the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 26 Apr 2024
A novel data-driven global model of photosynthesis using solar-induced chlorophyll fluorescence
Abstract. Space-based vegetation indices have been used to model global photosynthesis for more than two decades. However, vegetation indices are linked to leaf optical properties rather than leaf physiology, which limits their utility in regions where changes in photosynthesis are driven by leaf development and demography. Conversely, solar-induced chlorophyll fluorescence contains information on leaf physiology and has been shown to be synchronous with photosynthetic activity. Here we present a novel model of global photosynthesis, ChloFluo, which uses spaceborne chlorophyll fluorescence to estimate the amount of photosynthetically active radiation (PAR) absorbed by chlorophyll (APARchl). ChloFluo is unique in that instead of estimating APARchl as a function of a vegetation index and an ancillary PAR product, we model APARchl using its empirical relationship with SIF and the proportion of APARchl that is reemitted as SIF, or ΦF. Potential uses of our model are to advance our understanding of the timing and magnitude of photosynthesis, its effect on atmospheric carbon dioxide fluxes, and vegetation response to climate events and change.
Status: closed (peer review stopped)
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CEC1: 'Comment on egusphere-2023-3024', Juan Antonio Añel, 12 May 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.html
We have detected several violations of our policy. I detail them next:
First, as the Topical Editor pointed out in the previous correspondence, you have archived your code on GitHub. However, GitHub is not a suitable repository for scientific publication. GitHub itself instructs authors to use other long-term archival and publishing alternatives, such as Zenodo.
Additionally, you state that the output data is available upon request, and both input and output data should be available in a permanent repository. Therefore, please publish them.
Finally, you link several external web pages for data you have used in your work. However, these (at least some of them) are main homepages, not the specific pages for the particular data you have used, and they are not permanent repositories, so they can not be trusted as permanent storage for the assets necessary to replicate your work. You must provide specific links and DOIs to the data you use, not these pages.
Therefore, you must publish the code and data used in your work in one of the appropriate repositories and reply to this comment with the relevant information (link and DOI) as soon as possible, as it should be available before the Discussion stage.
If you do not fix this problem, we will have to 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, the current situation with your manuscript is irregular.
Juan A. Añel
Geosci. Model Dev. Executive EditorCitation: https://doi.org/10.5194/egusphere-2023-3024-CEC1 -
AC1: 'Reply on CEC1', Russell Doughty, 19 May 2024
Okay, please give me a few days to update the manuscript.
Thanks,
Russ
Citation: https://doi.org/10.5194/egusphere-2023-3024-AC1 -
AC2: 'Reply on CEC1', Russell Doughty, 28 May 2024
Dr. Añel,
It has come to my attention that the supplementary material is also missing. I will finish the requested changes and also include the SM as soon as possible, and no later than the end of the day Friday. Please note that it was Memorial Day weekend here in the US.
Thanks,
Russell Doughty
Citation: https://doi.org/10.5194/egusphere-2023-3024-AC2 -
AC3: 'Reply on CEC1', Russell Doughty, 29 May 2024
I have made the following changes to conform with the journal’s policies:
- The model code hosted at GitHub is now linked and archived at Zenodo. The DOI is https://doi.org/10.5281/zenodo.11388569.
- The model output is also hosted at Zenodo: https://zenodo.org/doi/10.5281/zenodo.11389888
- I have provided DOIs for all the input data, as detailed in the Data Availability section.
- I made sure the document has line numbers.
- I have updated the preprint to reflect these changes: https://doi.org/10.22541/essoar.168167172.20799710/v1
- I have attached the supplementary material to this post and have emailed it to the editorial office.
Thanks,
Russ
-
AC1: 'Reply on CEC1', Russell Doughty, 19 May 2024
-
RC1: 'Comment on egusphere-2023-3024', Anonymous Referee #1, 01 Jun 2024
Review on “A novel data-driven global model of…” by Doughty et al.
Doughty et al have developed a novel model of photosynthesis at global scale, called ChloFluo. This is a light use efficiency (LUE) model, that has a new way to estimate the absorbed photosynthetically active radiation by chlorophyll (APARchl). Empirical relationship between solar-induced chlorophyll fluorescence (SIF) and chlorophyll fluorescence yield (ΦF) is used for this. SIF is obtained from the TROPOMI observations and ΦF is estimated by the CliMA model, that is based on a novel theoretical framework.
The GPP estimated from the new ChloFluo model were compared to earlier GPP predictions by FluxCom and FluxSat at different spatial scales in 2019. Additionally, a comparison against FLUXNET GPP observations was done. It was concluded that the perfomance of the ChloFluo was well enough in other regions compared to earlier estimates, but that it was better for tropics, demonstrated here for three regions and a flux tower site located in the Amazon.
The paper is well written and the figures are clear and illustrative. The paper is also fitting to the scope of the journal. I’d anyhow be interested in some clarifications from the authors.
Major comments
I had difficulties in understanding the modelling system. The SIF originates from the TROPOMI observations and the fluorescence yield you obtain from the CliMA model? What kind of meteorological forcing had been used for those CliMA runs and was the land cover description in line with those used here? At the moment, this modelling protocol of CliMA is not described, only a reference to another paper is made. It would be helpful for the reader, if basic description of these model runs was given. Now it's not showed, that the model systems would be consistent.
Fig. 4 shows predicted seasonal cycles of GPP for TransCom regions by ChloFluo, FluxCom and FluxSat. ChloFluo is having higher values in several regions. The authors explain this by presence of C4 plants in these regions. However, the maximum GPP for Europe seems to be almost double compared to the other estimates. Europe being the region with several flux towers, that should favor the other methods used in the comparison. Is the GPP in Europe also explained by the C4 fraction or what would be the causes for this behaviour? The strong bias in ChloFluo in Europe needs some explanation, especially as the year 2019 had a heat wave in Europe that seems to lower the SIF signal in the latter part of the summer (see below), potentially reducing the bias for this particular year.
l. 205 “temporally overlap the model output” The FLUXNET data you used here is not overlapping with the 2019 year, that you’re using. Some of the site data used for comparison in the supplement is really old, e.g. FI-Jok data is from 2000-2003. It would be worthwhile to discuss, what are the downfalls in using evaluation data that is not overlapping in time. Understandably having global coverage of recent flux tower data is not feasible, but e.g. ICOS data from Europe has been used with TROPOMI related work (Balde et al., 2023) and then exact timing is possible. In the methods you state that you used the sites used in FluxSat development, but now that more recent data has become available, it would make sense to use it.
Minor comments
According to the reviewing criteria of the journal (https://www.geoscientific-model-development.net/peer-review_process/review_criteria.html, #8), the name of the model should be included in the title.
First sentence of introduction: reference?
p. 3 title 1.2 - add SIF in parenthesis to this title?
p. 3 section 1.2: Would it make sense to note the wavelength region for the SIF emission?
p. 4 ΦF – would it make sense to also mention ‘chlorophyll fluorescence yield’ at this point?
p. 3 section 1.3: Would it be useful to add a table with the the abbreviations / variable names used in the study?
p. 4, Add references to FluxCom and FluxSat already here.
Figure 1. These abbreviations shown in the figure must be clearly explained. Many of them have not yet been mentioned in the text. E.g. LSWI.
l. 158: You’re using the SIF_clima to calculate ΦF_clima. Would you like to describe the performance of the SIF_clima against the TROPOMI SIF observations?
p. 7 “𝑆𝐼𝐹𝑑𝑐 is daily-corrected TROPOMI SIF” Could you add a reference to this?
p. 8: How do you define Topt?
l. 218: You could also refer to S2 for the regions of Amazon Basin and SE Asia.
p. 11. Fig 4: In addition to these seasonal cycle figures, it would be good to see a table with the annual GPP for these regions from the three estimates. (Fig. 4 TransCom regions: Is there a certain reason that Mediterranean is not showing up?)
p. 11, l. 247: Could you explain why the C4 fraction explains for the higher peak? Would that stem from the epsilon value that you use, or could also the ΦF_clima play a role there?
p. 12, Fig. 5: The seasonal behavior you’re able to obtain in the Amazon Basin seems to originate from the ΦF. It would be helpful, if you could further explain, what is causing this seasonality in the CliMA model, if that can be explored. Is it stemming from PS1 or PS2 or both?
l. 267. Reference to Fig 5?
l. 287, Fig. S9: Several flux sites have a peak in GPP during June according to ChloFluo and a strong decline then in July. This happens e.g. in eight sites in Fig. S9. If I understood right, ChloFluo is only for 2019, whereas at least the flux data is for other years. There occurred a heat wave in Europe in 2019 (https://en.wikipedia.org/wiki/2019_European_heatwaves), having likely influenced on the German sites shown in this figure. Do you consider it hazardous to use only one year of data for validation, especially when extreme events have been taking place? One might now speculate that because of this extreme event the SIF signal went down at the European sites and without it taking place, the overestimation of annual GPP estimates for Europe would be even higher. Now I find something hinting to this direction only in line 343…
Fig. 8. Where do you have definitions for the land cover types?
p. 15, sect. 4.1, first line: Needs reference.
p. 16: “past, current, and future satellite missions that estimate atmospheric CO2” – I get a bit lost with the reasoning. To my understanding you need SIF observations, that you can then use to infer estimates of GPP and you get SIF observations from the trace gas satellites. But with GPP you only get part of the story to reach to atmospheric CO2, you need respiration and anthropogenic emissions. So are you here aiming for atmospheric inversion models, having a better a priori estimate of GPP for them?
l. 320: So, what’s your view on using a land surface model CliMA in combination with your further studies? Would that also not allow for testing hypothesis related to environmental variables?
l. 334, Fig. S4: Could you explain a bit what a negative beta for ΦF means? Could you explain a bit what is in Fig S4c. From the title I’d guess a subtraction of a and b subpanels, but likely not, when looking at the values…
l. 335: So, why did you not include CliMA results in this comparison?
I guess the reference list in the supplementary material is missing.
Typos etc
p. 6 l. 141: “The leaf-level equation for SIF (Eq. 9)”: Should this be referencing to Eq. 11?
l. 197: “MODIS surface” + reflectance?
l. 304: Where have you defined sigma?
p. 9, line 2: extra “.”
l. 355 Reference to Gamon here differing from the reference style used elsewhere.
References: Reference to Y. Wang is to the preprint, not the publication in JAMES.
References
Balde et al. BG, 2023, https://bg.copernicus.org/articles/20/1473/2023/
Citation: https://doi.org/10.5194/egusphere-2023-3024-RC1 -
RC2: 'Comment on egusphere-2023-3024', Anonymous Referee #2, 05 Aug 2024
This manuscript proposed a novel photosynthesis model by improving term in LUE model (GPP = APAR * ε_g). The authors used the empirical relationship with SIF and to calculate PAR absorbed by chlorophyll (APAR_chl = SIF/ϕ_F) which is more directly related to photosynthesis processes. The model performed well in capturing tropical forest GPP seasonality, which is not well-captured in traditional VIs-based LUE models. Overall, the authors provided a novel global photosynthesis model using state-of-art satellite SIF observation, with the potential to improve our understanding of GPP seasonal variations. I only have some specific comments on the current version of manuscript:
Abstract: It’s better to add the results with model performance.
L69: “best”? Could you please change this extreme description of SIF? And maybe considering there some nonlinear relationship between fluorescence and photochemical yields.
Eq. 11: The theoretical derivation section is detailed, but it is unclear that how APAR_PS2* ϕ_F2 + APAR_PS1* ϕ_F1 equals to APAR_chl* ϕ_F. As shown in equation (38) in Johnson et al. (2021, Photosynth Res), the author could make the derivation clearer in the revision.
L177 It’s better to define the ε0 used in this model.
L179 The title seems to have no numbering.
Eq. 15 Could you give more details about the calculation of Topt?
L245-247 Could you please give more explanation about how C4 fraction map accounted for higher peak GPP values in most regions in Figure4? Why use this C3/C4 map data if it caused estimation uncertainty?
L258 I cannot conclude the result from figure 5. Please give more explanation.
Figure 6: “R2” in legend should be replaced by “R2”.
L296 "lowest" describes too many land cover types. It’s better to change the description.
Figure 2, 3:
- Why is the background color set to black?
- Figure title is “Mean annual GPP” but the unit is gC m-2 day-1. Please check the title and units used.
- The labels for the x-axis and y-axis labels of the inserted histograms are missing.
Citation: https://doi.org/10.5194/egusphere-2023-3024-RC2 -
AC4: 'Comment on egusphere-2023-3024', Russell Doughty, 09 Nov 2024
We are requesting more time on this manuscript, as I had reviews come back from EGU for two papers within a day of each other. Also, I have transitioned to industry from academia, and I only have the weekends to work on the revisions. Currently, I am working to incorporate a co-author(s) to help lead the revision. With the upcoming holidays and AGU, it is likely that we will not be able to submit a revision before February. Even if I had responses and a revision ready to submit, there would not be enough time for my co-authors to contribute given the holidays and AGU.
Thanks for your understanding,
Russ
Citation: https://doi.org/10.5194/egusphere-2023-3024-AC4
Status: closed (peer review stopped)
-
CEC1: 'Comment on egusphere-2023-3024', Juan Antonio Añel, 12 May 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.html
We have detected several violations of our policy. I detail them next:
First, as the Topical Editor pointed out in the previous correspondence, you have archived your code on GitHub. However, GitHub is not a suitable repository for scientific publication. GitHub itself instructs authors to use other long-term archival and publishing alternatives, such as Zenodo.
Additionally, you state that the output data is available upon request, and both input and output data should be available in a permanent repository. Therefore, please publish them.
Finally, you link several external web pages for data you have used in your work. However, these (at least some of them) are main homepages, not the specific pages for the particular data you have used, and they are not permanent repositories, so they can not be trusted as permanent storage for the assets necessary to replicate your work. You must provide specific links and DOIs to the data you use, not these pages.
Therefore, you must publish the code and data used in your work in one of the appropriate repositories and reply to this comment with the relevant information (link and DOI) as soon as possible, as it should be available before the Discussion stage.
If you do not fix this problem, we will have to 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, the current situation with your manuscript is irregular.
Juan A. Añel
Geosci. Model Dev. Executive EditorCitation: https://doi.org/10.5194/egusphere-2023-3024-CEC1 -
AC1: 'Reply on CEC1', Russell Doughty, 19 May 2024
Okay, please give me a few days to update the manuscript.
Thanks,
Russ
Citation: https://doi.org/10.5194/egusphere-2023-3024-AC1 -
AC2: 'Reply on CEC1', Russell Doughty, 28 May 2024
Dr. Añel,
It has come to my attention that the supplementary material is also missing. I will finish the requested changes and also include the SM as soon as possible, and no later than the end of the day Friday. Please note that it was Memorial Day weekend here in the US.
Thanks,
Russell Doughty
Citation: https://doi.org/10.5194/egusphere-2023-3024-AC2 -
AC3: 'Reply on CEC1', Russell Doughty, 29 May 2024
I have made the following changes to conform with the journal’s policies:
- The model code hosted at GitHub is now linked and archived at Zenodo. The DOI is https://doi.org/10.5281/zenodo.11388569.
- The model output is also hosted at Zenodo: https://zenodo.org/doi/10.5281/zenodo.11389888
- I have provided DOIs for all the input data, as detailed in the Data Availability section.
- I made sure the document has line numbers.
- I have updated the preprint to reflect these changes: https://doi.org/10.22541/essoar.168167172.20799710/v1
- I have attached the supplementary material to this post and have emailed it to the editorial office.
Thanks,
Russ
-
AC1: 'Reply on CEC1', Russell Doughty, 19 May 2024
-
RC1: 'Comment on egusphere-2023-3024', Anonymous Referee #1, 01 Jun 2024
Review on “A novel data-driven global model of…” by Doughty et al.
Doughty et al have developed a novel model of photosynthesis at global scale, called ChloFluo. This is a light use efficiency (LUE) model, that has a new way to estimate the absorbed photosynthetically active radiation by chlorophyll (APARchl). Empirical relationship between solar-induced chlorophyll fluorescence (SIF) and chlorophyll fluorescence yield (ΦF) is used for this. SIF is obtained from the TROPOMI observations and ΦF is estimated by the CliMA model, that is based on a novel theoretical framework.
The GPP estimated from the new ChloFluo model were compared to earlier GPP predictions by FluxCom and FluxSat at different spatial scales in 2019. Additionally, a comparison against FLUXNET GPP observations was done. It was concluded that the perfomance of the ChloFluo was well enough in other regions compared to earlier estimates, but that it was better for tropics, demonstrated here for three regions and a flux tower site located in the Amazon.
The paper is well written and the figures are clear and illustrative. The paper is also fitting to the scope of the journal. I’d anyhow be interested in some clarifications from the authors.
Major comments
I had difficulties in understanding the modelling system. The SIF originates from the TROPOMI observations and the fluorescence yield you obtain from the CliMA model? What kind of meteorological forcing had been used for those CliMA runs and was the land cover description in line with those used here? At the moment, this modelling protocol of CliMA is not described, only a reference to another paper is made. It would be helpful for the reader, if basic description of these model runs was given. Now it's not showed, that the model systems would be consistent.
Fig. 4 shows predicted seasonal cycles of GPP for TransCom regions by ChloFluo, FluxCom and FluxSat. ChloFluo is having higher values in several regions. The authors explain this by presence of C4 plants in these regions. However, the maximum GPP for Europe seems to be almost double compared to the other estimates. Europe being the region with several flux towers, that should favor the other methods used in the comparison. Is the GPP in Europe also explained by the C4 fraction or what would be the causes for this behaviour? The strong bias in ChloFluo in Europe needs some explanation, especially as the year 2019 had a heat wave in Europe that seems to lower the SIF signal in the latter part of the summer (see below), potentially reducing the bias for this particular year.
l. 205 “temporally overlap the model output” The FLUXNET data you used here is not overlapping with the 2019 year, that you’re using. Some of the site data used for comparison in the supplement is really old, e.g. FI-Jok data is from 2000-2003. It would be worthwhile to discuss, what are the downfalls in using evaluation data that is not overlapping in time. Understandably having global coverage of recent flux tower data is not feasible, but e.g. ICOS data from Europe has been used with TROPOMI related work (Balde et al., 2023) and then exact timing is possible. In the methods you state that you used the sites used in FluxSat development, but now that more recent data has become available, it would make sense to use it.
Minor comments
According to the reviewing criteria of the journal (https://www.geoscientific-model-development.net/peer-review_process/review_criteria.html, #8), the name of the model should be included in the title.
First sentence of introduction: reference?
p. 3 title 1.2 - add SIF in parenthesis to this title?
p. 3 section 1.2: Would it make sense to note the wavelength region for the SIF emission?
p. 4 ΦF – would it make sense to also mention ‘chlorophyll fluorescence yield’ at this point?
p. 3 section 1.3: Would it be useful to add a table with the the abbreviations / variable names used in the study?
p. 4, Add references to FluxCom and FluxSat already here.
Figure 1. These abbreviations shown in the figure must be clearly explained. Many of them have not yet been mentioned in the text. E.g. LSWI.
l. 158: You’re using the SIF_clima to calculate ΦF_clima. Would you like to describe the performance of the SIF_clima against the TROPOMI SIF observations?
p. 7 “𝑆𝐼𝐹𝑑𝑐 is daily-corrected TROPOMI SIF” Could you add a reference to this?
p. 8: How do you define Topt?
l. 218: You could also refer to S2 for the regions of Amazon Basin and SE Asia.
p. 11. Fig 4: In addition to these seasonal cycle figures, it would be good to see a table with the annual GPP for these regions from the three estimates. (Fig. 4 TransCom regions: Is there a certain reason that Mediterranean is not showing up?)
p. 11, l. 247: Could you explain why the C4 fraction explains for the higher peak? Would that stem from the epsilon value that you use, or could also the ΦF_clima play a role there?
p. 12, Fig. 5: The seasonal behavior you’re able to obtain in the Amazon Basin seems to originate from the ΦF. It would be helpful, if you could further explain, what is causing this seasonality in the CliMA model, if that can be explored. Is it stemming from PS1 or PS2 or both?
l. 267. Reference to Fig 5?
l. 287, Fig. S9: Several flux sites have a peak in GPP during June according to ChloFluo and a strong decline then in July. This happens e.g. in eight sites in Fig. S9. If I understood right, ChloFluo is only for 2019, whereas at least the flux data is for other years. There occurred a heat wave in Europe in 2019 (https://en.wikipedia.org/wiki/2019_European_heatwaves), having likely influenced on the German sites shown in this figure. Do you consider it hazardous to use only one year of data for validation, especially when extreme events have been taking place? One might now speculate that because of this extreme event the SIF signal went down at the European sites and without it taking place, the overestimation of annual GPP estimates for Europe would be even higher. Now I find something hinting to this direction only in line 343…
Fig. 8. Where do you have definitions for the land cover types?
p. 15, sect. 4.1, first line: Needs reference.
p. 16: “past, current, and future satellite missions that estimate atmospheric CO2” – I get a bit lost with the reasoning. To my understanding you need SIF observations, that you can then use to infer estimates of GPP and you get SIF observations from the trace gas satellites. But with GPP you only get part of the story to reach to atmospheric CO2, you need respiration and anthropogenic emissions. So are you here aiming for atmospheric inversion models, having a better a priori estimate of GPP for them?
l. 320: So, what’s your view on using a land surface model CliMA in combination with your further studies? Would that also not allow for testing hypothesis related to environmental variables?
l. 334, Fig. S4: Could you explain a bit what a negative beta for ΦF means? Could you explain a bit what is in Fig S4c. From the title I’d guess a subtraction of a and b subpanels, but likely not, when looking at the values…
l. 335: So, why did you not include CliMA results in this comparison?
I guess the reference list in the supplementary material is missing.
Typos etc
p. 6 l. 141: “The leaf-level equation for SIF (Eq. 9)”: Should this be referencing to Eq. 11?
l. 197: “MODIS surface” + reflectance?
l. 304: Where have you defined sigma?
p. 9, line 2: extra “.”
l. 355 Reference to Gamon here differing from the reference style used elsewhere.
References: Reference to Y. Wang is to the preprint, not the publication in JAMES.
References
Balde et al. BG, 2023, https://bg.copernicus.org/articles/20/1473/2023/
Citation: https://doi.org/10.5194/egusphere-2023-3024-RC1 -
RC2: 'Comment on egusphere-2023-3024', Anonymous Referee #2, 05 Aug 2024
This manuscript proposed a novel photosynthesis model by improving term in LUE model (GPP = APAR * ε_g). The authors used the empirical relationship with SIF and to calculate PAR absorbed by chlorophyll (APAR_chl = SIF/ϕ_F) which is more directly related to photosynthesis processes. The model performed well in capturing tropical forest GPP seasonality, which is not well-captured in traditional VIs-based LUE models. Overall, the authors provided a novel global photosynthesis model using state-of-art satellite SIF observation, with the potential to improve our understanding of GPP seasonal variations. I only have some specific comments on the current version of manuscript:
Abstract: It’s better to add the results with model performance.
L69: “best”? Could you please change this extreme description of SIF? And maybe considering there some nonlinear relationship between fluorescence and photochemical yields.
Eq. 11: The theoretical derivation section is detailed, but it is unclear that how APAR_PS2* ϕ_F2 + APAR_PS1* ϕ_F1 equals to APAR_chl* ϕ_F. As shown in equation (38) in Johnson et al. (2021, Photosynth Res), the author could make the derivation clearer in the revision.
L177 It’s better to define the ε0 used in this model.
L179 The title seems to have no numbering.
Eq. 15 Could you give more details about the calculation of Topt?
L245-247 Could you please give more explanation about how C4 fraction map accounted for higher peak GPP values in most regions in Figure4? Why use this C3/C4 map data if it caused estimation uncertainty?
L258 I cannot conclude the result from figure 5. Please give more explanation.
Figure 6: “R2” in legend should be replaced by “R2”.
L296 "lowest" describes too many land cover types. It’s better to change the description.
Figure 2, 3:
- Why is the background color set to black?
- Figure title is “Mean annual GPP” but the unit is gC m-2 day-1. Please check the title and units used.
- The labels for the x-axis and y-axis labels of the inserted histograms are missing.
Citation: https://doi.org/10.5194/egusphere-2023-3024-RC2 -
AC4: 'Comment on egusphere-2023-3024', Russell Doughty, 09 Nov 2024
We are requesting more time on this manuscript, as I had reviews come back from EGU for two papers within a day of each other. Also, I have transitioned to industry from academia, and I only have the weekends to work on the revisions. Currently, I am working to incorporate a co-author(s) to help lead the revision. With the upcoming holidays and AGU, it is likely that we will not be able to submit a revision before February. Even if I had responses and a revision ready to submit, there would not be enough time for my co-authors to contribute given the holidays and AGU.
Thanks for your understanding,
Russ
Citation: https://doi.org/10.5194/egusphere-2023-3024-AC4
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