the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 16 Apr 2024
Evaluation of Aeolus feature mask and particle extinction coefficient profile products using CALIPSO data
Abstract. The Atmospheric LAser Doppler INstrument (ALADIN) onboard Aeolus, was the first high-spectral-resolution lidar (HSRL) in space. It was launched in 2018 and re-entered in 2023. The feature mask (A-FM) and extinction profile algorithms (A-PRO) developed for the Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) HSRL Atmospheric Lider (ATLID) have been adapted to Aeolus, called AEL-FM and AEL-PRO, respectively. These algorithms have been purpose built to process low signal-to-noise ratio space-based lidar signals. A short description of the AEL-FM and AEL-PRO algorithms is provided in this paper. AEL-FM and AEL-PRO prototype products (v1.7) have been evaluated using collocated Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Vertical Feature Mask (VFM) product and Level 2 aerosol profile product for two months of data in October 2018 and May 2019. Aeolus and CALIPSO are both polar orbiting satellites but they have different overpass time. The evaluations are focused on desert dust aerosols over Africa. These types of scenes are often stable in space (tens of km) and time (on the order of 0.5–1 hr), and thus, a useful number of col-located cases can be collected.
We have found that AEL-FM feature mask and the CALIPSO VFM show similar aerosol patterns in the collocated orbits but AEL-FM does not separate aerosol and cloud features. Aeolus and CALIPSO have good agreement for the extinction coefficients for the dust aerosols, especially for the cloud-free scenes. The Aeolus aerosol optical thickness (AOT) is larger than CALIPSO AOT mainly due to cloud contamination. Because of missing a cross polar channel, it is difficult to distinguish aerosols and thin ice clouds by using the Aeolus extinction coefficients alone.
The AEL-FM and AEL-PRO algorithms have been implemented in the Aeolus level 2A (L2A) processor. The findings here are applicable to the AEL-FM and AEL-PRO products in the L2A Baseline 17. This is the first time the AEL-FM and AEL-PRO products have been evaluated using CALIPSO data.
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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
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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
-
RC1: 'Comment on egusphere-2024-731', Anonymous Referee #2, 30 May 2024
The manuscript presents and discusses an algorithm that is used to analyze aerosol-related observations with ESA’s spaceborne wind Doppler lidar AEOLUS. The unique methodology is originally designed to analyze EarthCARE space lidar observations (feature mask algorithm, aerosol profile algorithm).
The respective AEOLUS aerosol products are compared with observations performed with NASA’s CALIPSO space lidar.
I clearly recommend publication.
I have only minor points
P5, L149: in Eq.3 we have … Ra … then in L150 we have … R_a …. please harmonize!
P5, L156: In Eq.4 we have Ra_a,1 and so on. All this is a bit confusing!
P7, L197: To my opinion, a discussion of the findings in Figures 4 and 5 is missing! Please, explain the observed features, at least a bit! The paper should not only focus on technical and data analysis points.
For example, the feature in Figure 4 (0-12.5km, and 15-20.0km , -63.2N, 228.3E, winter, July 2019) is interesting, I mean this column-like red/yellow feature? What is it? Smoke? Volcanic aerosol at 15-17.5 km height? The lidar ratio seems to be around 50 sr at 355 nm. So that could have been smoke! The particles were probably spherical so that AEOLUS data can provide reliable lidar ratios.
The lidar ratios in Figure 4 are often in yellow (around 100sr). Is that always related to dust and cirrus features, and therefore related to the fact that the cross-polarized signal component is missing in the case of the AEOLUS observations?
In Figure 5, there is layer from 7.5-11 km height over North/Eastern Siberia on the way to Alaska. Is that a smoke layer? Please explain and discuss. In Figure 4 (on the right and left sides of panels), there are large areas with reasonable lidar ratios around 50 sr, all over Siberia (from the ground up to the tropopause, 40N-85N, 42E-210E). Is that related to the strong Siberian fires in the summer of 2019? The smoke particles were probably spherical and the cross-polarized signal component zero…, that may explain the reasonable lidar ratios (see the MOSAiC paper of Ohneiser, ACP, 2021).
P7, section 3.1: I would mention more often that the wavelength is 355 nm.
Be clear: The CALIPSO extinction profiles are computed (estimated) from the retrieved backscatter profiles. CALIPSO cannot measure extinction profiles.
An Angstroem exponent of 0.55 is almost too high for dust, may be useful for marine aerosol, but is clearly too low for other aerosols (urban haze, smoke). However, you used 0.55 for all observations, right?
I am missing a bit a discussion on the uncertainty in the CALIPSO products caused by the Angstroem exponent assumption (0.55).
P10, Sect 4.1.2:
P10, L290: When comparing CALIPSO and AEOLUS observations please clearly state the wavelengths of comparison. It is always 355 nm, but the reader may not remember the content of section 3.1. One could provide such information in the figure captions.
Are the AEOLUS signals stronger than CALIPSO signals because the AEOLUS wavelength is 355 nm and the CALIPSO wavelength is 532 nm?
P12, L357: Monthly mean extinction coefficient… for the PBL? or for the entire troposphere?
Check and update the literature (preprint status may have changed).
Figure 7 and 8, the text on top of the panels is too small. Mention wavelength in the caption.
Figure 9: Mention the wavelength in the figure caption.
Figure 10: so many lidar ratios in yellow. Is the reason discussed in the main text body? Is that related to dust and cirrus?
Figure 11: the lidar ratio distribution belongs to what height range? .
Figure 12: Mention the wavelength in the figure caption.
Figure 13: What is the message of the correlation? What is the impact of the assumed Angstroem exponent of 0.55?
Figure 14: The extinction values from 5-15 km are confusing. The tropopause for latitudes from 0-30N is probably around 15-17 km height. So, probably only tropospheric extinction profiles are shown? Why is the agreement of the different extinction profiles so bad for heights >5km? The background extinction coefficients in the clean upper troposphere (and lower stratosphere) should be around 0.75-1 Mm-1 at 355 nm and about 0.25-0.5 Mm-1 at 532 nm. Is again an Angstroem exponent of 0.55 used in the conversion of the CALIPSO data?
Figures 15 and 16. Do we need these figures?
Citation: https://doi.org/10.5194/egusphere-2024-731-RC1 - AC1: 'Reply on RC1', Ping Wang, 01 Aug 2024
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RC2: 'Comment on egusphere-2024-731', Anonymous Referee #1, 30 May 2024
Review report egusphere-2024-731
The authors present an assessment study of the Aeolus’ feature mask and vertical extinction profiles versus CALIPSO data. Aeolus products have been obtained via the implementation of the AEL-FM and AEL-PRO retrieval algorithms adapted from the A-FM and A-PRO algorithms, which have been developed for the EarthCARE HSRL ATLID. The analysis focuses on dust-rich scenes probed by the two spaceborne instruments across N. Africa in October 2018 and May 2019. The study is well-organized, and all the essential details are well presented and discussed. Therefore, I recommend that the manuscript be published after addressing the minor comments provided below.
- Lines 64-65: To what extent your results will be affected by the consideration of L1B data generated with the most recent Baseline version (i.e., Baseline 16)?
- Lines 91-92: Is there any threshold on the number of counts?
- Line 177: Which is the source of the a priori lidar ratios and the particle effective area radii?
- Lines 179-181: Can you please explain better this sentence? What do you mean “… otherwise the lidar-ratio supplied by the classification procedure is used.”?
- Lines 234-236: In my opinion it would be quite interesting to show this comparison and briefly discuss the obtained outcomes. It is well known that when non-spherical particles (e.g., dust) are probed by ALADIN it is expected a “weak” performance in terms of reproducing the backscatter coefficient (for reasons already stated in the manuscript). Taking into account that there is a sufficient volume of Aeolus-CALIPSO collocated data, a better assessment can be given than those in Abril-Gago et al. (2022) and Gkikas et al. (2023), who presented single (few) dust cases.
- Line 286: I would suggest to remove this sentence since CALIPSO assigns a lidar ratio for each aerosol type.
- Lines 294-300: I am confused with this part of the text. Why are you considering all aerosol subtypes across the scene in order to reproduce the frequency histogram of S values? Do you think that it would be better to reproduce the histograms for specific aerosol types (dust and smoke for this case)? I think that the dust lidar ratio given by Song et al. (2023) are substantially higher than those provided in the DeLiAn database (Floutsi et al., 2023).
- Line 304: What do you mean with the term “error” for the CALIPSO extinction coefficients?
- Section 4.2: Do you see any noticeable differences between daytime and nighttime conditions?
- Section 4.1: Are you taking into account all the CALIPSO retrievals or are you processing only those tagged as “dust” in the classification scheme?
- Lines 335-336: How much your results would be affected in the case of using more realistic aerosol speciated lidar ratios (see DeLiAn)?
Lines 364-365: It would be nice to provide further explanation regarding this assertion, highlighting the necessity of the deployment of a cross-polar channel on the Aeolus-2 satellite mission.
Citation: https://doi.org/10.5194/egusphere-2024-731-RC2 - AC2: 'Reply on RC2', Ping Wang, 01 Aug 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-731', Anonymous Referee #2, 30 May 2024
The manuscript presents and discusses an algorithm that is used to analyze aerosol-related observations with ESA’s spaceborne wind Doppler lidar AEOLUS. The unique methodology is originally designed to analyze EarthCARE space lidar observations (feature mask algorithm, aerosol profile algorithm).
The respective AEOLUS aerosol products are compared with observations performed with NASA’s CALIPSO space lidar.
I clearly recommend publication.
I have only minor points
P5, L149: in Eq.3 we have … Ra … then in L150 we have … R_a …. please harmonize!
P5, L156: In Eq.4 we have Ra_a,1 and so on. All this is a bit confusing!
P7, L197: To my opinion, a discussion of the findings in Figures 4 and 5 is missing! Please, explain the observed features, at least a bit! The paper should not only focus on technical and data analysis points.
For example, the feature in Figure 4 (0-12.5km, and 15-20.0km , -63.2N, 228.3E, winter, July 2019) is interesting, I mean this column-like red/yellow feature? What is it? Smoke? Volcanic aerosol at 15-17.5 km height? The lidar ratio seems to be around 50 sr at 355 nm. So that could have been smoke! The particles were probably spherical so that AEOLUS data can provide reliable lidar ratios.
The lidar ratios in Figure 4 are often in yellow (around 100sr). Is that always related to dust and cirrus features, and therefore related to the fact that the cross-polarized signal component is missing in the case of the AEOLUS observations?
In Figure 5, there is layer from 7.5-11 km height over North/Eastern Siberia on the way to Alaska. Is that a smoke layer? Please explain and discuss. In Figure 4 (on the right and left sides of panels), there are large areas with reasonable lidar ratios around 50 sr, all over Siberia (from the ground up to the tropopause, 40N-85N, 42E-210E). Is that related to the strong Siberian fires in the summer of 2019? The smoke particles were probably spherical and the cross-polarized signal component zero…, that may explain the reasonable lidar ratios (see the MOSAiC paper of Ohneiser, ACP, 2021).
P7, section 3.1: I would mention more often that the wavelength is 355 nm.
Be clear: The CALIPSO extinction profiles are computed (estimated) from the retrieved backscatter profiles. CALIPSO cannot measure extinction profiles.
An Angstroem exponent of 0.55 is almost too high for dust, may be useful for marine aerosol, but is clearly too low for other aerosols (urban haze, smoke). However, you used 0.55 for all observations, right?
I am missing a bit a discussion on the uncertainty in the CALIPSO products caused by the Angstroem exponent assumption (0.55).
P10, Sect 4.1.2:
P10, L290: When comparing CALIPSO and AEOLUS observations please clearly state the wavelengths of comparison. It is always 355 nm, but the reader may not remember the content of section 3.1. One could provide such information in the figure captions.
Are the AEOLUS signals stronger than CALIPSO signals because the AEOLUS wavelength is 355 nm and the CALIPSO wavelength is 532 nm?
P12, L357: Monthly mean extinction coefficient… for the PBL? or for the entire troposphere?
Check and update the literature (preprint status may have changed).
Figure 7 and 8, the text on top of the panels is too small. Mention wavelength in the caption.
Figure 9: Mention the wavelength in the figure caption.
Figure 10: so many lidar ratios in yellow. Is the reason discussed in the main text body? Is that related to dust and cirrus?
Figure 11: the lidar ratio distribution belongs to what height range? .
Figure 12: Mention the wavelength in the figure caption.
Figure 13: What is the message of the correlation? What is the impact of the assumed Angstroem exponent of 0.55?
Figure 14: The extinction values from 5-15 km are confusing. The tropopause for latitudes from 0-30N is probably around 15-17 km height. So, probably only tropospheric extinction profiles are shown? Why is the agreement of the different extinction profiles so bad for heights >5km? The background extinction coefficients in the clean upper troposphere (and lower stratosphere) should be around 0.75-1 Mm-1 at 355 nm and about 0.25-0.5 Mm-1 at 532 nm. Is again an Angstroem exponent of 0.55 used in the conversion of the CALIPSO data?
Figures 15 and 16. Do we need these figures?
Citation: https://doi.org/10.5194/egusphere-2024-731-RC1 - AC1: 'Reply on RC1', Ping Wang, 01 Aug 2024
-
RC2: 'Comment on egusphere-2024-731', Anonymous Referee #1, 30 May 2024
Review report egusphere-2024-731
The authors present an assessment study of the Aeolus’ feature mask and vertical extinction profiles versus CALIPSO data. Aeolus products have been obtained via the implementation of the AEL-FM and AEL-PRO retrieval algorithms adapted from the A-FM and A-PRO algorithms, which have been developed for the EarthCARE HSRL ATLID. The analysis focuses on dust-rich scenes probed by the two spaceborne instruments across N. Africa in October 2018 and May 2019. The study is well-organized, and all the essential details are well presented and discussed. Therefore, I recommend that the manuscript be published after addressing the minor comments provided below.
- Lines 64-65: To what extent your results will be affected by the consideration of L1B data generated with the most recent Baseline version (i.e., Baseline 16)?
- Lines 91-92: Is there any threshold on the number of counts?
- Line 177: Which is the source of the a priori lidar ratios and the particle effective area radii?
- Lines 179-181: Can you please explain better this sentence? What do you mean “… otherwise the lidar-ratio supplied by the classification procedure is used.”?
- Lines 234-236: In my opinion it would be quite interesting to show this comparison and briefly discuss the obtained outcomes. It is well known that when non-spherical particles (e.g., dust) are probed by ALADIN it is expected a “weak” performance in terms of reproducing the backscatter coefficient (for reasons already stated in the manuscript). Taking into account that there is a sufficient volume of Aeolus-CALIPSO collocated data, a better assessment can be given than those in Abril-Gago et al. (2022) and Gkikas et al. (2023), who presented single (few) dust cases.
- Line 286: I would suggest to remove this sentence since CALIPSO assigns a lidar ratio for each aerosol type.
- Lines 294-300: I am confused with this part of the text. Why are you considering all aerosol subtypes across the scene in order to reproduce the frequency histogram of S values? Do you think that it would be better to reproduce the histograms for specific aerosol types (dust and smoke for this case)? I think that the dust lidar ratio given by Song et al. (2023) are substantially higher than those provided in the DeLiAn database (Floutsi et al., 2023).
- Line 304: What do you mean with the term “error” for the CALIPSO extinction coefficients?
- Section 4.2: Do you see any noticeable differences between daytime and nighttime conditions?
- Section 4.1: Are you taking into account all the CALIPSO retrievals or are you processing only those tagged as “dust” in the classification scheme?
- Lines 335-336: How much your results would be affected in the case of using more realistic aerosol speciated lidar ratios (see DeLiAn)?
Lines 364-365: It would be nice to provide further explanation regarding this assertion, highlighting the necessity of the deployment of a cross-polar channel on the Aeolus-2 satellite mission.
Citation: https://doi.org/10.5194/egusphere-2024-731-RC2 - AC2: 'Reply on RC2', Ping Wang, 01 Aug 2024
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Cited
Ping Wang
David Patrick Donovan
Gerd-Jan van Zadelhoff
Jos de Kloe
Dorit Huber
Katja Reissig
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(14486 KB) - Metadata XML