the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 26 Sep 2023
Aerosols and Clouds data processing and optical properties retrieval algorithms for the spaceborne ACDL/DQ-1
Abstract. The new-generation atmospheric environment monitoring satellite DQ-1, launched successfully in April 2022 carries the Aerosol and Carbon Detection Lidar (ACDL) which is capable of globally profiling the aerosols and clouds optical properties with high accuracy. The ACDL/DQ-1 is a high-spectral-resolution lidar (HSRL) with two-wavelength polarization detection, that can be utilized to derive the aerosol optical properties. The methods are specifically developed for the data processing and optical properties retrieval according to the specific characteristics of the ACDL system are introduced in detail in this paper. Considering the different signal characteristics and different background noise behaviours of each channel during daytime and nighttime, the procedures of data pre-processing, denoising process and quality control are applied to the original measurement signals. The aerosol and cloud optical properties products of the ACDL/DQ-1 including total depolarization ratio, backscatter coefficient, extinction coefficient, lidar ratio and colour ratio can be calculated by the retrieval algorithms presented in this paper. Two measurement cases with use of the ACDL/DQ-1 on 27th June 2022 and the global averaged aerosol optical depth (AOD) from 1st June to 4th August 2022 are provided and analysed, which demonstrated the measurement capability of the ACDL/DQ-1.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
(1587 KB)
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-2182', Anonymous Referee #1, 27 Nov 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2182/egusphere-2023-2182-RC1-supplement.pdf
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AC1: 'Reply on RC1', Guangyao Dai, 22 Dec 2023
Dear Reviewer,
Many thanks for reviewing our manuscript. We greatly appreciate the substantial amount of time and effort that you dedicated to this review process.
We have revised the manuscript according to your comments point-to-point and the response is presented below as the supplement.
Many thanks and best regards.
Guangyao Dai, Songhua Wu and Wenrui Long
On behalf of the co-authors
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AC1: 'Reply on RC1', Guangyao Dai, 22 Dec 2023
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RC2: 'Review of ‚Aerosols and Clouds data processing and optical properties retrieval algorithms for the spaceborne ACDL/DQ-1’ by Dai et al.', Anonymous Referee #2, 27 Nov 2023
The Aerosol and Carbon Detection Lidar (ACDL) is the first high spectral resolution lidar using an iodine filter in space. This is an important milestone for aerosol and cloud research from space and thus has the opportunity to advance our understanding of aerosols, clouds and their interaction, once the data will hopefully be made publicly. The manuscript describes the data, retrieval and first results of ACDL with focus on the aerosol (cloud) retrieval (ACDL-A). Thus, the paper is very important with respect to future use of the data, especially if viewed as a piece of documentation of the aerosol retrieval for DQ-1. However, for me to accept the paper, revisions are needed, as too many details of the processing are missing. In the block diagram Fig.6 there are some crucial processing steps like ‘Wavelet domain denoising’ or ‘Multi scale local denoising’ which are not described at all. There is also no description of the depolarization calibration.
Specific comments:
P1, l.16: ‘two wavelength polarization detection’ gives the impression that the depolarization is also detected for the 1064 nm channel. But according to the block diagram this is not the case.
P2, l.39: Please state once for non-lidar specialists what the lidar ratio is.
P2, l.50: It would be good to also include the first papers that proposed the HSRL technique.
P4, Figure 1: Besides the block diagram a table containing basic system parameters (rep. rate, pulse energy, telescope diameter, detector type, sensitivity, …) should be included. Some are mentioned in the text, but it is best to put them together in one place.
P5, l.110: If z is height (altitude), this assumes an exactly nadir pointing lidar. Since this is not the case, there are some terms missing to account for off nadir pointing.
P5, l.115: f_a should not depend on temperature and pressure, only f_m
P5, l.119: Can you give a reference, please?
P6, l.1443: Launch = emission?
P6, l.146: It is not clear, what is meant here. The two pulses are already separated in time.
P7, l.155: ‘The mean signals’ would be better, as a contrast to the ‘minimum values’ for the other channels. And only the mean offset can be estimated and subtracted and not the total ‘noise’ as stated in the text.
P8, l.159: It is not the ‘background noise’ but the ‘background signal’.
P9, Figure 5: Font of scale and axis titles are too small
P10, l.228: Median filters are not linear and do not preserve mean values. How large is the window for this? What is the size of the sliding window
P11, Equ.8: What numerical scheme is used to calculate the derivative? And in calculating the lidar-ratio, what measures are taken that alpha and beta have the same vertical resolution?
p.12, l.249: This paper gives only the basic algorithm. What values for bulk- and sheer viscosity and thermal conductivity and their temperature dependence are used? Please give a reference!
p.13, Figure 8: Fonts are too small.
P14, l281: flied = flew?
Citation: https://doi.org/10.5194/egusphere-2023-2182-RC2 -
AC2: 'Reply on RC2', Guangyao Dai, 22 Dec 2023
Dear Reviewer,
Many thanks for reviewing our manuscript. We greatly appreciate the substantial amount of time and effort that you dedicated to this review process.
We have revised the manuscript according to your comments point-to-point and the response is presented below as the supplement.Many thanks and best regards.
Guangyao Dai, Songhua Wu and Wenrui Long
On behalf of the co-authors
-
AC2: 'Reply on RC2', Guangyao Dai, 22 Dec 2023
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-2182', Anonymous Referee #1, 27 Nov 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2182/egusphere-2023-2182-RC1-supplement.pdf
-
AC1: 'Reply on RC1', Guangyao Dai, 22 Dec 2023
Dear Reviewer,
Many thanks for reviewing our manuscript. We greatly appreciate the substantial amount of time and effort that you dedicated to this review process.
We have revised the manuscript according to your comments point-to-point and the response is presented below as the supplement.
Many thanks and best regards.
Guangyao Dai, Songhua Wu and Wenrui Long
On behalf of the co-authors
-
AC1: 'Reply on RC1', Guangyao Dai, 22 Dec 2023
-
RC2: 'Review of ‚Aerosols and Clouds data processing and optical properties retrieval algorithms for the spaceborne ACDL/DQ-1’ by Dai et al.', Anonymous Referee #2, 27 Nov 2023
The Aerosol and Carbon Detection Lidar (ACDL) is the first high spectral resolution lidar using an iodine filter in space. This is an important milestone for aerosol and cloud research from space and thus has the opportunity to advance our understanding of aerosols, clouds and their interaction, once the data will hopefully be made publicly. The manuscript describes the data, retrieval and first results of ACDL with focus on the aerosol (cloud) retrieval (ACDL-A). Thus, the paper is very important with respect to future use of the data, especially if viewed as a piece of documentation of the aerosol retrieval for DQ-1. However, for me to accept the paper, revisions are needed, as too many details of the processing are missing. In the block diagram Fig.6 there are some crucial processing steps like ‘Wavelet domain denoising’ or ‘Multi scale local denoising’ which are not described at all. There is also no description of the depolarization calibration.
Specific comments:
P1, l.16: ‘two wavelength polarization detection’ gives the impression that the depolarization is also detected for the 1064 nm channel. But according to the block diagram this is not the case.
P2, l.39: Please state once for non-lidar specialists what the lidar ratio is.
P2, l.50: It would be good to also include the first papers that proposed the HSRL technique.
P4, Figure 1: Besides the block diagram a table containing basic system parameters (rep. rate, pulse energy, telescope diameter, detector type, sensitivity, …) should be included. Some are mentioned in the text, but it is best to put them together in one place.
P5, l.110: If z is height (altitude), this assumes an exactly nadir pointing lidar. Since this is not the case, there are some terms missing to account for off nadir pointing.
P5, l.115: f_a should not depend on temperature and pressure, only f_m
P5, l.119: Can you give a reference, please?
P6, l.1443: Launch = emission?
P6, l.146: It is not clear, what is meant here. The two pulses are already separated in time.
P7, l.155: ‘The mean signals’ would be better, as a contrast to the ‘minimum values’ for the other channels. And only the mean offset can be estimated and subtracted and not the total ‘noise’ as stated in the text.
P8, l.159: It is not the ‘background noise’ but the ‘background signal’.
P9, Figure 5: Font of scale and axis titles are too small
P10, l.228: Median filters are not linear and do not preserve mean values. How large is the window for this? What is the size of the sliding window
P11, Equ.8: What numerical scheme is used to calculate the derivative? And in calculating the lidar-ratio, what measures are taken that alpha and beta have the same vertical resolution?
p.12, l.249: This paper gives only the basic algorithm. What values for bulk- and sheer viscosity and thermal conductivity and their temperature dependence are used? Please give a reference!
p.13, Figure 8: Fonts are too small.
P14, l281: flied = flew?
Citation: https://doi.org/10.5194/egusphere-2023-2182-RC2 -
AC2: 'Reply on RC2', Guangyao Dai, 22 Dec 2023
Dear Reviewer,
Many thanks for reviewing our manuscript. We greatly appreciate the substantial amount of time and effort that you dedicated to this review process.
We have revised the manuscript according to your comments point-to-point and the response is presented below as the supplement.Many thanks and best regards.
Guangyao Dai, Songhua Wu and Wenrui Long
On behalf of the co-authors
-
AC2: 'Reply on RC2', Guangyao Dai, 22 Dec 2023
Peer review completion
Journal article(s) based on this preprint
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Cited
4 citations as recorded by crossref.
- A Deep Learning Lidar Denoising Approach for Improving Atmospheric Feature Detection P. Selmer et al. 10.3390/rs16152735
- Validation of initial observation from the first spaceborne high-spectral-resolution lidar with a ground-based lidar network Q. Liu et al. 10.5194/amt-17-1403-2024
- Aerosol optical property measurement using the orbiting high-spectral-resolution lidar on board the DQ-1 satellite: retrieval and validation C. Zha et al. 10.5194/amt-17-4425-2024
- Monitoring biomass burning aerosol transport using CALIOP observations and reanalysis models: a Canadian wildfire event in 2019 X. Shang et al. 10.5194/acp-24-1329-2024
Guangyao Dai
Songhua Wu
Wenrui Long
Jiqiao Liu
Yuan Xie
Kangwen Sun
Fanqian Meng
Xiaoquan Song
Zhongwei Huang
Weibiao Chen
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(1587 KB) - Metadata XML