the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 25 Mar 2024
Evaluating CHASER V4.0 global formaldehyde (HCHO) simulations using satellite, aircraft, and ground-based remote sensing observations
Abstract. Formaldehyde (HCHO), a precursor to tropospheric ozone, is an important tracer of volatile organic compounds (VOCs) in the atmosphere. Two years of HCHO simulations obtained from the global chemistry transport model CHASER at a horizontal resolution of 2.8° × 2.8° have been evaluated using observations from the Tropospheric Ozone Monitoring Experiment (TROPOMI), Atmospheric Tomography Mission (ATom), and multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations. CHASER reproduced the observed global HCHO spatial distribution with a spatial correlation (r) of 0.93 and a negative bias of 7 %. The model showed good capability for reproducing the observed magnitude of the HCHO seasonality in different regions, including the background conditions. The discrepancies between the model and satellite in the Asian regions were related mainly to the underestimated and missing anthropogenic emission inventories. TROPOMI's finer spatial resolution than that of the Ozone Monitoring Experiment (OMI) sensor reduced the global model–satellite root-mean-square-error (RMSE) by 20 %. The OMI and TROPOMI observed seasonal variations in HCHO abundances were consistent. However, the simulated seasonality showed better agreement with TROPOMI in most regions. The simulated HCHO and isoprene profiles correlated strongly (R = 0.81) with the ATom observations. CHASER overestimated HCHO mixing ratios over dense vegetation areas in South America and the remote Pacific (background condition) regions, mainly within the planetary boundary layer (< 2 km). The simulated temporal (daily and diurnal) variations in the HCHO mixing ratio showed good congruence with the MAX-DOAS observations and agreed within the 1-sigma standard deviation of the observed values.
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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.
Journal article(s) based on this preprint
Interactive discussion
Status: closed
-
CEC1: 'Comment on egusphere-2024-734', Juan Antonio Añel, 28 Mar 2024
Dear authors,
Unfortunately, after checking your manuscript, it has come to our attention that it does not comply with our "Code and Data Policy".
https://www.geoscientific-model-development.net/policies/code_and_data_policy.htmlIn your manuscript, the "Code Availability" section says that the code relevant for your manuscript is only available under request to authors. The policy of Geosc. Model Dev. (which you should have read and complied with before submitting your manuscript) is very strict and clear, all the code and data relevant for a manuscript must be available in a public repository of the ones listed in our policy before submission.
Therefore, if you do not fix promptly this problem, we will reject your manuscript for publication in our journal. I should note that, given this lack of compliance with our policy, your manuscript should not have been accepted in Discussions.
Therefore, please, publish your code and in one of the appropriate repositories, and reply to this comment with the relevant information (link and DOI). This includes the MAX-DOAS data.
Also, you must include in a potentially reviewed version of your manuscript the modified 'Code Availability' and 'Data Availability' sections, with links and DOIs.
Juan A. Añel
Geosci. Model Dev. Executive EditorCitation: https://doi.org/10.5194/egusphere-2024-734-CEC1 -
AC1: 'Reply on CEC1', H.M.S. Hoque, 29 Mar 2024
Dear Chief Editor,
Thank you very much for pointing out the issue. As the corresponding author, I take responsibility for the unintentional mistake. The model source code is accessible through https://zenodo.org/records/10892945 (Sudo et al., 2024), and the MAX-DOAS data is accessible through https://zenodo.org/records/10052384 (Hoque et al., 2024). Here is the revised code and data availability statement, which will be included in the revised version of the manuscript.
Code availability: The CHASER source code needed to reproduce the simulations in this work is available from the repository at https://zenodo.org/records/10892945 (Sudo et al., 2024).
Data availability: The processed model output and observational datasets needed to reproduce the results are available from the repository at https://zenodo.org/records/10052384 (Hoque et al., 2024). The MAX-DOAS profile and column data provided by Dr. Hitoshi Irie can be accessed from the repository(i.e., Hoque et al., 2024). TROPOMI (https://scihub.copernicus.eu/dhus/#/home, last access: 01 July 2023; De Smedt et al., 2021), OMI BIRA product, (https://www.temis.nl/qa4ecv/hcho/hcho_omi.php, last access: 01 July 2023; De Smedt et al., 2021) and ATom(https://daac.ornl.gov/ATOM/guides/ATom_nav.html, last access: 01 July 2023; Wofsy et al., 2018) data were obtained from the respective websites.
Reference:
Hoque, H. M. S., Sudo, K., and Irie, H., Model and observational datasets used for evaluating CHASER simulated formaldehyde (HCHO) abundances in 2019 and 2020. [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.10052384, 2024
Sudo, K.: Evaluating CHASER V4.0 global formaldehyde (HCHO) simulations using satellite, aircraft, and ground-based remote sensing observations.[Dataset].Zenodo https://zenodo.org/records/10892945
Kind Regards,
Syedul Hoque
Citation: https://doi.org/10.5194/egusphere-2024-734-AC1
-
AC1: 'Reply on CEC1', H.M.S. Hoque, 29 Mar 2024
-
RC1: 'Comment on egusphere-2024-734', Anonymous Referee #1, 15 Apr 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-734/egusphere-2024-734-RC1-supplement.pdf
- AC2: 'Reply on RC1', H.M.S. Hoque, 27 May 2024
-
RC2: 'Comment on egusphere-2024-734', Anonymous Referee #2, 29 Apr 2024
I trust this meassage finds you in good health. I am writing to offer my review of your article titled "Evaluating CHASER V4.0 global formaldehyde (HCHO) simulations using satellite, aircraft, and ground-based remote sensing observations" After a thorough evaluation of your research, I would like to extend my appreciation for the valuable contributions your work brings to the field.
There are some areas where minor enhancements could be made to elevate the clarity and coherence of the text. I would like to highlight these areas for your consideration:
Line 70: Any result or outcome that reflects that "good agreement"?
Line 143: Reprocessed and Offline TROPOMI products are different datasets. Please provide more detail about how and when each one is used.
174: Typo: "2.2" where it should read "2.3".
190: 2018 is out of the original study period (2019-2020). Please clarify why this year was chosen.
194-196: Typo: "TOGO" where it should read "TOGA" (Trace Organic Gas Analyzer).
201: Why were those specific locations chosen? Please provide more detail about that decision.
208: Typo: "Kasugai" where it should read "Kasuga".
257: Figure 1 is a valuable result and should appear in a larger size. With the current layout, the visualization is very difficult.
279: Figure 2 and similar ones: The temporal axis should specifically detail the study period, indicating whether it represents an average of both study years (2019-2020).
467: Typo: "Fig. ", without a number.
489: Please place the MBE values always in the same position in the graphs.
725: THat is still a high negative bias. Any further possible reasons for this result?
756: TROPOMI spatial resolution is 3.5 x 5.5 km2. Would there be any chance to perform this comparison at higher resolution instead of 200 km spatial averaging?
I would like to extend my congratulations to all the authors of this paper and wish them luck in future research endeavors.
Citation: https://doi.org/10.5194/egusphere-2024-734-RC2 - AC3: 'Reply on RC2', H.M.S. Hoque, 27 May 2024
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RC3: 'Comment on egusphere-2024-734', Narendra Ojha, 05 May 2024
In this study, Hoque et al. have evaluated the global distribution of formaldehyde (HCHO) simulated by CHASER v4.0 model against satellite, aircraft, and ground-based observations. Studies evaluating the global distribution of volatile organic compounds (VOCs) from models have been limited, and observations from space have the potential to help filling this gap. The investigations presented here add new insights, nevertheless, the manuscript in its current form has some limitations.
The authors have already published a paper on the global distribution of HCHO from the CHASER model comparing with satellite data and MAX DOAS [Hoque et al., Atmos. Chem. Phys., 2022]. Sensitivity simulations analyzing the roles of different emissions have also been published there. In this case, a clear and detailed discussion is required (at the end of the introduction) on the main findings of that paper, the research gap, and the novelty of this new study.
Abstract: l.19: “CHASER reproduced the observed….”, which observational data you are referring to?
Introduction
“ozone production regime can be determined”. In this context, you are referring to your past study. References where this type of approach was proposed [Martin et al., GRL, 2004] and later applied [Duncan et al., Atmos. Environ., 2010] should also be cited. Additionally, l.57-58: Several satellite-based observations have been used to evaluate the model simulation of HCHO by Chutia et al., [Environ. Poll., 2019]
l.59-65: I agree that higher resolution TROPOMI may provide new features at finer resolution (3.5 km x 5.5 km). But how does it help your study running model at roughly 300 km x 300 km? Satellite data also seems to be averaged to the same grid resolution as the model, although that is not described in detail.
l.72-74: Mention what has been learned from these studies, possibly the quantitative role of anthropogenic emissions.
Section 2: Model
Anthropogenic emission is representative of which year. How has it been varied for different simulation years (2019, 2020)?
l.111-112- Seems ambiguous. The reanalysis data might not have provided an emission inventory. Maybe there is some inventory from the same or similar project.
l.113- The VISIT model is used here for estimating the flux of biogenic VOCs. How do these estimates compare to other widely applied MEGAN model (Guenther et al., Atmos. Chem. Phys., 2006) based inventories? ECMWF’s CAMS has made freely available inventory for biogenic emissions, which may be used for comparison.
Table 1: Some simulations are missing from this list, like in which biogenic / biomass-burning is switched OFF.
l.196: Check and correct “TOGO” to “TOGA”
Results
Results from two different years appear identical in Figure 1. In the text also, there is no significant discussion on interannual differences. Values of correlation and RMSE have turned out to be the same between the analysis for 2 years separately. I suggest combining and discussing averages of both years for better statistics and reducing extra figures. This will further make this analysis consistent with follow-up results (e.g., Figures 2, 3), where mean is presented instead of year-wise segregation. The size of the figures can be enhanced.
Figure 2 and other results: you are referring to different regions of the world. These need to be marked clearly on the global distribution map (Figure 1). Make bigger figures and define the regions on them.
l.293 (and throughout the manuscript), be careful to always mention if you are referring to “spatial” or “temporal” correlations while reporting r values.
l.300-301: This needs some supporting analysis/discussions. Either compare the emission inventory used here with other estimates or discuss if the model is underestimating particularly near urban centers (so to attribute to anthropogenic) but performing better in remote / vegetated areas.
Table 3 and other places: Are the temporal correlations derived from the mean seasonal cycle (12 points)? It is advisable to use all data (daily values over 2 years) to comment on temporal correlations. Or to discuss both ways. This is a “model evaluation paper” and these details are important.
Table 4 and l.450: here also, clearly write if these are spatial correlations, seasonal (or daily). Check and make this aspect clear throughout the manuscript.
l.471-472: here also check from MEGAN model-based emissions.
Figure 5: I did not get the rationale behind enhancing anthropogenic emissions by a factor of 3. While HCHO was underestimated in reference simulation, now with this change the levels are equally (or more) overestimated over China, US, Africa, America (also see table 5). What has been achieved in terms of model performance?l.503-504: No, the MBE values have increased! Check and revise/strengthen this whole section l.503-518. Also, reconsider tuning the simulation design itself (in place of 3 times more emissions)
Section 3.4: This is an important aspect. Errors in the NOx emissions could have impacted model performance, especially in regions like South and Southeast Asia where inventories have greater uncertainties. Your simulations show that the model driven by older inventory shows lower bias in HCHO. Do you conclude that NOx emissions are overestimated in the new inventory? I did not find a clear assessment out of this important exercise.
Tables and figures coming afterward often has data shown in previous figures and tables. Review them carefully and combine them whenever possible. Like, instead of comparing 1 simulation then another, you may put them in same table as reference, simulation1 and 2;
CHASER and TROPOMI are already compared (Section 3.1). Then there is an extra section comparing CHASER, TROPMI with OMI. Better to combine and strengthen the discussion.
Fig 8: When emission is increased (OLNE), why HCHO is reduced over Chiba and Kasuga, what is the underlying chemistry?
Outside Japan also, there have been MAX-DOAS measurements. This paper being a global model evaluation, comparison over other regions of the world should also be added. If systematic data is not available, mean values may be compared (see Table 2 of Oomen et al., Atmos. Chem. Phys., 2024). Authors themselves have also published observations from another station in South Asia [Hoque et al., SOLA, 2018]
Minor comments
Check the consistency of r values between l.352 and in Table 3.
The data selection criteria for TROPOMI has not been discussed.
Line 387, line no. 467 - Figure no. is missing
In Figure S3, the correlation between TROPOMI and CHASER HCHO columns is marked as r=1 (blue text).
Figure numbering should be corrected. There is no figure 4.
Table 7 , last column name should have been ‘r-value (CHASER vs. OMI)’
Line 781, slope values inconsistent with the slope in figure 9.
References
Chutia, L., N. Ojha, Imran A. Girach, Lokesh K. Sahu, Leonardo M.A. Alvarado, John P. Burrows, Binita Pathak, Pradip Kumar Bhuyan, Distribution of volatile organic compounds over Indian subcontinent during winter: WRF-chem simulation versus observations, Environmental Pollution, Volume 252, Part A, 2019, Pages 256-269, ISSN 0269-7491, https://doi.org/10.1016/j.envpol.2019.05.097.
Duncan, B. N., Y. Yoshida, J.R. Olson, S. Sillman, R.V. Martin, L. Lamsal, Y. Hu, K.E. Pickering, C. Retscher, D.J. Allen, J.H. Crawford, Application of OMI observations to a space-based indicator of NOx and VOC controls on surface ozone formation, Atmos. Environ., 44 (18) (2010), pp. 2213-2223, 10.1016/j.atmosenv.2010.03.010.
Guenther, A., T. Karl, P. Harley, C. Wiedinmyer, P. Palmer, and C. Geron, Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature), Atmos. Chem Phys., 6, 3181-3210, 2006.
Hoque, H. M. S., Sudo, K., Irie, H., Damiani, A., Naja, M., and Fatmi, A. M.: Multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations of formaldehyde and nitrogen dioxide at three sites in Asia and comparison with the global chemistry transport model CHASER, Atmos. Chem. Phys., 22, 12559–12589, https://doi.org/10.5194/acp-22-12559-2022, 2022
Martin, R. V., A.M. Fiore, A. Van Donkelaar, Space-based diagnosis of surface ozone sensitivity to anthropogenic emissions, Geophys. Res. Lett., 31 (6) (2004), 10.1029/2004gl019416.
Oomen, G.-M., Müller, J.-F., Stavrakou, T., De Smedt, I., Blumenstock, T., Kivi, R., Makarova, M., Palm, M., Röhling, A., Té, Y., Vigouroux, C., Friedrich, M. M., Frieß, U., Hendrick, F., Merlaud, A., Piters, A., Richter, A., Van Roozendael, M., and Wagner, T.: Weekly derived top-down volatile-organic-compound fluxes over Europe from TROPOMI HCHO data from 2018 to 2021, Atmos. Chem. Phys., 24, 449–474, https://doi.org/10.5194/acp-24-449-2024, 2024.
Citation: https://doi.org/10.5194/egusphere-2024-734-RC3 - AC4: 'Reply on RC3', H.M.S. Hoque, 27 May 2024
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RC4: 'Comment on egusphere-2024-734', Anonymous Referee #4, 20 May 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-734/egusphere-2024-734-RC4-supplement.pdf
- AC5: 'Reply on RC4', H.M.S. Hoque, 27 May 2024
Interactive discussion
Status: closed
-
CEC1: 'Comment on egusphere-2024-734', Juan Antonio Añel, 28 Mar 2024
Dear authors,
Unfortunately, after checking your manuscript, it has come to our attention that it does not comply with our "Code and Data Policy".
https://www.geoscientific-model-development.net/policies/code_and_data_policy.htmlIn your manuscript, the "Code Availability" section says that the code relevant for your manuscript is only available under request to authors. The policy of Geosc. Model Dev. (which you should have read and complied with before submitting your manuscript) is very strict and clear, all the code and data relevant for a manuscript must be available in a public repository of the ones listed in our policy before submission.
Therefore, if you do not fix promptly this problem, we will reject your manuscript for publication in our journal. I should note that, given this lack of compliance with our policy, your manuscript should not have been accepted in Discussions.
Therefore, please, publish your code and in one of the appropriate repositories, and reply to this comment with the relevant information (link and DOI). This includes the MAX-DOAS data.
Also, you must include in a potentially reviewed version of your manuscript the modified 'Code Availability' and 'Data Availability' sections, with links and DOIs.
Juan A. Añel
Geosci. Model Dev. Executive EditorCitation: https://doi.org/10.5194/egusphere-2024-734-CEC1 -
AC1: 'Reply on CEC1', H.M.S. Hoque, 29 Mar 2024
Dear Chief Editor,
Thank you very much for pointing out the issue. As the corresponding author, I take responsibility for the unintentional mistake. The model source code is accessible through https://zenodo.org/records/10892945 (Sudo et al., 2024), and the MAX-DOAS data is accessible through https://zenodo.org/records/10052384 (Hoque et al., 2024). Here is the revised code and data availability statement, which will be included in the revised version of the manuscript.
Code availability: The CHASER source code needed to reproduce the simulations in this work is available from the repository at https://zenodo.org/records/10892945 (Sudo et al., 2024).
Data availability: The processed model output and observational datasets needed to reproduce the results are available from the repository at https://zenodo.org/records/10052384 (Hoque et al., 2024). The MAX-DOAS profile and column data provided by Dr. Hitoshi Irie can be accessed from the repository(i.e., Hoque et al., 2024). TROPOMI (https://scihub.copernicus.eu/dhus/#/home, last access: 01 July 2023; De Smedt et al., 2021), OMI BIRA product, (https://www.temis.nl/qa4ecv/hcho/hcho_omi.php, last access: 01 July 2023; De Smedt et al., 2021) and ATom(https://daac.ornl.gov/ATOM/guides/ATom_nav.html, last access: 01 July 2023; Wofsy et al., 2018) data were obtained from the respective websites.
Reference:
Hoque, H. M. S., Sudo, K., and Irie, H., Model and observational datasets used for evaluating CHASER simulated formaldehyde (HCHO) abundances in 2019 and 2020. [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.10052384, 2024
Sudo, K.: Evaluating CHASER V4.0 global formaldehyde (HCHO) simulations using satellite, aircraft, and ground-based remote sensing observations.[Dataset].Zenodo https://zenodo.org/records/10892945
Kind Regards,
Syedul Hoque
Citation: https://doi.org/10.5194/egusphere-2024-734-AC1
-
AC1: 'Reply on CEC1', H.M.S. Hoque, 29 Mar 2024
-
RC1: 'Comment on egusphere-2024-734', Anonymous Referee #1, 15 Apr 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-734/egusphere-2024-734-RC1-supplement.pdf
- AC2: 'Reply on RC1', H.M.S. Hoque, 27 May 2024
-
RC2: 'Comment on egusphere-2024-734', Anonymous Referee #2, 29 Apr 2024
I trust this meassage finds you in good health. I am writing to offer my review of your article titled "Evaluating CHASER V4.0 global formaldehyde (HCHO) simulations using satellite, aircraft, and ground-based remote sensing observations" After a thorough evaluation of your research, I would like to extend my appreciation for the valuable contributions your work brings to the field.
There are some areas where minor enhancements could be made to elevate the clarity and coherence of the text. I would like to highlight these areas for your consideration:
Line 70: Any result or outcome that reflects that "good agreement"?
Line 143: Reprocessed and Offline TROPOMI products are different datasets. Please provide more detail about how and when each one is used.
174: Typo: "2.2" where it should read "2.3".
190: 2018 is out of the original study period (2019-2020). Please clarify why this year was chosen.
194-196: Typo: "TOGO" where it should read "TOGA" (Trace Organic Gas Analyzer).
201: Why were those specific locations chosen? Please provide more detail about that decision.
208: Typo: "Kasugai" where it should read "Kasuga".
257: Figure 1 is a valuable result and should appear in a larger size. With the current layout, the visualization is very difficult.
279: Figure 2 and similar ones: The temporal axis should specifically detail the study period, indicating whether it represents an average of both study years (2019-2020).
467: Typo: "Fig. ", without a number.
489: Please place the MBE values always in the same position in the graphs.
725: THat is still a high negative bias. Any further possible reasons for this result?
756: TROPOMI spatial resolution is 3.5 x 5.5 km2. Would there be any chance to perform this comparison at higher resolution instead of 200 km spatial averaging?
I would like to extend my congratulations to all the authors of this paper and wish them luck in future research endeavors.
Citation: https://doi.org/10.5194/egusphere-2024-734-RC2 - AC3: 'Reply on RC2', H.M.S. Hoque, 27 May 2024
-
RC3: 'Comment on egusphere-2024-734', Narendra Ojha, 05 May 2024
In this study, Hoque et al. have evaluated the global distribution of formaldehyde (HCHO) simulated by CHASER v4.0 model against satellite, aircraft, and ground-based observations. Studies evaluating the global distribution of volatile organic compounds (VOCs) from models have been limited, and observations from space have the potential to help filling this gap. The investigations presented here add new insights, nevertheless, the manuscript in its current form has some limitations.
The authors have already published a paper on the global distribution of HCHO from the CHASER model comparing with satellite data and MAX DOAS [Hoque et al., Atmos. Chem. Phys., 2022]. Sensitivity simulations analyzing the roles of different emissions have also been published there. In this case, a clear and detailed discussion is required (at the end of the introduction) on the main findings of that paper, the research gap, and the novelty of this new study.
Abstract: l.19: “CHASER reproduced the observed….”, which observational data you are referring to?
Introduction
“ozone production regime can be determined”. In this context, you are referring to your past study. References where this type of approach was proposed [Martin et al., GRL, 2004] and later applied [Duncan et al., Atmos. Environ., 2010] should also be cited. Additionally, l.57-58: Several satellite-based observations have been used to evaluate the model simulation of HCHO by Chutia et al., [Environ. Poll., 2019]
l.59-65: I agree that higher resolution TROPOMI may provide new features at finer resolution (3.5 km x 5.5 km). But how does it help your study running model at roughly 300 km x 300 km? Satellite data also seems to be averaged to the same grid resolution as the model, although that is not described in detail.
l.72-74: Mention what has been learned from these studies, possibly the quantitative role of anthropogenic emissions.
Section 2: Model
Anthropogenic emission is representative of which year. How has it been varied for different simulation years (2019, 2020)?
l.111-112- Seems ambiguous. The reanalysis data might not have provided an emission inventory. Maybe there is some inventory from the same or similar project.
l.113- The VISIT model is used here for estimating the flux of biogenic VOCs. How do these estimates compare to other widely applied MEGAN model (Guenther et al., Atmos. Chem. Phys., 2006) based inventories? ECMWF’s CAMS has made freely available inventory for biogenic emissions, which may be used for comparison.
Table 1: Some simulations are missing from this list, like in which biogenic / biomass-burning is switched OFF.
l.196: Check and correct “TOGO” to “TOGA”
Results
Results from two different years appear identical in Figure 1. In the text also, there is no significant discussion on interannual differences. Values of correlation and RMSE have turned out to be the same between the analysis for 2 years separately. I suggest combining and discussing averages of both years for better statistics and reducing extra figures. This will further make this analysis consistent with follow-up results (e.g., Figures 2, 3), where mean is presented instead of year-wise segregation. The size of the figures can be enhanced.
Figure 2 and other results: you are referring to different regions of the world. These need to be marked clearly on the global distribution map (Figure 1). Make bigger figures and define the regions on them.
l.293 (and throughout the manuscript), be careful to always mention if you are referring to “spatial” or “temporal” correlations while reporting r values.
l.300-301: This needs some supporting analysis/discussions. Either compare the emission inventory used here with other estimates or discuss if the model is underestimating particularly near urban centers (so to attribute to anthropogenic) but performing better in remote / vegetated areas.
Table 3 and other places: Are the temporal correlations derived from the mean seasonal cycle (12 points)? It is advisable to use all data (daily values over 2 years) to comment on temporal correlations. Or to discuss both ways. This is a “model evaluation paper” and these details are important.
Table 4 and l.450: here also, clearly write if these are spatial correlations, seasonal (or daily). Check and make this aspect clear throughout the manuscript.
l.471-472: here also check from MEGAN model-based emissions.
Figure 5: I did not get the rationale behind enhancing anthropogenic emissions by a factor of 3. While HCHO was underestimated in reference simulation, now with this change the levels are equally (or more) overestimated over China, US, Africa, America (also see table 5). What has been achieved in terms of model performance?l.503-504: No, the MBE values have increased! Check and revise/strengthen this whole section l.503-518. Also, reconsider tuning the simulation design itself (in place of 3 times more emissions)
Section 3.4: This is an important aspect. Errors in the NOx emissions could have impacted model performance, especially in regions like South and Southeast Asia where inventories have greater uncertainties. Your simulations show that the model driven by older inventory shows lower bias in HCHO. Do you conclude that NOx emissions are overestimated in the new inventory? I did not find a clear assessment out of this important exercise.
Tables and figures coming afterward often has data shown in previous figures and tables. Review them carefully and combine them whenever possible. Like, instead of comparing 1 simulation then another, you may put them in same table as reference, simulation1 and 2;
CHASER and TROPOMI are already compared (Section 3.1). Then there is an extra section comparing CHASER, TROPMI with OMI. Better to combine and strengthen the discussion.
Fig 8: When emission is increased (OLNE), why HCHO is reduced over Chiba and Kasuga, what is the underlying chemistry?
Outside Japan also, there have been MAX-DOAS measurements. This paper being a global model evaluation, comparison over other regions of the world should also be added. If systematic data is not available, mean values may be compared (see Table 2 of Oomen et al., Atmos. Chem. Phys., 2024). Authors themselves have also published observations from another station in South Asia [Hoque et al., SOLA, 2018]
Minor comments
Check the consistency of r values between l.352 and in Table 3.
The data selection criteria for TROPOMI has not been discussed.
Line 387, line no. 467 - Figure no. is missing
In Figure S3, the correlation between TROPOMI and CHASER HCHO columns is marked as r=1 (blue text).
Figure numbering should be corrected. There is no figure 4.
Table 7 , last column name should have been ‘r-value (CHASER vs. OMI)’
Line 781, slope values inconsistent with the slope in figure 9.
References
Chutia, L., N. Ojha, Imran A. Girach, Lokesh K. Sahu, Leonardo M.A. Alvarado, John P. Burrows, Binita Pathak, Pradip Kumar Bhuyan, Distribution of volatile organic compounds over Indian subcontinent during winter: WRF-chem simulation versus observations, Environmental Pollution, Volume 252, Part A, 2019, Pages 256-269, ISSN 0269-7491, https://doi.org/10.1016/j.envpol.2019.05.097.
Duncan, B. N., Y. Yoshida, J.R. Olson, S. Sillman, R.V. Martin, L. Lamsal, Y. Hu, K.E. Pickering, C. Retscher, D.J. Allen, J.H. Crawford, Application of OMI observations to a space-based indicator of NOx and VOC controls on surface ozone formation, Atmos. Environ., 44 (18) (2010), pp. 2213-2223, 10.1016/j.atmosenv.2010.03.010.
Guenther, A., T. Karl, P. Harley, C. Wiedinmyer, P. Palmer, and C. Geron, Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature), Atmos. Chem Phys., 6, 3181-3210, 2006.
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Citation: https://doi.org/10.5194/egusphere-2024-734-RC3 - AC4: 'Reply on RC3', H.M.S. Hoque, 27 May 2024
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RC4: 'Comment on egusphere-2024-734', Anonymous Referee #4, 20 May 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-734/egusphere-2024-734-RC4-supplement.pdf
- AC5: 'Reply on RC4', H.M.S. Hoque, 27 May 2024
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Hossain Mohammed Syedul Hoque
Kengo Sudo
Hitoshi Irie
Yanfeng He
Md Firoz Khan
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.