHz cloud radar aided by 1064 nm lidar
- Final revised paper (published on 30 Aug 2022)
- Preprint (discussion started on 03 May 2022)
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor |
: Report abuse
RC1: 'Comment on amt-2022-86', Anonymous Referee #1, 28 May 2022
- AC1: 'Reply on RC1', Yun Yuan, 02 Jun 2022
RC2: 'Comment on amt-2022-86', Anonymous Referee #2, 06 Jun 2022
- AC2: 'Reply on RC2', Yun Yuan, 22 Jun 2022
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision
AR by Yun Yuan on behalf of the Authors (28 Jun 2022)  Author's response Author's tracked changes Manuscript
ED: Referee Nomination & Report Request started (30 Jun 2022) by Hiren Jethva
RR by Anonymous Referee #2 (15 Jul 2022)
RR by Anonymous Referee #1 (19 Jul 2022)
ED: Publish subject to minor revisions (review by editor) (23 Jul 2022) by Hiren Jethva
AR by Yun Yuan on behalf of the Authors (26 Jul 2022)  Author's response Author's tracked changes Manuscript
ED: Publish as is (13 Aug 2022) by Hiren Jethva
Yuan et al 2022 – Lidar and MMCR applied for the study on cloud boundary detection and the statistical analysis of cloud distribution in Xi’an region
This manuscript presents an observational combined lidar (1064 nm) and radar (8.6 mm) data set to determine the cloud boundaries over the ground station located at the Xian region. The authors use signal enhancement techniques to avoid background and aerosol signal thereby improving the SNR for the identification of cloud top and base boundaries. Analysis of one-year data set over the Xian is presented characterizing the cloud cover and single/multiple cloud layer occurrences. Overall, this is an interesting manuscript and has the potential to be published.
L 49: ‘Pal et al’ is repeated. There are several instances throughout the manuscript where the citations embedded in the sentence has repeated words.
L 115: Please use appropriate standard literature reference for the elastic backscattering lidar equation. For example: Measures, R.M., Laser remote sensing: Fundamentals and applications, Willey Publishers, 510 pp, 1984.
L 133: Details on the wavelet function used should be mentioned here.
L 135: Complete description of the flow chart processes – variables are missing. For example, the variables/symbols Rs, id, Pe, Ma, and Mi shown in figure 2 are nowhere defined.
L 138: What about the cases when high level clouds exist? It is well known that cirrus types of clouds occur high in the troposphere extending to the tropopause (on average ~17 km during summer over the subtropics).
L 206: Do you mean the 2 min time-resolution lidar profiles are duplicated 24 times to make it look like 5 sec temporal resolution data? Please mention this clearly.
L 355: I don’t think these are statistical rules. Please replace the term ‘statistical rules’ with ‘logic-based’ rules or something like that throughout the manuscript
L 359: The case1 in Table 3, please be specific if you mean ‘optically thin’ or ‘geometrical thin’ cloud? If it is optically thin than both cloud top and base can unambiguously be determined from lidar.
L 376: Clouds above 8 km has highest frequency in autumn, and these are likely stratus and cumulus clouds? This sentence doesn’t make any sense. Please refer to the WMO cloud classification – stratus and cumulus are low-level clouds those formed within 2 km above the surface level.
L 378: “height range of clouds is narrow, and the numerical range is wide”? Please re-write this sentence for more clarity mentioning the height range you are referring to.
L 383: Why the data presented in the figures showing vertical distribution of frequency of cloud occurrences are limited to 12 km? Or is this an underestimation of cloud top boundaries owing to the sensitivity of 8.6 mm radar? It is not uncommon to have high level clouds extending up to 15 km or more in the region of interest. Please present the results upto the tropopause level.
L 390: Before discussing the result, it would be beneficial to briefly describe how normalized cloud amount is computed here. Also, indicate the months of the season – spring (MAM), and summer (JJA). How is the maximum cloud amount 2.46 in summer?
L 394: I suggest adding fig 18c showing the total monthly hours of lidar, radar and simultaneous measurements in this figure. This is essential to understand the reported cloud characterization.
L 396: ‘frequency change characteristics…’? This does not make any sense. As the figure caption says it is the frequency distribution of cloud boundaries observed over Xian in 2021.
L 424: Remove the word ‘statistical’.