the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Improved CCD tropospheric ozone from S5P TROPOMI satellite data using local cloud fields
Abstract. We present the CHORA (Cloud Height Ozone Reference Algorithm) algorithm for retrieving tropospheric ozone columns from S5P/TROPOMI. The method uses a local cloud reference sector (CLC, CHORA Local Cloud) to determine the stratospheric (above cloud) column, which is subtracted from the total column in clear-sky scenes in the same zonal band to retrieve the tropospheric column. The standard CCD (Convective Cloud Differential) approach uses cloud data from the Pacific region (CPC, CHORA Pacific Cloud) instead. An important assumption for the standard method is the zonal invariance of stratospheric ozone. The local cloud approach is the first step to diminish this constraint in order to extend the CCD method to middle latitudes, where stratospheric ozone variability is larger. An iterative approach has been developed for the automatic selection of an optimal local cloud reference sector around each retrieval grid box varying longitudinally between ±5° and ±50° and latitudinally by ±1°. The optimised CLCT (CHORA-Local Cloud Theil-Sen algorithm) algorithm, a follow-up from CLC, employs a homogeneity criterion for total ozone from the cloud reference sector in order to overcome the inhomogeneities in stratospheric ozone. It directly estimates the above cloud column ozone for a common reference altitude of 270 hPa using the Theil-Sen regression. The latter allows combining the CCD method with the cloud slicing algorithm that retrieves upper tropospheric ozone volume mixing ratios. Monthly averaged Tropospheric Column Ozone (TCO) using the Pacific cloud reference sector (CPC) and local cloud reference sector (CLC, CLCT) have been determined over the tropics and subtropics (26° S–21° N) from TROPOMI for the time period from 2018 to 2022. The accuracy of the various methods was investigated by comparisons with collocated NASA/GSFC SHADOZ ozonesonde measurements and the ESA TROPOMI Level 2 tropospheric ozone product. At eleven out of twelve stations, tropospheric ozone columns using CLCT yield better agreement with ozonesondes than CPC. The overall statistical dispersion is effectively reduced from 4 DU (CPC) to 2 DU (CLCT). In the tropical region (20° S–20° N), CLCT shows a significantly lower overall mean bias and dispersion of -1±8 %, outperforming both CPC (12±9 %) and CCD-ESA (22±10 %). CLCT surpasses the ESA operational product, providing more accurate tropospheric ozone retrievals at eight out of nine stations in the tropics. For the Hilo station, with a larger stratospheric ozone variability due to its proximity to the subtropics, the bias of +25 % (CPC) is effectively reduced to -12 % (CLCT). Similarly, in the subtropics (Reunion, Irene, and Hanoi), the CLCT algorithm provides an improved overall bias and scatter (-11±8 %) compared to CPC (-17±13 %) with respect to sondes but the bias remains negative. The CLCT effectively reduces the impact of stratospheric ozone inhomogeneity, typically at higher latitudes. These results demonstrate the advantage of the local cloud reference sector in the subtropics. The algorithm, thereby, is an important basis for subsequent systematic applications in current and future missions of geostationary satellites, like GEMS (Geostationary Environment Monitoring Spectrometer, Korea), ESA Sentinel-4, and NASA TEMPO (Tropospheric Emissions: Monitoring of POllution) covering predominantly middle latitudes.
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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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Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-2825', Anonymous Referee #2, 12 Mar 2024
General comments
Satheesan et al. introduced a CCD-modified algorithm for retrieving tropospheric ozone columns from TROPOMI measurements. This study also includes validation efforts using independent ozonesonde reference datasets and comparisons with operational TROPOMI CCD products. The main difference of their algorithm to the standard CCD algorithm is in estimating the stratospheric columns above the convective clouds and adjusting the ozone amount between cloud height and 270 hPa. This study experiments the use of a local reference sector to broaden the application range of the CCD based method from the tropical region (20S-20N) to mid-latitudes, compared to the standard CCD method that use a fixed (pacific) reference sector assuming zonal invariance of the stratospheric ozone in the tropics. The findings hold significant scientific value for the space-borne atmospheric monitoring community and align well with the scope of AMT. However, the authors are requested to address the following scientific comments and revise the manuscript for its acceptance.
Specific comments
C1 This manuscript needs a substantial revision to clearly convey the similarities and differences among the presented algorithms. The four algorithms involved in this work is 4.1 CPC algorithm, 4.2 CLC algorithm, 4.3 CLCT algorithm as well as the standard CCD algorithm (3.2). The algorithm descriptions span from pages 5 to 11, including an extensive repetition of common processes shared across each algorithm. Moreover, it is inappropriate to treat them as independent algorithms for CPC, CLC, and CLCT, respectively, they should be specific option details in the process of the reference sector choice (pacific or local) and the adjustment schemes (climatological, regression).
C2 Revise the structures. My suggestion is
- data
- TROPOMI (bring here 2.1 and introduce the TROPOMI total ozone/cloud/CCD TCO products)
- ozonesonde
- Algorithms
First describe the general common process. And then specify implementation details in each section.
- standard CCD
- Authors’ algorithm
4 results
C3 5.1 Uncertainty Budget. The error budget estimation method needs to be improved. According to Equation 1, the uncertainty estimate is almost dependent on the number of samplings for each grid box. But, In the local reference sector process, the longitudinal range of the reference sector is expanded until the minimum of sampling encounters, affecting the inhomogeneity of the samplings. The error term to the inhomogeneity of the samplings caused by stratospheric variability and upwelling of the boundary layer into the upper troposphere, should be included.
C4. Section 5.2 should be significantly revised. It is not proper to deliver comparison results for each station. My suggestion is discussing the validation results, separately w.r.t 1) geophysical variables (e.g. total column ozone, cloud pressure, aerosol index) using all pairs from all stations (not each station) 2) seasonal comparison for maybe several sectors (e.g., pacific region, subtropical), 3) Figure 12 and Table 1 and a few stations from Figure 8 to summary the validation results.
C5. It is more interesting to see the comparison/evaluation results for ACCO with each meteorology against ozone sonde, rather than TCO.
Citation: https://doi.org/10.5194/egusphere-2023-2825-RC1 - AC2: 'Reply on RC1', Swathi Maratt Satheesan, 31 Jul 2024
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RC2: 'Comment on egusphere-2023-2825', Klaus-Peter Heue, 13 Mar 2024
Interesting ideas some more details might be added see detailed comments
- AC1: 'Reply on RC2', Swathi Maratt Satheesan, 31 Jul 2024
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CC1: 'Comment on egusphere-2023-2825', Owen Cooper, 28 Mar 2024
This comment can be found in the attached pdf.
- AC3: 'Reply on CC1', Swathi Maratt Satheesan, 31 Jul 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-2825', Anonymous Referee #2, 12 Mar 2024
General comments
Satheesan et al. introduced a CCD-modified algorithm for retrieving tropospheric ozone columns from TROPOMI measurements. This study also includes validation efforts using independent ozonesonde reference datasets and comparisons with operational TROPOMI CCD products. The main difference of their algorithm to the standard CCD algorithm is in estimating the stratospheric columns above the convective clouds and adjusting the ozone amount between cloud height and 270 hPa. This study experiments the use of a local reference sector to broaden the application range of the CCD based method from the tropical region (20S-20N) to mid-latitudes, compared to the standard CCD method that use a fixed (pacific) reference sector assuming zonal invariance of the stratospheric ozone in the tropics. The findings hold significant scientific value for the space-borne atmospheric monitoring community and align well with the scope of AMT. However, the authors are requested to address the following scientific comments and revise the manuscript for its acceptance.
Specific comments
C1 This manuscript needs a substantial revision to clearly convey the similarities and differences among the presented algorithms. The four algorithms involved in this work is 4.1 CPC algorithm, 4.2 CLC algorithm, 4.3 CLCT algorithm as well as the standard CCD algorithm (3.2). The algorithm descriptions span from pages 5 to 11, including an extensive repetition of common processes shared across each algorithm. Moreover, it is inappropriate to treat them as independent algorithms for CPC, CLC, and CLCT, respectively, they should be specific option details in the process of the reference sector choice (pacific or local) and the adjustment schemes (climatological, regression).
C2 Revise the structures. My suggestion is
- data
- TROPOMI (bring here 2.1 and introduce the TROPOMI total ozone/cloud/CCD TCO products)
- ozonesonde
- Algorithms
First describe the general common process. And then specify implementation details in each section.
- standard CCD
- Authors’ algorithm
4 results
C3 5.1 Uncertainty Budget. The error budget estimation method needs to be improved. According to Equation 1, the uncertainty estimate is almost dependent on the number of samplings for each grid box. But, In the local reference sector process, the longitudinal range of the reference sector is expanded until the minimum of sampling encounters, affecting the inhomogeneity of the samplings. The error term to the inhomogeneity of the samplings caused by stratospheric variability and upwelling of the boundary layer into the upper troposphere, should be included.
C4. Section 5.2 should be significantly revised. It is not proper to deliver comparison results for each station. My suggestion is discussing the validation results, separately w.r.t 1) geophysical variables (e.g. total column ozone, cloud pressure, aerosol index) using all pairs from all stations (not each station) 2) seasonal comparison for maybe several sectors (e.g., pacific region, subtropical), 3) Figure 12 and Table 1 and a few stations from Figure 8 to summary the validation results.
C5. It is more interesting to see the comparison/evaluation results for ACCO with each meteorology against ozone sonde, rather than TCO.
Citation: https://doi.org/10.5194/egusphere-2023-2825-RC1 - AC2: 'Reply on RC1', Swathi Maratt Satheesan, 31 Jul 2024
-
RC2: 'Comment on egusphere-2023-2825', Klaus-Peter Heue, 13 Mar 2024
Interesting ideas some more details might be added see detailed comments
- AC1: 'Reply on RC2', Swathi Maratt Satheesan, 31 Jul 2024
-
CC1: 'Comment on egusphere-2023-2825', Owen Cooper, 28 Mar 2024
This comment can be found in the attached pdf.
- AC3: 'Reply on CC1', Swathi Maratt Satheesan, 31 Jul 2024
Peer review completion
Journal article(s) based on this preprint
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Swathi Maratt Satheesan
Kai-Uwe Eichmann
John P. Burrows
Mark Weber
Ryan Stauffer
Anne M. Thompson
Debra Kollonige
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(4015 KB) - Metadata XML