the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Retrieval of greenhouse gases from GOSAT and greenhouse gases and carbon monoxide from GOSAT-2 using the FOCAL algorithm
- 1Institute of Environmental Physics, University of Bremen, FB 1, P.O. Box 330440, 28334 Bremen, Germany
- 2Earth Observation Science, University of Leicester, LE1 7RH, Leicester, UK
- 3National Centre for Earth Observation, University of Leicester, UK
- 4Japan Aerospace Exploration Agency (JAXA), 305-8505, Tsukuba, Japan
- 5National Institute for Environmental Studies (NIES), Onogawa 16-2, Tsukuba, Ibaraki 305-8506, Japan
- 6Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences, University of Wollongong NSW 2522 Australia
- 7Max Planck Institute for Biogeochemistry, 07745 Jena, Germany
- 8Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, 82234 Oberpfaffenhofen, Germany
- 9Ludwig-Maximilians-Universität München, Lehrstuhl für Physik der Atmosphäre, 80539 Munich, Germany
- 10Karlsruhe Institute of Technology, IMK-ASF, 76021 Karlsruhe, Germany
- 11Finnish Meteorological Institute, Space and Earth Observation Centre, Tähteläntie 62, 99600 Sodankylä, Finland
- 12Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, 230026 Hefei, China
- 13Global Atmosphere Watch Team, Innovative Meteorological Research Department, National Institute of Meteorological Sciences, 3, Seohobuk-ro, Seogwipo-si, Jeju-do, Republic of Korea
- 14National Institute of Water and Atmospheric Research Ltd (NIWA), Lauder, Private Bag 50061, Omakau 9352, New Zealand
- 15Karlsruhe Institute of Technology, IMK-IFU, 82467 Garmisch-Partenkirchen, Germany
- 16California Institute of Technology, Global Environmental Center, Pasadena, CA 91125, USA
- 17Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, Nicosia, Cyprus
- 18Royal Belgian Institute for Space Aeronomy (BIRA-IASB), 1180 Brussels, Belgium
- 19Department of Physics, University of Toronto, Toronto, ON, M5S 1A7, Canada
- 20Laboratoire d’Etudes du Rayonnement et de la Matière en Astrophysique et Atmosphères (LERMA-IPSL), Sorbonne Université, CNRS, Observatoire de Paris, PSL Université, 75005 Paris, France
- 21Deutscher Wetterdienst, Meteorological Observatory, 82383 Hohenpeissenberg, Germany
- 22Center of Marine Environmental Sciences (MARUM), University of Bremen, Germany
- 1Institute of Environmental Physics, University of Bremen, FB 1, P.O. Box 330440, 28334 Bremen, Germany
- 2Earth Observation Science, University of Leicester, LE1 7RH, Leicester, UK
- 3National Centre for Earth Observation, University of Leicester, UK
- 4Japan Aerospace Exploration Agency (JAXA), 305-8505, Tsukuba, Japan
- 5National Institute for Environmental Studies (NIES), Onogawa 16-2, Tsukuba, Ibaraki 305-8506, Japan
- 6Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences, University of Wollongong NSW 2522 Australia
- 7Max Planck Institute for Biogeochemistry, 07745 Jena, Germany
- 8Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, 82234 Oberpfaffenhofen, Germany
- 9Ludwig-Maximilians-Universität München, Lehrstuhl für Physik der Atmosphäre, 80539 Munich, Germany
- 10Karlsruhe Institute of Technology, IMK-ASF, 76021 Karlsruhe, Germany
- 11Finnish Meteorological Institute, Space and Earth Observation Centre, Tähteläntie 62, 99600 Sodankylä, Finland
- 12Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, 230026 Hefei, China
- 13Global Atmosphere Watch Team, Innovative Meteorological Research Department, National Institute of Meteorological Sciences, 3, Seohobuk-ro, Seogwipo-si, Jeju-do, Republic of Korea
- 14National Institute of Water and Atmospheric Research Ltd (NIWA), Lauder, Private Bag 50061, Omakau 9352, New Zealand
- 15Karlsruhe Institute of Technology, IMK-IFU, 82467 Garmisch-Partenkirchen, Germany
- 16California Institute of Technology, Global Environmental Center, Pasadena, CA 91125, USA
- 17Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, Nicosia, Cyprus
- 18Royal Belgian Institute for Space Aeronomy (BIRA-IASB), 1180 Brussels, Belgium
- 19Department of Physics, University of Toronto, Toronto, ON, M5S 1A7, Canada
- 20Laboratoire d’Etudes du Rayonnement et de la Matière en Astrophysique et Atmosphères (LERMA-IPSL), Sorbonne Université, CNRS, Observatoire de Paris, PSL Université, 75005 Paris, France
- 21Deutscher Wetterdienst, Meteorological Observatory, 82383 Hohenpeissenberg, Germany
- 22Center of Marine Environmental Sciences (MARUM), University of Bremen, Germany
Abstract. Recently, the Fast atmOspheric traCe gAs retrievaL (FOCAL) algorithm has been applied to measurements of the Greenhouse gases Observing SATellite (GOSAT) and its successor GOSAT-2. FOCAL has been originally developed for Orbiting Carbon Observatory-2 (OCO-2) retrievals with the focus on the derivation of carbon dioxide (XCO2). However, depending on the available spectral windows, FOCAL also successfully retrieves total column amounts for other atmospheric species. Here, we show new results from updated GOSAT and GOSAT-2 FOCAL retrievals. The main focus is placed on methane (XCH4; full physics and proxy product), water vapour (XH2O) and the relative ratio of semi-heavy water (HDO) to water vapour (δD). Due to the extended spectral range of GOSAT-2 it is also possible to derive information on carbon monoxide (XCO) and nitrous oxide (XN2O) for which we also show first results. We also present an update on XCO2 from both instruments.
Compared to the previous product version (v1), the number of valid XCO2 data could be significantly increased in the updated version (v3.0) by 50 % for GOSAT and about a factor of two for GOSAT-2. All FOCAL data products show reasonable spatial distribution and temporal variations. Comparisons with TCCON (Total Carbon Column Observing Network) result in station-to-station biases which are generally in line with the reported TCCON uncertainties.
With this updated version of the GOSAT-2 FOCAL data, we provide a first total column average XN2O product. Global XN2O maps show a gradient from the tropics to higher latitudes in the order of 15 ppb, which can be explained by variations in tropopause height. The new GOSAT-2 XN2O product compares well with TCCON. Its station-to-station variability is lower than 2 ppb, which is about the magnitude of the typical N2O variations close to the surface. However, both GOSAT-2 and TCCON measurements show that the seasonal variations in the total column average XN2O are in the order of 8 ppb peak-to-peak, which can be easily resolved by the GOSAT-2 FOCAL data.
Stefan Noël et al.
Status: closed
-
RC1: 'Comment on amt-2022-43', T. E. Taylor, 23 Mar 2022
Overall this manuscript provides an important contribution to the remote sensing of GHGs from space. I recommend that it be published after a number of minor revisions given in the attached marked-up PDF.
- AC1: 'Reply on RC1', Stefan Noël, 17 May 2022
-
RC2: 'Comment on amt-2022-43', Anonymous Referee #3, 24 Mar 2022
The updated FOCAL retrieval (v3) is presented in this paper. It can process GOSAT and GOSAT-2 data. It has improved capabilities, mostly bigger spatial coverage than its predecesors, new molecular species measured and new processing. It can measure CO2, CH4, H2O, HDO, CO and N2O.
The paper is well written and well presented, and, as such, deserves publsihing. Some minor comments would improve the readability of the paper.
Unfortunately, it has been written in a manner that serves solely as a reference, since most of the content are references to previous papers. It is therefore very dull to read and has very little "information" appart from some uncertainty figures, sepcially for someone outside of the field . Since the style of the paper cannot be modified substantitally because this would mean a huge effort, I suggest to include the following additions:
- It should be stated, in the abstract, the beggining and in section "3.2 Processing" whether the uncertainties of the retrievals are determined. A great emphasis is placed on the amounts derived, but very little in the uncertainties. Are the uncertainties for each individual "pixel" determined? Or can a global uncertainty figure be derived?
- In line with the previous statement, include a sentence or two describing, in general, the algorithm used for pre-processing, processing and post-processing. Is it something similar to a linear regression? Non-linear regression? Machine learning? Optimal estimation? Please include some phrases such that the reader does not need to read one or two other papers to understand in general terms how the retrieval works.
- In the conclusion, for a reader outside from this field, it is not known whether these retrievals will make a difference in the community or not. Do they satisfy the requirements to geographycally locate the sources and sinks of CO2? CH4? Do they satisfy some requirements that can be useful to the communitty? Can they be assimilated in an AC numerical model? If not, which requirements would be needed in future instruments? In summary, a paragraph to show that this work is useful for humanity and not just for the machines that are being fed the numbers.
- AC2: 'Reply on RC2', Stefan Noël, 17 May 2022
-
RC3: 'Comment on amt-2022-43', Anonymous Referee #2, 12 Apr 2022
This paper presents a new retrieval (FOCAL 3.0) for XCO2, XCH4, XH2O, XCO, HDO, and XN2O from GOSAT and GOSAT-2. It is exciting to see retrievals from GOSAT-2. The retrievals are validated following standard protocols. I was very interested by the scatter and temporal bias metrics relative to TCCON – they are not usually shown but I found them very instructive. I recommend publication in AMT but suggest that the authors consider the following comments:
- The Introduction advertises that comparisons with previous satellite products will be shown but I could not find these comparisons in the text.
- Equation (1) suggests that methane must be retrieved by the full-physics algorithm in order to derive a proxy estimate but that would erase much of the benefit of the proxy method in enabling successful retrievals when the full-physics method can’t.
- Gradients in Figures 2 and 3 are so washed out as to make the Figures useless.
- Line 390: ‘the data sets…are available from the authors’. That’s OK at the submission stage but won’t do at the publication stage. The data sets should be publicly posted.
- AC3: 'Reply on RC3', Stefan Noël, 17 May 2022
-
RC4: 'Comment on amt-2022-43', Anonymous Referee #4, 21 Apr 2022
This paper describes the new v3.0 FOCAL retrievals for GOSAT and GOSAT-2, used to retrieve XCO2, XCH4, XCO, XNO2, XH2O, and the relative ratio of semi-heavy water to water vapour. The paper describes the methods used in the retrievals and validates the new dataset against the TCCON network. Overall, the paper clearly describes the retrieval methods and demonstrates the value of the new data products. Therefore, I recommend publication, with several minor revisions based on the comments below.
Specific comments
- Title: Should the title list the species being retrieved?
- Abstract: Are the new FOCAL v3.0 datasets publicly available?
- Line 10: I found this paragraph a bit difficult to follow. For lines 10-11, do you mean something like this? "For XCO2, the new FOCAL retrieval (v3.0) significantly increases the number of valid XCO2 data compared with the previous FOCAL retrieval version (v1) by 50% for GOSAT and about a factor of two for GOSAT-2." Are "All FOCAL data products" in line 11 referring to all v3.0 data products?
- Line 165: For the filtering procedure - how do you ensure that real variability isn't accidently filtered out from the dataset?
- Line 216: Could you add a brief definition of the full physics vs proxy datasets for CH4 and explain why there are more data for the proxy products? Are the full physics and proxy comparable or do they have different applications/uncertainties?
- Line 252: Add a brief description of the CO2 timeseries to the text since this is also shown in the figure? Is the timeseries qualitatively in line with other versions of the CO2 retrieval? Other monitoring?
- Line 263: Is there also no temporal trend in delta_D? Is it expected that year-to-year variations for delta_D be larger?
- Line 287: Please add a bit more detail about the comparison quantities being calculated. Perhaps including formulae would be helpful. For example, how is the seasonal variation of the difference at each station being calculated?
- Figure 1: This figure takes a bit of effort to read. Is there a reason that the full timeseries is shown instead of, e.g., a summary of the count during the measurement period with all available datasets? If so, describe the timeseries more in the text. Perhaps it would be easier to read if colours were used consistently across figure panels and if the FOCAL data product was somehow distinguished from the other products (e.g., with a distinct colour choice, cross-hatching or something else?). In panel (d), could the FOCAL v1.0 and focal v3.0 XCO2 be put next to each other so that they can be more easily compared?
- Figures 6-10 are barely described in the text. Can these be moved into an appendix or the supplementary material? Also, please make font sizes bigger.
- Tables: There are a lot of tables included in the paper. Some of these are not referenced from anywhere in the text (Table 2, 4, 5). Are all tables needed in the main body of the text - if so add descriptive text. (Otherwise, could move to appendix or supplement)
Technical comments
- Line 266: Rephrase so that it is clear what XCO is similar to. E.g., "Across different latitudes, GOSAT-2 XCO shows similar values and seasonal variations, except in the southern hemisphere…"
- AC4: 'Reply on RC4', Stefan Noël, 17 May 2022
Status: closed
-
RC1: 'Comment on amt-2022-43', T. E. Taylor, 23 Mar 2022
Overall this manuscript provides an important contribution to the remote sensing of GHGs from space. I recommend that it be published after a number of minor revisions given in the attached marked-up PDF.
- AC1: 'Reply on RC1', Stefan Noël, 17 May 2022
-
RC2: 'Comment on amt-2022-43', Anonymous Referee #3, 24 Mar 2022
The updated FOCAL retrieval (v3) is presented in this paper. It can process GOSAT and GOSAT-2 data. It has improved capabilities, mostly bigger spatial coverage than its predecesors, new molecular species measured and new processing. It can measure CO2, CH4, H2O, HDO, CO and N2O.
The paper is well written and well presented, and, as such, deserves publsihing. Some minor comments would improve the readability of the paper.
Unfortunately, it has been written in a manner that serves solely as a reference, since most of the content are references to previous papers. It is therefore very dull to read and has very little "information" appart from some uncertainty figures, sepcially for someone outside of the field . Since the style of the paper cannot be modified substantitally because this would mean a huge effort, I suggest to include the following additions:
- It should be stated, in the abstract, the beggining and in section "3.2 Processing" whether the uncertainties of the retrievals are determined. A great emphasis is placed on the amounts derived, but very little in the uncertainties. Are the uncertainties for each individual "pixel" determined? Or can a global uncertainty figure be derived?
- In line with the previous statement, include a sentence or two describing, in general, the algorithm used for pre-processing, processing and post-processing. Is it something similar to a linear regression? Non-linear regression? Machine learning? Optimal estimation? Please include some phrases such that the reader does not need to read one or two other papers to understand in general terms how the retrieval works.
- In the conclusion, for a reader outside from this field, it is not known whether these retrievals will make a difference in the community or not. Do they satisfy the requirements to geographycally locate the sources and sinks of CO2? CH4? Do they satisfy some requirements that can be useful to the communitty? Can they be assimilated in an AC numerical model? If not, which requirements would be needed in future instruments? In summary, a paragraph to show that this work is useful for humanity and not just for the machines that are being fed the numbers.
- AC2: 'Reply on RC2', Stefan Noël, 17 May 2022
-
RC3: 'Comment on amt-2022-43', Anonymous Referee #2, 12 Apr 2022
This paper presents a new retrieval (FOCAL 3.0) for XCO2, XCH4, XH2O, XCO, HDO, and XN2O from GOSAT and GOSAT-2. It is exciting to see retrievals from GOSAT-2. The retrievals are validated following standard protocols. I was very interested by the scatter and temporal bias metrics relative to TCCON – they are not usually shown but I found them very instructive. I recommend publication in AMT but suggest that the authors consider the following comments:
- The Introduction advertises that comparisons with previous satellite products will be shown but I could not find these comparisons in the text.
- Equation (1) suggests that methane must be retrieved by the full-physics algorithm in order to derive a proxy estimate but that would erase much of the benefit of the proxy method in enabling successful retrievals when the full-physics method can’t.
- Gradients in Figures 2 and 3 are so washed out as to make the Figures useless.
- Line 390: ‘the data sets…are available from the authors’. That’s OK at the submission stage but won’t do at the publication stage. The data sets should be publicly posted.
- AC3: 'Reply on RC3', Stefan Noël, 17 May 2022
-
RC4: 'Comment on amt-2022-43', Anonymous Referee #4, 21 Apr 2022
This paper describes the new v3.0 FOCAL retrievals for GOSAT and GOSAT-2, used to retrieve XCO2, XCH4, XCO, XNO2, XH2O, and the relative ratio of semi-heavy water to water vapour. The paper describes the methods used in the retrievals and validates the new dataset against the TCCON network. Overall, the paper clearly describes the retrieval methods and demonstrates the value of the new data products. Therefore, I recommend publication, with several minor revisions based on the comments below.
Specific comments
- Title: Should the title list the species being retrieved?
- Abstract: Are the new FOCAL v3.0 datasets publicly available?
- Line 10: I found this paragraph a bit difficult to follow. For lines 10-11, do you mean something like this? "For XCO2, the new FOCAL retrieval (v3.0) significantly increases the number of valid XCO2 data compared with the previous FOCAL retrieval version (v1) by 50% for GOSAT and about a factor of two for GOSAT-2." Are "All FOCAL data products" in line 11 referring to all v3.0 data products?
- Line 165: For the filtering procedure - how do you ensure that real variability isn't accidently filtered out from the dataset?
- Line 216: Could you add a brief definition of the full physics vs proxy datasets for CH4 and explain why there are more data for the proxy products? Are the full physics and proxy comparable or do they have different applications/uncertainties?
- Line 252: Add a brief description of the CO2 timeseries to the text since this is also shown in the figure? Is the timeseries qualitatively in line with other versions of the CO2 retrieval? Other monitoring?
- Line 263: Is there also no temporal trend in delta_D? Is it expected that year-to-year variations for delta_D be larger?
- Line 287: Please add a bit more detail about the comparison quantities being calculated. Perhaps including formulae would be helpful. For example, how is the seasonal variation of the difference at each station being calculated?
- Figure 1: This figure takes a bit of effort to read. Is there a reason that the full timeseries is shown instead of, e.g., a summary of the count during the measurement period with all available datasets? If so, describe the timeseries more in the text. Perhaps it would be easier to read if colours were used consistently across figure panels and if the FOCAL data product was somehow distinguished from the other products (e.g., with a distinct colour choice, cross-hatching or something else?). In panel (d), could the FOCAL v1.0 and focal v3.0 XCO2 be put next to each other so that they can be more easily compared?
- Figures 6-10 are barely described in the text. Can these be moved into an appendix or the supplementary material? Also, please make font sizes bigger.
- Tables: There are a lot of tables included in the paper. Some of these are not referenced from anywhere in the text (Table 2, 4, 5). Are all tables needed in the main body of the text - if so add descriptive text. (Otherwise, could move to appendix or supplement)
Technical comments
- Line 266: Rephrase so that it is clear what XCO is similar to. E.g., "Across different latitudes, GOSAT-2 XCO shows similar values and seasonal variations, except in the southern hemisphere…"
- AC4: 'Reply on RC4', Stefan Noël, 17 May 2022
Stefan Noël et al.
Stefan Noël et al.
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 371 | 157 | 21 | 549 | 7 | 5 |
- HTML: 371
- PDF: 157
- XML: 21
- Total: 549
- BibTeX: 7
- EndNote: 5
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1