the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 27 Apr 2023
Cloud top heights and aerosol layer properties from EarthCARE lidar observations: the A-CTH and A-ALD products
Abstract. The Atmospheric Lidar (ATLID) on the Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) provides vertically resolved information on aerosols and clouds at the global scale. This paper describes the algorithms for the determination of cloud-top-height and aerosol-layer information from ATLID Level 1b (L1b) and Level 2a (L2a) input data. The ATLID L2a Cloud Top Height (A-CTH) and ATLID Aerosol Layer Descriptor (A-ALD) products are developed to ensure the provision of atmospheric layer products in continuation of the heritage from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). Moreover, the products serve as input for synergistic algorithms that make use of data from ATLID and EarthCARE’s Multi Spectral Imager (MSI). Therefore, the products are provided on the EarthCARE Joint Standard Grid (JSG). A wavelet covariance transform (WCT) method with flexible thresholds is applied to determine layer boundaries from the ATLID Mie co-polar signal. Strong features detected with a horizontal resolution of one JSG pixel (approximately 1 km) or 11 JSG pixels are classified as thick or thin clouds, respectively. The top height of the uppermost cloud layer together with information on cloud layering is stored in the A-CTH product for further use in the generation of the ATLID-MSI Cloud Top Height (AM-CTH) synergy product. Aerosol layers are detected as weaker features at a resolution of 11 JSG pixels. Layer-mean optical properties are calculated from the ATLID L2a Extinction, Backscatter and Depolarization (A-EBD) product and stored in the A-ALD product, which also contains the aerosol optical thickness (AOT) of each layer, the stratospheric AOT, and the AOT of the entire atmospheric column. The latter parameter is used to produce the synergistic ATLID-MSI Aerosol Column Descriptor (AM-ACD) later in the processing chain. Several quality criteria are applied in the generation of A-CTH and A-ALD, and respective information is stored in the products. The functionality and performance of the algorithm are demonstrated by applying it to common EarthCARE test scenes. Conclusions are drawn for the application to real-world data and the validation of the products after the launch of EarthCARE.
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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
(5826 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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- BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-748', Anonymous Referee #1, 17 May 2023
Accept as is
Citation: https://doi.org/10.5194/egusphere-2023-748-RC1 -
AC1: 'Reply on RC1', Ulla Wandinger, 10 Jul 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-748/egusphere-2023-748-AC1-supplement.pdf
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AC1: 'Reply on RC1', Ulla Wandinger, 10 Jul 2023
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RC2: 'Comment on egusphere-2023-748', Anonymous Referee #2, 19 May 2023
The paper describes the EarthCARE cloud top height and aerosol layer products (A-CTH, A-ALD). The paper is very well-written, logically organized, and the methods employed are sound. However, the motivation for this study was never quite clearly laid out in the manuscript. The authors also do mention a desire to maintain the heritage of the CALIPSO layer products, which is worthwhile. But why then develop an additional independent data products with independent methods when there already exists cloud and aerosol profiles products from ATLID (i.e. A-FM/APRO)? Layer products are indeed useful when it is more convenient to use layer data rather than more detailed profile data, but it seems more desirable to make the information provided by the layer product consistent with the profile product. That is: it would seem more prudent to derive the layer product from directly form the information given in the profile products rather developing a different algorithm.
While a flag is developed to alert a data user to such disagreement between these layers data products and their profile counterparts, how does one then decide which information is more reliable to use for their purpose? I'm concerned about the potential pitfalls of providing data users with 2 independent descriptions of cloud+aerosol locations and properties.
Other comments:line 108: why clear conditions only? One of strengths of lidars being able to provide aerosol information in the presence of clouds.
This layer information appears to be as a needed precursor to the MSI cloud and aerosol retrievals. But, in a similar vain to my comments above, why couldn't the profile version of the products be used for this purpose?
A ~10km average (i.e. 11 JSG pixels) seem insufficient to detect optically thinner layers as evident by the evident application of the algorithm to the Halifax aerosol scene. Why is 11 pixels chosen as the coarsest resolution? Are these undetected thin clouds/aerosols expected to impact the MSI retrievals?
For the test scenes, it be would be good to summarize the level of consistency between the (e.g. statistics of the level of consistency flag in
Figure 7)How sensitive are the results using the test scenes to the parameters chosen in Tables 1 and 2? Relatedly, have the authors thought about the process for optimizing these once EarthCARE is collecting real data?
Citation: https://doi.org/10.5194/egusphere-2023-748-RC2 -
AC1: 'Reply on RC1', Ulla Wandinger, 10 Jul 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-748/egusphere-2023-748-AC1-supplement.pdf
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AC1: 'Reply on RC1', Ulla Wandinger, 10 Jul 2023
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RC3: 'Comment on egusphere-2023-748', Anonymous Referee #3, 22 May 2023
This manuscript provides an introduction to the products of cloud top height and aerosol layer properties derived from EarthCARE lidar. Retrieval algorithms are discussed, and validation is carried out using model simulations. This study is of significant importance to the EarthCARE satellite mission and deserves documentation as it serves as a valuable resource for future data users, facilitating a better understanding of the data products and providing useful guidance. The manuscript is generally well-written, the methodology is sound, and the conclusions are solid. I recommend a minor revision prior to publication. Please find my detailed comments below:
1. While the manuscript provides a good discussion of the algorithm, it is not an Algorithm Theoretical Basis Document (ATBD). The objective of this paper could be better tied to the broader needs of the community. I believe it would be worthwhile to highlight the advantages and benefits of the EarthCARE lidar and the algorithm in the manuscript. Additionally, the paper could benefit from discussing what unique aspects of the products future data users can anticipate.
2. The manuscript contains numerous acronyms, which can become confusing. A table summarizing all acronyms in a single place would be appreciated.
3. I would appreciate a discussion on how the accuracy of the retrieval depends on the chosen configuration parameters.
4. Given that modeled cases are utilized to validate the algorithm, I would like to suggest performing a statistical performance analysis using a larger set of model outputs, as opposed to a limited number of cases.
5. Line 94: Can you explain the reason for choosing 11-pixel for this algorithm?
6. Line 108: Why only clear sky? There are two crucial scenarios that need to study the aerosol radiative effects, namely aerosols above low-level water clouds and aerosols beneath thin cirrus. These datasets are currently missing from existing satellite products.
7. Line 111: The assumption being made here is that the aerosol is vertically well-mixed within the boundary layer. Could you elaborate on the uncertainty associated with this assumption?
8. Line 293-295: In cases where QA equals 2 and 3, which data should a data user use?
9. Line 371-372: Same question as above.Citation: https://doi.org/10.5194/egusphere-2023-748-RC3 -
AC1: 'Reply on RC1', Ulla Wandinger, 10 Jul 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-748/egusphere-2023-748-AC1-supplement.pdf
-
AC1: 'Reply on RC1', Ulla Wandinger, 10 Jul 2023
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-748', Anonymous Referee #1, 17 May 2023
Accept as is
Citation: https://doi.org/10.5194/egusphere-2023-748-RC1 -
AC1: 'Reply on RC1', Ulla Wandinger, 10 Jul 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-748/egusphere-2023-748-AC1-supplement.pdf
-
AC1: 'Reply on RC1', Ulla Wandinger, 10 Jul 2023
-
RC2: 'Comment on egusphere-2023-748', Anonymous Referee #2, 19 May 2023
The paper describes the EarthCARE cloud top height and aerosol layer products (A-CTH, A-ALD). The paper is very well-written, logically organized, and the methods employed are sound. However, the motivation for this study was never quite clearly laid out in the manuscript. The authors also do mention a desire to maintain the heritage of the CALIPSO layer products, which is worthwhile. But why then develop an additional independent data products with independent methods when there already exists cloud and aerosol profiles products from ATLID (i.e. A-FM/APRO)? Layer products are indeed useful when it is more convenient to use layer data rather than more detailed profile data, but it seems more desirable to make the information provided by the layer product consistent with the profile product. That is: it would seem more prudent to derive the layer product from directly form the information given in the profile products rather developing a different algorithm.
While a flag is developed to alert a data user to such disagreement between these layers data products and their profile counterparts, how does one then decide which information is more reliable to use for their purpose? I'm concerned about the potential pitfalls of providing data users with 2 independent descriptions of cloud+aerosol locations and properties.
Other comments:line 108: why clear conditions only? One of strengths of lidars being able to provide aerosol information in the presence of clouds.
This layer information appears to be as a needed precursor to the MSI cloud and aerosol retrievals. But, in a similar vain to my comments above, why couldn't the profile version of the products be used for this purpose?
A ~10km average (i.e. 11 JSG pixels) seem insufficient to detect optically thinner layers as evident by the evident application of the algorithm to the Halifax aerosol scene. Why is 11 pixels chosen as the coarsest resolution? Are these undetected thin clouds/aerosols expected to impact the MSI retrievals?
For the test scenes, it be would be good to summarize the level of consistency between the (e.g. statistics of the level of consistency flag in
Figure 7)How sensitive are the results using the test scenes to the parameters chosen in Tables 1 and 2? Relatedly, have the authors thought about the process for optimizing these once EarthCARE is collecting real data?
Citation: https://doi.org/10.5194/egusphere-2023-748-RC2 -
AC1: 'Reply on RC1', Ulla Wandinger, 10 Jul 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-748/egusphere-2023-748-AC1-supplement.pdf
-
AC1: 'Reply on RC1', Ulla Wandinger, 10 Jul 2023
-
RC3: 'Comment on egusphere-2023-748', Anonymous Referee #3, 22 May 2023
This manuscript provides an introduction to the products of cloud top height and aerosol layer properties derived from EarthCARE lidar. Retrieval algorithms are discussed, and validation is carried out using model simulations. This study is of significant importance to the EarthCARE satellite mission and deserves documentation as it serves as a valuable resource for future data users, facilitating a better understanding of the data products and providing useful guidance. The manuscript is generally well-written, the methodology is sound, and the conclusions are solid. I recommend a minor revision prior to publication. Please find my detailed comments below:
1. While the manuscript provides a good discussion of the algorithm, it is not an Algorithm Theoretical Basis Document (ATBD). The objective of this paper could be better tied to the broader needs of the community. I believe it would be worthwhile to highlight the advantages and benefits of the EarthCARE lidar and the algorithm in the manuscript. Additionally, the paper could benefit from discussing what unique aspects of the products future data users can anticipate.
2. The manuscript contains numerous acronyms, which can become confusing. A table summarizing all acronyms in a single place would be appreciated.
3. I would appreciate a discussion on how the accuracy of the retrieval depends on the chosen configuration parameters.
4. Given that modeled cases are utilized to validate the algorithm, I would like to suggest performing a statistical performance analysis using a larger set of model outputs, as opposed to a limited number of cases.
5. Line 94: Can you explain the reason for choosing 11-pixel for this algorithm?
6. Line 108: Why only clear sky? There are two crucial scenarios that need to study the aerosol radiative effects, namely aerosols above low-level water clouds and aerosols beneath thin cirrus. These datasets are currently missing from existing satellite products.
7. Line 111: The assumption being made here is that the aerosol is vertically well-mixed within the boundary layer. Could you elaborate on the uncertainty associated with this assumption?
8. Line 293-295: In cases where QA equals 2 and 3, which data should a data user use?
9. Line 371-372: Same question as above.Citation: https://doi.org/10.5194/egusphere-2023-748-RC3 -
AC1: 'Reply on RC1', Ulla Wandinger, 10 Jul 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-748/egusphere-2023-748-AC1-supplement.pdf
-
AC1: 'Reply on RC1', Ulla Wandinger, 10 Jul 2023
Peer review completion
Journal article(s) based on this preprint
Data sets
EarthCARE level-2 demonstration products from simulated scenes Gerd-Jan van Zadelhoff, Howard W. Barker, Edward Baudrez, Sebastian Bley, Nicolas Clerbaux, Jason N. S. Cole, Jos de Kloe, Nicole Docter, Carlos Domenech, David P. Donovan, Jean-Louis Dufresne, Michael Eisinger, Juergen Fischer, Raquel García-Marañón, Moritz Haarig, Robin J. Hogan, Anja Hünerbein, Pavlos Kollias, Rob Koopman, Nils Madenach, Shannon L. Mason, Rene Preusker, Bernat Puigdomènech Treserras, Zhipeng Qu, Manuel Ruiz-Saldaña, Mark Shephard, Almudena Velázquez-Blazquez, Nadja Villefranque, Ulla Wandinger, Ping Wang, and Tobias Wehr https://doi.org/10.5281/zenodo.7311704
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Cited
Moritz Haarig
Holger Baars
David Donovan
Gerd-Jan van Zadelhoff
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(5826 KB) - Metadata XML