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https://doi.org/10.5194/egusphere-2024-358
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/egusphere-2024-358
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
08 Feb 2024
| 08 Feb 2024
Retrieval of stratospheric aerosol extinction coefficients from OMPS-LP measurements
Abstract. A new retrieval algorithm to obtain vertical profiles of the aerosol extinction coefficient from the measurements of the scattered solar light in the limb viewing geometry made by the OMPS-LP instrument is presented. The method employs the normalization of the limb radiances to the solar irradiance in contrast to the normalization by a limb measurement at an upper tangent height, which is used by most of the other published limb-scatter retrievals. The main advantage of this approach is a nearly complete elimination of the dependence of the retrieval results on the prior aerosol extinction profile used in the retrieval. This makes the retrieval well suitable to analyze the observation scenes with highly elevated aerosol plumes as occurred after the Hunga Tonga-Hunga Ha'apai volcanic eruption in January 2022. The results from the new approach were compared to independent data from SAGE III/ISS and OSIRIS. In general, an agreement within 25 % between the different data products was observed although larger differences were seen after very strong volcanic eruptions and wildfires. The new data product was used to investigate the evolution of the aerosol plume after the Hunga Tonga-Hunga Ha'apai volcanic eruption.
How to cite. Rozanov, A., Pohl, C., Arosio, C., Bourassa, A., Bramstedt, K., Malinina, E., Rieger, L., and Burrows, J. P.: Retrieval of stratospheric aerosol extinction coefficients from OMPS-LP measurements, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-358, 2024.
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RC1: 'Comment on egusphere-2024-358', Anonymous Referee #1, 20 May 2024
The manuscript “Retrieval of stratospheric aerosol extinction coefficients from OMPS-LP measurements” by Rozanov et al. presents a new retrieval algorithm to obtain vertical profiles of the aerosol extinction coefficient. The main claim of the paper is that by avoiding altitude normalization, the algorithm becomes almost completely independent of the “prior aerosol extinction profile.” However, in my view, the authors did not provide sufficient evidence to prove this point. Particularly, in Section 5, the authors wrote that uncertainties about the aerosol concentration at the normalization altitude would lead to a strong sensitivity to the a priori extinction profile across the entire vertical range. Figure 3 shows results for two algorithms (V1.0.9 and V2.1) and concludes that by removing altitude normalization in V2.1, the retrieved profiles become almost insensitive to a priori. However, I am afraid that the authors are comparing apples and oranges here. We (readers) do not know if the two algorithms use the same L1 data or different data because the differences in the magnitude of retrieved aerosol extinction coefficients are quite large between the two algorithms, as shown in Figure 5. The authors do not describe all the algorithmic differences between the two algorithms to convince the reader that the changes they see in Figure 3 are caused by the normalization at higher altitude.The authors listed three main reasons why altitude normalization can negatively affect aerosol retrievals: larger stray light at the normalization altitude, uncertainties about the aerosol amount at the normalization altitude (that comes from a priori), and scene reflectivity (albedo). I agree with all three points; however, I don’t understand how any of these factors can lead to a strong dependence on the a priori throughout the entire vertical range. To prove the claim, the authors perturbed a priori profiles by increasing them by a factor of 2 and 3 and ran retrievals using the two models. First of all, if the authors believe that it’s the uncertainties in aerosol concentration at the normalization altitude that affect aerosol retrievals below, then they should arbitrarily increase aerosol at the normalization altitude rather than the entire profile. The retrieval sensitivity to a priori can also be estimated using AKs (see Rodgers, 2000). The AKs for V2.1 are shown in Figure 2, but V1.0.9 AKs had not been demonstrated to readers. Can you please plot them as well? Can you estimate sensitivity to a priori using the equation (Rodgers et al., 2000) and check if it’s consistent with what you observe from direct perturbations of the a priori?Secondly, the authors claim that scene albedo R derived at 40 km depends on aerosol, which is true, but I am not sure how that can increase the sensitivity to the a priori aerosol. Since the background aerosol amount is negligibly small at 40.5 km, its contribution to R is quite small compared to the pure Rayleigh atmosphere. I agree that the change in R will affect aerosol retrievals, but I am not sure how that can increase the sensitivity to the a priori aerosol. The authors should provide evidence to support this claim.I believe the method proposed in this paper can be useful for aerosol retrievals in perturbed conditions like those after the Hunga eruption, when the aerosol at ~40 km was significantly different from the climatology. However, in my view, the paper needs to be substantially revised, and the authors have to provide more supporting evidence for their main claim.Major Comments:Title: The title of the paper is too vague and does not reflect the content of the paper. As the authors pointed out, there are multiple groups and multiple aerosol retrieval algorithms that use OMPS LP measurements to derive aerosol extinction. The title should be changed to reflect the paper’s content.Abstract, line 4: There is a statement in the paper, which is repeated multiple times, saying that the novelty of the presented algorithm is that “the method employs the normalization of the limb radiances to the solar irradiance in contrast to the normalization by a limb measurement at an upper tangent height, which is used by most of the other published limb-scatter retrievals.” A search in the literature reveals that, for example, NASA’s retrieval algorithm (Loughman et al., 2018; Chen et al., 2018; Taha et al., 2021) uses sun-normalized radiances to derive aerosol extinction. Indeed, the NASA algorithm requires the altitude normalization at higher altitudes, but it is incorrect to state that nobody uses sun-normalization.Abstract: A large fraction of the paper is dedicated to comparisons with other instruments (SAGE III and OSIRIS). The statement in the abstract declares that differences are mostly within 25%, but such agreement is only seen in a relatively narrow vertical range, and outside that range, the differences are much larger. In my view, the authors should clearly identify in the abstract the vertical and latitudinal ranges where the agreement is within the desired 25%.Page 2, lines 24-26: The authors stated that substantial ozone losses were observed after the 2020 Australian fires and the Hunga eruption and provided references. In my view, the words “significant losses” exaggerate the losses described in the cited studies. Instead of using the words “significant ozone losses,” the authors should quote numbers from the cited publications.Page 3, line 57: There is an extensive list of publications that estimate the SO2 amount injected by the Hunga eruption. It would be better to quote numbers rather than say “a significant amount.”Page 4, Section 3, line 115: Are you solving Equation 1 with respect to the initial guess or a priori profile? Is the first guess in your terminology the same as a priori?Page 4, line 116: By removing the altitude normalization, you need to accurately know the surface albedo. Can you reduce the number of iterations by retrieving reflectivity R0 at, say, 40 or 45 km first and use this as the initial guess for R?Page 5, Section 3, lines 26-28: It is not the normalization to solar radiances that makes retrievals more sensitive to upwelling radiances. It is the absence of the altitude normalization.Page 6, lines 170-173: The described convergence criteria are questionable and definitely are not optimal. The range between 15 and 28 km might be reasonable for the background aerosol conditions. However, for the case with a dense aerosol cloud like after the Hunga eruption, the line-of-sight optical depth becomes incredibly high. This means that the measurements at lower tangent points are not sensitive to changes at those altitudes, and the signal rather comes from upper levels that lie closer to the instrument. Under those conditions, instead of focusing on improving retrievals in places where the measurements are the most sensitive (based on K), the algorithm is pushed to retrieve hard in places with no sensitivity.Page 6, line 173: I am not sure that the algorithm with 100 iterations can be used in the operational environment. Can you plot a histogram showing the number of iterations under background conditions and under perturbed conditions (like volcanic eruptions or wildfires)?Page 10, lines 247-250: The measurement noise can be quite different between LP and SCIAMACHY. I would not extrapolate conclusions derived from the analysis of SCIAMACHY spectra to OMPS LP.Page 12, Figure 5: What do the horizontal green lines at ~9 km represent? Does it mean that positive differences for v1.09 switch to negative below 9 km? If I interpret the error bars correctly, the standard deviation for differences is larger than +/-100% at lower altitudes (depending on latitude zone). How meaningful are the comparisons with a standard deviation greater than100%?Page 12, line 275: Have you described the collocation criteria for comparisons with SAGE III?Page 14, Figure 7: Are you calculating zonal means from all available measurements for each instrument independently? If so, then the difference in the temporal and spatial sampling (particularly with SAGE III) can produce biases that are not accounted for.Page 14, lines 294-295 and Figure 7: OMPS LP aerosol retrievals at 869 nm were converted to 750 nm to compare with OSIRIS. Since this study validates OMPS LP retrievals, it would be better to run comparisons at the “native” wavelength and rather convert OSIRIS extinction to 869 nm.Page 15, lines 330-333: Why do you use 2022 data when you stated above that OSIRIS data quality degraded in 2022? Or is it a typo?Page 16, line 335: Both OSIRIS and LP have relatively dense sampling, so I am not sure what you meant here. Can you please elaborate on this?Page 16, line 336: I agree that the cloud correction is one of the many factors that contribute to reduced quality of aerosol data and larger differences in the troposphere, but I will not say that it is the only one.Multi-panel figures: Please add labels (a, b, c, etc.) on all figures that have multiple panels.Figure 10, legend: What do you mean by "Relative mean differences"? Do you calculate zonal means first and then calculate the difference between the two monthly zonal means? Then it should be "Relative differences." Otherwise, clarify that in the text.Section 7: There have been many publications in the last two years that describe the transport of volcanic aerosol after the Hunga eruption, which are not acknowledged here. Is there any reason for that? How do the conclusions of this study agree with previously published results?
Minor comments:
Page 2, line 46: it’s not clear from the context what “this range” refer to. It might be better to say “… to the aerosol at the normalization altitude”.
Page 2, line 46: It doesn’t sound right when you state that the knowledge is the major source of uncertainty. Perhaps, “the lack of knowledge” or “incomplete knowledge”.
Page 8, lines 213: should “for example”.
Page 8, line 214: should be “with the tangent point ground coordinates”
Page 8, line 216: should be “every third AK”
Page 11, line 258: the word “tangent” is used twice.
Citation: https://doi.org/10.5194/egusphere-2024-358-RC1 -
AC1: 'Reply on RC1', Alexei Rozanov, 15 Aug 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-358/egusphere-2024-358-AC1-supplement.pdf
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AC1: 'Reply on RC1', Alexei Rozanov, 15 Aug 2024
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RC2: 'Comment on egusphere-2024-358', Anonymous Referee #2, 10 Jun 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-358/egusphere-2024-358-RC2-supplement.pdf
-
AC2: 'Reply on RC2', Alexei Rozanov, 15 Aug 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-358/egusphere-2024-358-AC2-supplement.pdf
-
AC2: 'Reply on RC2', Alexei Rozanov, 15 Aug 2024
-
EC1: 'Comment on egusphere-2024-358', Omar Torres, 14 Jun 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-358/egusphere-2024-358-EC1-supplement.pdf
-
AC3: 'Reply on EC1', Alexei Rozanov, 15 Aug 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-358/egusphere-2024-358-AC3-supplement.pdf
-
AC3: 'Reply on EC1', Alexei Rozanov, 15 Aug 2024
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
-
RC1: 'Comment on egusphere-2024-358', Anonymous Referee #1, 20 May 2024
The manuscript “Retrieval of stratospheric aerosol extinction coefficients from OMPS-LP measurements” by Rozanov et al. presents a new retrieval algorithm to obtain vertical profiles of the aerosol extinction coefficient. The main claim of the paper is that by avoiding altitude normalization, the algorithm becomes almost completely independent of the “prior aerosol extinction profile.” However, in my view, the authors did not provide sufficient evidence to prove this point. Particularly, in Section 5, the authors wrote that uncertainties about the aerosol concentration at the normalization altitude would lead to a strong sensitivity to the a priori extinction profile across the entire vertical range. Figure 3 shows results for two algorithms (V1.0.9 and V2.1) and concludes that by removing altitude normalization in V2.1, the retrieved profiles become almost insensitive to a priori. However, I am afraid that the authors are comparing apples and oranges here. We (readers) do not know if the two algorithms use the same L1 data or different data because the differences in the magnitude of retrieved aerosol extinction coefficients are quite large between the two algorithms, as shown in Figure 5. The authors do not describe all the algorithmic differences between the two algorithms to convince the reader that the changes they see in Figure 3 are caused by the normalization at higher altitude.The authors listed three main reasons why altitude normalization can negatively affect aerosol retrievals: larger stray light at the normalization altitude, uncertainties about the aerosol amount at the normalization altitude (that comes from a priori), and scene reflectivity (albedo). I agree with all three points; however, I don’t understand how any of these factors can lead to a strong dependence on the a priori throughout the entire vertical range. To prove the claim, the authors perturbed a priori profiles by increasing them by a factor of 2 and 3 and ran retrievals using the two models. First of all, if the authors believe that it’s the uncertainties in aerosol concentration at the normalization altitude that affect aerosol retrievals below, then they should arbitrarily increase aerosol at the normalization altitude rather than the entire profile. The retrieval sensitivity to a priori can also be estimated using AKs (see Rodgers, 2000). The AKs for V2.1 are shown in Figure 2, but V1.0.9 AKs had not been demonstrated to readers. Can you please plot them as well? Can you estimate sensitivity to a priori using the equation (Rodgers et al., 2000) and check if it’s consistent with what you observe from direct perturbations of the a priori?Secondly, the authors claim that scene albedo R derived at 40 km depends on aerosol, which is true, but I am not sure how that can increase the sensitivity to the a priori aerosol. Since the background aerosol amount is negligibly small at 40.5 km, its contribution to R is quite small compared to the pure Rayleigh atmosphere. I agree that the change in R will affect aerosol retrievals, but I am not sure how that can increase the sensitivity to the a priori aerosol. The authors should provide evidence to support this claim.I believe the method proposed in this paper can be useful for aerosol retrievals in perturbed conditions like those after the Hunga eruption, when the aerosol at ~40 km was significantly different from the climatology. However, in my view, the paper needs to be substantially revised, and the authors have to provide more supporting evidence for their main claim.Major Comments:Title: The title of the paper is too vague and does not reflect the content of the paper. As the authors pointed out, there are multiple groups and multiple aerosol retrieval algorithms that use OMPS LP measurements to derive aerosol extinction. The title should be changed to reflect the paper’s content.Abstract, line 4: There is a statement in the paper, which is repeated multiple times, saying that the novelty of the presented algorithm is that “the method employs the normalization of the limb radiances to the solar irradiance in contrast to the normalization by a limb measurement at an upper tangent height, which is used by most of the other published limb-scatter retrievals.” A search in the literature reveals that, for example, NASA’s retrieval algorithm (Loughman et al., 2018; Chen et al., 2018; Taha et al., 2021) uses sun-normalized radiances to derive aerosol extinction. Indeed, the NASA algorithm requires the altitude normalization at higher altitudes, but it is incorrect to state that nobody uses sun-normalization.Abstract: A large fraction of the paper is dedicated to comparisons with other instruments (SAGE III and OSIRIS). The statement in the abstract declares that differences are mostly within 25%, but such agreement is only seen in a relatively narrow vertical range, and outside that range, the differences are much larger. In my view, the authors should clearly identify in the abstract the vertical and latitudinal ranges where the agreement is within the desired 25%.Page 2, lines 24-26: The authors stated that substantial ozone losses were observed after the 2020 Australian fires and the Hunga eruption and provided references. In my view, the words “significant losses” exaggerate the losses described in the cited studies. Instead of using the words “significant ozone losses,” the authors should quote numbers from the cited publications.Page 3, line 57: There is an extensive list of publications that estimate the SO2 amount injected by the Hunga eruption. It would be better to quote numbers rather than say “a significant amount.”Page 4, Section 3, line 115: Are you solving Equation 1 with respect to the initial guess or a priori profile? Is the first guess in your terminology the same as a priori?Page 4, line 116: By removing the altitude normalization, you need to accurately know the surface albedo. Can you reduce the number of iterations by retrieving reflectivity R0 at, say, 40 or 45 km first and use this as the initial guess for R?Page 5, Section 3, lines 26-28: It is not the normalization to solar radiances that makes retrievals more sensitive to upwelling radiances. It is the absence of the altitude normalization.Page 6, lines 170-173: The described convergence criteria are questionable and definitely are not optimal. The range between 15 and 28 km might be reasonable for the background aerosol conditions. However, for the case with a dense aerosol cloud like after the Hunga eruption, the line-of-sight optical depth becomes incredibly high. This means that the measurements at lower tangent points are not sensitive to changes at those altitudes, and the signal rather comes from upper levels that lie closer to the instrument. Under those conditions, instead of focusing on improving retrievals in places where the measurements are the most sensitive (based on K), the algorithm is pushed to retrieve hard in places with no sensitivity.Page 6, line 173: I am not sure that the algorithm with 100 iterations can be used in the operational environment. Can you plot a histogram showing the number of iterations under background conditions and under perturbed conditions (like volcanic eruptions or wildfires)?Page 10, lines 247-250: The measurement noise can be quite different between LP and SCIAMACHY. I would not extrapolate conclusions derived from the analysis of SCIAMACHY spectra to OMPS LP.Page 12, Figure 5: What do the horizontal green lines at ~9 km represent? Does it mean that positive differences for v1.09 switch to negative below 9 km? If I interpret the error bars correctly, the standard deviation for differences is larger than +/-100% at lower altitudes (depending on latitude zone). How meaningful are the comparisons with a standard deviation greater than100%?Page 12, line 275: Have you described the collocation criteria for comparisons with SAGE III?Page 14, Figure 7: Are you calculating zonal means from all available measurements for each instrument independently? If so, then the difference in the temporal and spatial sampling (particularly with SAGE III) can produce biases that are not accounted for.Page 14, lines 294-295 and Figure 7: OMPS LP aerosol retrievals at 869 nm were converted to 750 nm to compare with OSIRIS. Since this study validates OMPS LP retrievals, it would be better to run comparisons at the “native” wavelength and rather convert OSIRIS extinction to 869 nm.Page 15, lines 330-333: Why do you use 2022 data when you stated above that OSIRIS data quality degraded in 2022? Or is it a typo?Page 16, line 335: Both OSIRIS and LP have relatively dense sampling, so I am not sure what you meant here. Can you please elaborate on this?Page 16, line 336: I agree that the cloud correction is one of the many factors that contribute to reduced quality of aerosol data and larger differences in the troposphere, but I will not say that it is the only one.Multi-panel figures: Please add labels (a, b, c, etc.) on all figures that have multiple panels.Figure 10, legend: What do you mean by "Relative mean differences"? Do you calculate zonal means first and then calculate the difference between the two monthly zonal means? Then it should be "Relative differences." Otherwise, clarify that in the text.Section 7: There have been many publications in the last two years that describe the transport of volcanic aerosol after the Hunga eruption, which are not acknowledged here. Is there any reason for that? How do the conclusions of this study agree with previously published results?
Minor comments:
Page 2, line 46: it’s not clear from the context what “this range” refer to. It might be better to say “… to the aerosol at the normalization altitude”.
Page 2, line 46: It doesn’t sound right when you state that the knowledge is the major source of uncertainty. Perhaps, “the lack of knowledge” or “incomplete knowledge”.
Page 8, lines 213: should “for example”.
Page 8, line 214: should be “with the tangent point ground coordinates”
Page 8, line 216: should be “every third AK”
Page 11, line 258: the word “tangent” is used twice.
Citation: https://doi.org/10.5194/egusphere-2024-358-RC1 -
AC1: 'Reply on RC1', Alexei Rozanov, 15 Aug 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-358/egusphere-2024-358-AC1-supplement.pdf
-
AC1: 'Reply on RC1', Alexei Rozanov, 15 Aug 2024
-
RC2: 'Comment on egusphere-2024-358', Anonymous Referee #2, 10 Jun 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-358/egusphere-2024-358-RC2-supplement.pdf
-
AC2: 'Reply on RC2', Alexei Rozanov, 15 Aug 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-358/egusphere-2024-358-AC2-supplement.pdf
-
AC2: 'Reply on RC2', Alexei Rozanov, 15 Aug 2024
-
EC1: 'Comment on egusphere-2024-358', Omar Torres, 14 Jun 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-358/egusphere-2024-358-EC1-supplement.pdf
-
AC3: 'Reply on EC1', Alexei Rozanov, 15 Aug 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-358/egusphere-2024-358-AC3-supplement.pdf
-
AC3: 'Reply on EC1', Alexei Rozanov, 15 Aug 2024
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3 citations as recorded by crossref.
- CREST: a Climate Data Record of Stratospheric Aerosols V. Sofieva et al. 10.5194/essd-16-5227-2024
- Transport of the Hunga volcanic aerosols inferred from Himawari-8/9 limb measurements F. Prata 10.5194/amt-17-3751-2024
- An empirical characterization of the aerosol Ångström exponent interpolation bias using SAGE III/ISS data R. Damadeo et al. 10.5194/amt-17-3669-2024
Latest update: 18 Nov 2024
Alexei Rozanov
CORRESPONDING AUTHOR
Institute of Environmental Physics, University of Bremen, Germany
Christine Pohl
Institute of Environmental Physics, University of Bremen, Germany
Carlo Arosio
Institute of Environmental Physics, University of Bremen, Germany
Adam Bourassa
University of Saskatchewan, Canada
Klaus Bramstedt
Institute of Environmental Physics, University of Bremen, Germany
Elizaveta Malinina
Institute of Environmental Physics, University of Bremen, Germany
now at: Canadian Centre for Climate Modeling and Analysis (CCCma), Environment and Climate Change Canada (ECCC), Canada
Landon Rieger
University of Saskatchewan, Canada
John P. Burrows
Institute of Environmental Physics, University of Bremen, Germany
Short summary
We developed a new algorithm to retrieve vertical distributions of the aerosol extinction coefficient in the stratosphere. The algorithm is applied to measurements of the scattered solar light form the space borne OMPS-LP (Ozone Mapping and Profiler Suite-Limb Profiler) instrument. The retrieval results are compared to the data from other space borne instruments and used to investigate the evolution of the aerosol plume after the eruption of the Hunga Tonga-Hunga Ha'apai volcano in January 2022.
We developed a new algorithm to retrieve vertical distributions of the aerosol extinction...