the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
An Approach to Track Instrument Calibration and Produce Consistent Products with the Version-8 Total Column Ozone Algorithm (V8TOZ)
Abstract. The Ozone Mapping and Profiler Suite (OMPS) has been onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite since October 2011, and was followed by an OMPS on NOAA-20 (N20) in November 2017, as part of the US Joint Polar Satellite System (JPSS) program. The OMPS measurements are processed to yield various products of atmospheric composition data for near-real-time monitoring and off-line study, including retrievals of total column ozone (TCO) and an Ultraviolet absorbing aerosol index (AI) based on the version-8 total ozone (V8TOZ) algorithm. With the implementation of changes to employ a broadband channel approach in the NOAA OMPS V8TOZ, the retrieved TCO and AI products become more stable and consistent between S-NPP and N20. Two particular regions have been chosen for building soft-calibration adjustments for both OMPS S-NPP and N20, which force the V8TOZ retrievals to be in quite good agreement from both sensors with little change by seasons. However, bias analysis shows that some noticeable errors / differences still exist after soft-calibration, and those errors appear to be quite persistently associated with solar zenith angle (SZA) and satellite viewing angle (SVA) in the retrievals of TCO and AI for both OMPS S-NPP and N20. Comparisons of TCO and AI from NOAA OMPS retrievals with other products such as those from the Tropospheric Monitoring Instrument (TROPOMI) and the Earth Polychromatic Imaging Camera (EPIC), show that, although the sensor, algorithm and solar spectra are different among them, the overall retrievals from those products are quite similar and consistent.
-
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.
-
Preprint
(6825 KB)
-
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(6825 KB) - Metadata XML
- BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2022-1500', Anonymous Referee #1, 17 Mar 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2022-1500/egusphere-2022-1500-RC1-supplement.pdf
-
AC1: 'Reply on RC1', Zhihua Zhang, 13 Apr 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2022-1500/egusphere-2022-1500-AC1-supplement.pdf
-
AC1: 'Reply on RC1', Zhihua Zhang, 13 Apr 2023
-
RC2: 'Comment on egusphere-2022-1500', Anonymous Referee #2, 20 Mar 2023
General comments
I enjoyed reading this paper, as harmonization of datasets is an important aspect in intercomparison of measurments and the interpretation of trends in timeseries, for example related to climate aspects. More specific, the paper focuses on a softcalibration technique to harmonize the total ozone measurments of the S-NPP and N20 OMPS sensors.
Overall, the paper is well written, although also some questions arose while reading, as indicated below.
I agree to publication of this paper, if the authors attend to the specifics below.
Â
Specific comments:
Â
Throughout the manuscript
I have the impression that the included imagery suffers from insufficient resolution, something that should be easily remedied.
Â
1 Introduction
Overall a clearly written introduction, providing sufficient justification and background for the use of the V8TOZ algorithm and sufficient references to relevant literature. I would like to read a little more here, though, on the motivation of the study. Why is the development of a new sof-calibration scheme required? What is missing in existing schemes (NASA) or why can't those be applied? Little by little the answers are give elsewhere in the paper, but the motivation should already be clear here.
2. V8TOZ with a broader bandpass approach
The broadband approach is described convincingly and is later shown to reduce retrieval noise and product biases. In section 2.4, the broadband approach is tested on one month of V8TOZ runs. Any reason to specifically choose this month and year? Same question for data selection further on in the paper.
Line 204: see Fig. 3, left panel --> see Fig. 3, right panel.
Â
3. Soft-calibration for both OMPS S-NPP and N20.
In Section 3.1, it becomes clear that OMPS S-NPP V8TOZ retrieval results from NASA are used as reference data set. At the same time, it appears that the existing soft-calibation method developed at NASA cannot be applied to the NOAA datasets, because of different trreatment of the measurement data. This should be made clear earlier in the paper.
Line 287: "The reflecivity ftom the broadband approach is generally slghtly lower with less variation than the narrowband approach."
Line 294: agree --> agreement
Line 17: 0.3 --> 0.3%.
Â
4 Errors and uncertainties versus latitude.
In chapter 4, the authors show extensive tests and comparisons. I appreciate that they don't shy away from mentioning remaing uncertainties or lack of explanation of the origin of observed remaining biases.
Â
5 Comparison with other products
In the comparison of OMPS aerosol index and ozone column with those from other satellite sensors, it appears that ozone columns from NOAA OMPS show differences when compared to TROPOMI and EPIC. although suggestions are given to explain these differences, some uncertainty remains in these explanations (different factors contribute) and comparison with ground measurements for specific scenes woul smaybe be useful. I do not ask to ask the authors to add a full section on comparison with ground data, but literature may also provide some sources that may help explain the observed offsets. After all, NASA OMPS S-Npp data is taken as reference. is this data known to agree better with validation data than TROPOMI and EPIC?
Â
Â
Â
Â
ÂÂCitation: https://doi.org/10.5194/egusphere-2022-1500-RC2 -
AC2: 'Reply on RC2', Zhihua Zhang, 13 Apr 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2022-1500/egusphere-2022-1500-AC2-supplement.pdf
-
AC2: 'Reply on RC2', Zhihua Zhang, 13 Apr 2023
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2022-1500', Anonymous Referee #1, 17 Mar 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2022-1500/egusphere-2022-1500-RC1-supplement.pdf
-
AC1: 'Reply on RC1', Zhihua Zhang, 13 Apr 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2022-1500/egusphere-2022-1500-AC1-supplement.pdf
-
AC1: 'Reply on RC1', Zhihua Zhang, 13 Apr 2023
-
RC2: 'Comment on egusphere-2022-1500', Anonymous Referee #2, 20 Mar 2023
General comments
I enjoyed reading this paper, as harmonization of datasets is an important aspect in intercomparison of measurments and the interpretation of trends in timeseries, for example related to climate aspects. More specific, the paper focuses on a softcalibration technique to harmonize the total ozone measurments of the S-NPP and N20 OMPS sensors.
Overall, the paper is well written, although also some questions arose while reading, as indicated below.
I agree to publication of this paper, if the authors attend to the specifics below.
Â
Specific comments:
Â
Throughout the manuscript
I have the impression that the included imagery suffers from insufficient resolution, something that should be easily remedied.
Â
1 Introduction
Overall a clearly written introduction, providing sufficient justification and background for the use of the V8TOZ algorithm and sufficient references to relevant literature. I would like to read a little more here, though, on the motivation of the study. Why is the development of a new sof-calibration scheme required? What is missing in existing schemes (NASA) or why can't those be applied? Little by little the answers are give elsewhere in the paper, but the motivation should already be clear here.
2. V8TOZ with a broader bandpass approach
The broadband approach is described convincingly and is later shown to reduce retrieval noise and product biases. In section 2.4, the broadband approach is tested on one month of V8TOZ runs. Any reason to specifically choose this month and year? Same question for data selection further on in the paper.
Line 204: see Fig. 3, left panel --> see Fig. 3, right panel.
Â
3. Soft-calibration for both OMPS S-NPP and N20.
In Section 3.1, it becomes clear that OMPS S-NPP V8TOZ retrieval results from NASA are used as reference data set. At the same time, it appears that the existing soft-calibation method developed at NASA cannot be applied to the NOAA datasets, because of different trreatment of the measurement data. This should be made clear earlier in the paper.
Line 287: "The reflecivity ftom the broadband approach is generally slghtly lower with less variation than the narrowband approach."
Line 294: agree --> agreement
Line 17: 0.3 --> 0.3%.
Â
4 Errors and uncertainties versus latitude.
In chapter 4, the authors show extensive tests and comparisons. I appreciate that they don't shy away from mentioning remaing uncertainties or lack of explanation of the origin of observed remaining biases.
Â
5 Comparison with other products
In the comparison of OMPS aerosol index and ozone column with those from other satellite sensors, it appears that ozone columns from NOAA OMPS show differences when compared to TROPOMI and EPIC. although suggestions are given to explain these differences, some uncertainty remains in these explanations (different factors contribute) and comparison with ground measurements for specific scenes woul smaybe be useful. I do not ask to ask the authors to add a full section on comparison with ground data, but literature may also provide some sources that may help explain the observed offsets. After all, NASA OMPS S-Npp data is taken as reference. is this data known to agree better with validation data than TROPOMI and EPIC?
Â
Â
Â
Â
ÂÂCitation: https://doi.org/10.5194/egusphere-2022-1500-RC2 -
AC2: 'Reply on RC2', Zhihua Zhang, 13 Apr 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2022-1500/egusphere-2022-1500-AC2-supplement.pdf
-
AC2: 'Reply on RC2', Zhihua Zhang, 13 Apr 2023
Peer review completion
Journal article(s) based on this preprint
Viewed
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
183 | 62 | 17 | 262 | 6 | 6 |
- HTML: 183
- PDF: 62
- XML: 17
- Total: 262
- BibTeX: 6
- EndNote: 6
Viewed (geographical distribution)
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1
Zhihua Zhang
Jianguo Niu
Lawrence Flynn
Eric Beach
Trevor Beck
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(6825 KB) - Metadata XML