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| 10 Dec 2024
Sensitivity of climate-chemistry model simulated atmospheric composition to lightning-produced NOx parameterizations based on lightning frequency
Abstract. Lightning-produced nitrogen oxides (LNOx=LNO+LNO2) are an important source of upper tropospheric ozone. Typical parameterizations of LNOx in chemistry-climate models introduce a constant amount of NOx per flash or per flash type. However, recent satellite-based NO2 measurements suggest that the production of LNOx per flash depends on the lightning flash frequency. In this study, we implement a new parameterization of LNOx production per flash based on the lightning flash frequency into a chemistry-climate model to investigate the implications for the chemical composition of the atmosphere. We find that a larger injection of LNOx in weak thunderstorms leads to a larger mixing ratio of NOx in the lower and the middle troposphere, and to a lower mixing ratio of NOx in the upper troposphere. The mixing ratios of O3, CO, HOx, HNO3 and HNO4 in the troposphere are influenced by the simulated changes of LNOx. Our findings indicate a larger release of nitrogen oxides from lightning in the lower and the middle atmosphere, producing a slightly better agreement with the measurements of tropospheric ozone at a global scale. In turn, we obtain a small decrease of the lifetime of methane and of carbon monoxide.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Chemistry and Physics.
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RC1: 'Comment on egusphere-2024-3348', Anonymous Referee #1, 06 Jan 2025
Review of “Sensitivity of climate-chemistry model simulated atmospheric composition to lightning-produced NOx parameterizations based on lightning frequency” by Pérez-Invernón et al.
This study runs a number of simulations with a chemistry-climate model (with several of those in a chemistry-transport like setup, where the meteorology is independent of the chemistry simulation). Three lightning parametrisations are used to explore the sensitivity of results to that choice. The primary focus of the study is on the implementation of a LNOx emission per flash that is dependent on the flash rate, normally it is constant. The relationship is based on a previous study using satellite data over the midlatitudes that found an inverse relationship between flash rate and LNOx emission per flash. The authors report that the NOx concentration reduces in some regions typically higher in LNOx emissions, such as upper troposphere, and increases in regions with typically lower LNOx emissions, such as the lower and mid troposphere. They also report a number of other effectson atmospheric composition.
The Bucsela et al. (2019) finding of an inverse relationship between flash rate and LNOx per flash is an interesting one, and warrants investigation of the effects within lightning chemistry parametrisations. It is good that the authors have investigated this, and the results can provide a useful reference for all atmospheric chemistry modellers.
I have a few issues with the work as it stands and the authors would need to make changes for me to feel like this was ready to publish. I particularly note that in some cases I wonder whether the small changes described are actually insignificant, and therefore null results. The authors are not clear on this point, but I would encourage them to be, and I would encourage the editor to publish (once other comments have been addressed) whether there are significant or insignificant results. For this study, null results are as useful as significant results.
Major comments
Use of Bucsela et al. (2019) - There is not sufficient acknowledgement and discussion of the focus of Bucsela study over mid-laittudes, whilst you are applying it over the whole globe. Please add more text discussing the potential issues with this.
Description of different parametrisations – you use 3 parametrisations. They are reasonable choices, but you are not describing them sufficiently. I know there are references, but at the very least say what the input variables are (e.g. updraught mass flux for the Grewe). Please include some text to elaborate on that.
Description of NOx per flash parametrisation – Given its new and the focus of this study, I’m amazed you have not included at least the equation, if not a plot, of the LNOx per flash equation you have used. I appreciate the plot is in Bucsela, but you should at least include in the methods, your implemented equation. If other modellers want to implement this, they should quickly and easily be able to apply the same parameters and form that you have used.
L72 – How do you do this on a 1x1 deg grid when the model is simulated at a coarser resolution? Also, what allowances do you make for grid cell area varying with latitude as this would vary the flash rate purely because of an area change (do you actually use flash rate density in some way?)
L130-132 – It is not obvious to me which spatial map is best. I suggest you refer to particular features that have made you reach this conclusion. It is awkward that I had to look at another paper to corroborate your conclusion, given that it seems a pretty key bit of evaluation – is it not possible to have a figure in the introduction that reproduces relevant panels from Bucsela2019? Then you would be able to refer the reader to it throughout your paper, instead of drawing key conclusions based on material not in your manuscript.
Fig1 – Although I’m loathed to say someone should use a rainbow-based scale (as Bucsela has), in this case, it would help the reader compare your results to their figure if you used the same colourmap.
L236 – It's not obvious to me if any of the methane lifetime changes are significant. This is a general issue throughout the paper that the authors quote small changes without testing significance. I suggest this should be done for results the authors consider most key (I would say methane lifetime is one of those). Null results are fine and useful so please just be clear on that.
Fig14 – include a plot of the observations in the figure so the necessary material for your conclusion is here.
Figs10-13 – Broadly the biases are not affected by the new scheme. Have you checked if the temporal correlation is? It is not easy to tell by looking at different plots of each season. You could make an equivalent zonal plot of temporal correlation between the model and obs, and then panels with differences in correlation for your different schemes. It would be interesting to know if there was any significant improvements.
Minor comments
Title – I find the title is not precise enough for the novelty of this work to be clear. I would say that all lightning NOx parametrisations are based on lightning frequency in that the more lightning there is the more NOx. It is specifically the per flash parameter that you are varying and which is novel. It’s hard to think how to frame this in such a way as to be precise but also meaningful without detailed explanation. Maybe something like “...composition to applying an inverse relationship of NOx emission per lightning flash”?
L39-49 – There is a lot of text on Lightning and ozone here that is not obviously useful. It mainly seems to be saying lightning affects ozone but different schemes introduce different biases when simulating it. I think that can be said in a couple of sentences. If there’s something in here relevant to your results then I think it would make more sense for the reader for it to come in a discussion section.
L82 – Are there any scaling factors applied to the different paramtrisations (as discussed extensively in Tost et al (2007)? If so list them here.
Table2 – It would be quicker for the reader to take this in if it were a figure with three line plots.
L103 – why is only the Luhar percentile result mentioned?
Throughout - “Injection of LNOx” terminology is not something I’ve seen much. It seems strange because it is not coming from outside the atmosphere, and therefore is not injected. It is a result of reactions within the atmopshere. Most commonly, I see it referred to as LNOx “emissions”. Or the term “production” seems most precise to me.
Sec3.3 - Why are the Luhar results are not shown, or at least discussed, along with the other parametrisation results? Up to this point, I thought there was a sense that it was the better parametrisation, though I’m not sure. At least explain to the reader in the text, if and why you are deciding to focus on certain results.
L125 - “active” to “intense”? (normally I’d think of active as related to frequency of events, but I don’t think that’s what you mean. You mean few events that are more intense, I think).
L129 - “the largest amount” I don’t think you mean. You mean “relatively more”.
Fig10 – It is not a white “line” but a white “region”, that shows the straosphere.
Technical comments
L33 - “rate” to “rates”
L49 – I suggest yo umight want a new paragraph at “Previous studies...”
L71 and throughout - “bucsela2019midlatitude” citation typo
L125 - “sparsed” to “sparse”
L155 - “lead” to “leads”
Citation: https://doi.org/10.5194/egusphere-2024-3348-RC1 - AC1: 'Reply on RC1', Francisco Javier Perez-Invernon, 10 Feb 2025
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RC2: 'Comment on egusphere-2024-3348', Anonymous Referee #2, 08 Jan 2025
Using a global chemistry-climate model, this paper investigates how various formulations of lightning-generated oxides of nitrogen (LNOx) influences the chemical composition of the atmosphere. Of particular interest is the formulation in which the production of LNOx per lightning flash decreases with lightning flash frequency, in contrast to the commonly used assumption that the amount of LNOx produced per flash is constant. The authors find that this formulation leads to larger NOx mixing ratios in the lower and middle troposphere and lower NOx mixing ratios in the upper troposphere, with consequences on atmospheric composition also reported.
Uncertainty in the quantification of LNOx and its atmospheric and climate ramifications remains rather large, and the present paper is an interesting contribution towards assessing that uncertainty through examining the chemistry-climate model sensitivity to LNOx. I favour publication of the paper, but it requires a major revision, considering the following points.
1. As a starting point of the study, one would want to know how the flash frequencies predicted by the Price and Rind (1992), Grewe et al. (2001) and Luhar et al. (2021) schemes compare with observations. The authors merely state (lines 65-66) that ‘… we use scaling factors that ensure a global lightning occurrence rate of ∼45 flashes per second (Christian et al., 2003; Cecil et al., 2014).’ I would like the authors to compare the global distributions of the predicted flash frequencies with observations such as those from Cecil et al. (2014). Once there is a confidence in the prediction ability of these schemes, one can then move on to LNOx calculations and impacts on the chemical composition of the atmosphere.
Also, please give what the scaling factor values were for the three schemes, and the predicted and observed global mean values of flash frequency for the ocean and land.
2. The work presented is built around the relationship between the lightning flash frequency and the LNOx Production Efficiency (PE) per flash shown in Fig. 11(c) of Bucsela et al. (2019), which shows an almost exponentially decreasing relationship. While such a strong relationship is surprising, it is mainly based on observations from three continental regions in northern midlatitudes. Thus, the validity of this relationship for the ocean is untested. Generally, the flash frequency over the ocean is much less than that over the land, and thus this relationship would predict much larger values of the LNOx production efficiency per flash over the ocean. Whether that is the case, we do not know as the relationship is based on data for land. The authors need to discuss and clarify this point.
3. Some more details of the derivation of the relationship shown in Fig. 11(c) of Bucsela et al. (2019) should be presented. How does this relationship depend on the grid resolution? Also, it will be useful to provide the functional form of this relationship that the authors have used (or was it some form of interpolation?).
4. Line 35 and throughout: ‘…lightning as a total number of NOx molecules per flash...’ To remove any ambiguity, best to say if it is NO or NO2 molecules per flash (I think it’s the former). Similarly, is it moles per flash of NO or NO2?
5. Line 72: ‘We check that the percentage of boxes that contain a flash frequency lower than a specified value…’ Is this to account for the change from the 1° × 1° data analysis grid to the model 2.8° × 2.8° grid?
6. Line 80: ‘…to derive the forcings for the subsequent simulations.’ This is not clear to me. What type of forcings? Why are they needed? Later, Line 88 says ‘…but using the radiative forcing fields from the BASE simulations’ What exactly are these radiative forcing fields?
7. Line 81: ‘In these simulations, we impose a production of 1,112 mol per CG flash and 111.2 mol per IC flash...’ Obviously, this is a critical assumption (i.e. the LNOx ratio IC/CG = 0.1) following Price et al. (1997), and is by no means a certain one. The authors should give some discussion on the implications of the variability of this ratio for their simulations.
8. Table 1: The “LNOfs" simulations use the same moles NO produced per flash irrespective of CG or IC flash, unlike the other simulations. Is this because the CG-IC distinction is implicitly included in the relationship in Fig. 11(c) of Bucsela et al. (2019) used in the present LNOfs simulations?
9. Line 100: Why only year 2000? Weren’t the simulations done for 8 years?
10. Section 3.1: Table 2 data should be presented in graphical form for consistency with Fig. 11 of Bucsela et al. (2019).
11. Fig. 1: The colour scales are different in each panel which makes it difficult to make a meaningful visual intercomparison (the same issue with some of the other subsequent plots). I would like to see the same scale in the top two row plots and the same in the bottom row plots. Also, I find it uncomfortable to view the top two rows of plots. Can a better colour scheme be used?
12. Line 131: ‘…LNOfs simulations produces a spatial distribution of LNOx that aligns with space-based measurements more accurately (Bucsela et al., 2019, Fig. 3(c)) than…’ This is not convincing as there is no way of telling that, given the different colour schemes and scales used in the two studies.
13. Section 3.3: Not sure why the LNOfs_L and CTR_L simulations are not discussed here.
14. Line 206: ‘…where negative values represent a reduced LNOx injection in the LNOfsL simulation’ Check.
15. Page 8: Figures 5–8 are discussed before Figure 4?
16. Line 249: ‘During all the seasons, the LNOfs simulations produce more tropospheric ozone than the corresponding CTR simulations in the tropics, causing more disagreement with measurements…’ I am unable to see this in the difference plots, exacerbated by the fact that the scale is different in the plots.
17. Line 286: ‘Therefore, the results obtained in this study should be regarded as the upper limit…’ Please say this in the abstract too.
18. Line 267: ‘…resulting in a better agreement with measurements (Jockel et al., 2016, Fig. 29).’ I suggest the authors reproduce Fig. 29 of Jockel et al. to make comparison easier.
19. The reference Bucsela et al. (2021) is only an AGU conference abstract. I question the usefulness of it.
20. Both the terms ‘climate-chemistry model’ (e.g. in the title) and ‘chemistry-climate model’ (e.g. in the abstract) have been used. Please keep consistency (I think most researchers use the latter).
21. Lines 354 and 363: The https addresses of these two references seem to have been swapped.
Citation: https://doi.org/10.5194/egusphere-2024-3348-RC2 - AC2: 'Reply on RC2', Francisco Javier Perez-Invernon, 10 Feb 2025
Status: closed
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RC1: 'Comment on egusphere-2024-3348', Anonymous Referee #1, 06 Jan 2025
Review of “Sensitivity of climate-chemistry model simulated atmospheric composition to lightning-produced NOx parameterizations based on lightning frequency” by Pérez-Invernón et al.
This study runs a number of simulations with a chemistry-climate model (with several of those in a chemistry-transport like setup, where the meteorology is independent of the chemistry simulation). Three lightning parametrisations are used to explore the sensitivity of results to that choice. The primary focus of the study is on the implementation of a LNOx emission per flash that is dependent on the flash rate, normally it is constant. The relationship is based on a previous study using satellite data over the midlatitudes that found an inverse relationship between flash rate and LNOx emission per flash. The authors report that the NOx concentration reduces in some regions typically higher in LNOx emissions, such as upper troposphere, and increases in regions with typically lower LNOx emissions, such as the lower and mid troposphere. They also report a number of other effectson atmospheric composition.
The Bucsela et al. (2019) finding of an inverse relationship between flash rate and LNOx per flash is an interesting one, and warrants investigation of the effects within lightning chemistry parametrisations. It is good that the authors have investigated this, and the results can provide a useful reference for all atmospheric chemistry modellers.
I have a few issues with the work as it stands and the authors would need to make changes for me to feel like this was ready to publish. I particularly note that in some cases I wonder whether the small changes described are actually insignificant, and therefore null results. The authors are not clear on this point, but I would encourage them to be, and I would encourage the editor to publish (once other comments have been addressed) whether there are significant or insignificant results. For this study, null results are as useful as significant results.
Major comments
Use of Bucsela et al. (2019) - There is not sufficient acknowledgement and discussion of the focus of Bucsela study over mid-laittudes, whilst you are applying it over the whole globe. Please add more text discussing the potential issues with this.
Description of different parametrisations – you use 3 parametrisations. They are reasonable choices, but you are not describing them sufficiently. I know there are references, but at the very least say what the input variables are (e.g. updraught mass flux for the Grewe). Please include some text to elaborate on that.
Description of NOx per flash parametrisation – Given its new and the focus of this study, I’m amazed you have not included at least the equation, if not a plot, of the LNOx per flash equation you have used. I appreciate the plot is in Bucsela, but you should at least include in the methods, your implemented equation. If other modellers want to implement this, they should quickly and easily be able to apply the same parameters and form that you have used.
L72 – How do you do this on a 1x1 deg grid when the model is simulated at a coarser resolution? Also, what allowances do you make for grid cell area varying with latitude as this would vary the flash rate purely because of an area change (do you actually use flash rate density in some way?)
L130-132 – It is not obvious to me which spatial map is best. I suggest you refer to particular features that have made you reach this conclusion. It is awkward that I had to look at another paper to corroborate your conclusion, given that it seems a pretty key bit of evaluation – is it not possible to have a figure in the introduction that reproduces relevant panels from Bucsela2019? Then you would be able to refer the reader to it throughout your paper, instead of drawing key conclusions based on material not in your manuscript.
Fig1 – Although I’m loathed to say someone should use a rainbow-based scale (as Bucsela has), in this case, it would help the reader compare your results to their figure if you used the same colourmap.
L236 – It's not obvious to me if any of the methane lifetime changes are significant. This is a general issue throughout the paper that the authors quote small changes without testing significance. I suggest this should be done for results the authors consider most key (I would say methane lifetime is one of those). Null results are fine and useful so please just be clear on that.
Fig14 – include a plot of the observations in the figure so the necessary material for your conclusion is here.
Figs10-13 – Broadly the biases are not affected by the new scheme. Have you checked if the temporal correlation is? It is not easy to tell by looking at different plots of each season. You could make an equivalent zonal plot of temporal correlation between the model and obs, and then panels with differences in correlation for your different schemes. It would be interesting to know if there was any significant improvements.
Minor comments
Title – I find the title is not precise enough for the novelty of this work to be clear. I would say that all lightning NOx parametrisations are based on lightning frequency in that the more lightning there is the more NOx. It is specifically the per flash parameter that you are varying and which is novel. It’s hard to think how to frame this in such a way as to be precise but also meaningful without detailed explanation. Maybe something like “...composition to applying an inverse relationship of NOx emission per lightning flash”?
L39-49 – There is a lot of text on Lightning and ozone here that is not obviously useful. It mainly seems to be saying lightning affects ozone but different schemes introduce different biases when simulating it. I think that can be said in a couple of sentences. If there’s something in here relevant to your results then I think it would make more sense for the reader for it to come in a discussion section.
L82 – Are there any scaling factors applied to the different paramtrisations (as discussed extensively in Tost et al (2007)? If so list them here.
Table2 – It would be quicker for the reader to take this in if it were a figure with three line plots.
L103 – why is only the Luhar percentile result mentioned?
Throughout - “Injection of LNOx” terminology is not something I’ve seen much. It seems strange because it is not coming from outside the atmosphere, and therefore is not injected. It is a result of reactions within the atmopshere. Most commonly, I see it referred to as LNOx “emissions”. Or the term “production” seems most precise to me.
Sec3.3 - Why are the Luhar results are not shown, or at least discussed, along with the other parametrisation results? Up to this point, I thought there was a sense that it was the better parametrisation, though I’m not sure. At least explain to the reader in the text, if and why you are deciding to focus on certain results.
L125 - “active” to “intense”? (normally I’d think of active as related to frequency of events, but I don’t think that’s what you mean. You mean few events that are more intense, I think).
L129 - “the largest amount” I don’t think you mean. You mean “relatively more”.
Fig10 – It is not a white “line” but a white “region”, that shows the straosphere.
Technical comments
L33 - “rate” to “rates”
L49 – I suggest yo umight want a new paragraph at “Previous studies...”
L71 and throughout - “bucsela2019midlatitude” citation typo
L125 - “sparsed” to “sparse”
L155 - “lead” to “leads”
Citation: https://doi.org/10.5194/egusphere-2024-3348-RC1 - AC1: 'Reply on RC1', Francisco Javier Perez-Invernon, 10 Feb 2025
-
RC2: 'Comment on egusphere-2024-3348', Anonymous Referee #2, 08 Jan 2025
Using a global chemistry-climate model, this paper investigates how various formulations of lightning-generated oxides of nitrogen (LNOx) influences the chemical composition of the atmosphere. Of particular interest is the formulation in which the production of LNOx per lightning flash decreases with lightning flash frequency, in contrast to the commonly used assumption that the amount of LNOx produced per flash is constant. The authors find that this formulation leads to larger NOx mixing ratios in the lower and middle troposphere and lower NOx mixing ratios in the upper troposphere, with consequences on atmospheric composition also reported.
Uncertainty in the quantification of LNOx and its atmospheric and climate ramifications remains rather large, and the present paper is an interesting contribution towards assessing that uncertainty through examining the chemistry-climate model sensitivity to LNOx. I favour publication of the paper, but it requires a major revision, considering the following points.
1. As a starting point of the study, one would want to know how the flash frequencies predicted by the Price and Rind (1992), Grewe et al. (2001) and Luhar et al. (2021) schemes compare with observations. The authors merely state (lines 65-66) that ‘… we use scaling factors that ensure a global lightning occurrence rate of ∼45 flashes per second (Christian et al., 2003; Cecil et al., 2014).’ I would like the authors to compare the global distributions of the predicted flash frequencies with observations such as those from Cecil et al. (2014). Once there is a confidence in the prediction ability of these schemes, one can then move on to LNOx calculations and impacts on the chemical composition of the atmosphere.
Also, please give what the scaling factor values were for the three schemes, and the predicted and observed global mean values of flash frequency for the ocean and land.
2. The work presented is built around the relationship between the lightning flash frequency and the LNOx Production Efficiency (PE) per flash shown in Fig. 11(c) of Bucsela et al. (2019), which shows an almost exponentially decreasing relationship. While such a strong relationship is surprising, it is mainly based on observations from three continental regions in northern midlatitudes. Thus, the validity of this relationship for the ocean is untested. Generally, the flash frequency over the ocean is much less than that over the land, and thus this relationship would predict much larger values of the LNOx production efficiency per flash over the ocean. Whether that is the case, we do not know as the relationship is based on data for land. The authors need to discuss and clarify this point.
3. Some more details of the derivation of the relationship shown in Fig. 11(c) of Bucsela et al. (2019) should be presented. How does this relationship depend on the grid resolution? Also, it will be useful to provide the functional form of this relationship that the authors have used (or was it some form of interpolation?).
4. Line 35 and throughout: ‘…lightning as a total number of NOx molecules per flash...’ To remove any ambiguity, best to say if it is NO or NO2 molecules per flash (I think it’s the former). Similarly, is it moles per flash of NO or NO2?
5. Line 72: ‘We check that the percentage of boxes that contain a flash frequency lower than a specified value…’ Is this to account for the change from the 1° × 1° data analysis grid to the model 2.8° × 2.8° grid?
6. Line 80: ‘…to derive the forcings for the subsequent simulations.’ This is not clear to me. What type of forcings? Why are they needed? Later, Line 88 says ‘…but using the radiative forcing fields from the BASE simulations’ What exactly are these radiative forcing fields?
7. Line 81: ‘In these simulations, we impose a production of 1,112 mol per CG flash and 111.2 mol per IC flash...’ Obviously, this is a critical assumption (i.e. the LNOx ratio IC/CG = 0.1) following Price et al. (1997), and is by no means a certain one. The authors should give some discussion on the implications of the variability of this ratio for their simulations.
8. Table 1: The “LNOfs" simulations use the same moles NO produced per flash irrespective of CG or IC flash, unlike the other simulations. Is this because the CG-IC distinction is implicitly included in the relationship in Fig. 11(c) of Bucsela et al. (2019) used in the present LNOfs simulations?
9. Line 100: Why only year 2000? Weren’t the simulations done for 8 years?
10. Section 3.1: Table 2 data should be presented in graphical form for consistency with Fig. 11 of Bucsela et al. (2019).
11. Fig. 1: The colour scales are different in each panel which makes it difficult to make a meaningful visual intercomparison (the same issue with some of the other subsequent plots). I would like to see the same scale in the top two row plots and the same in the bottom row plots. Also, I find it uncomfortable to view the top two rows of plots. Can a better colour scheme be used?
12. Line 131: ‘…LNOfs simulations produces a spatial distribution of LNOx that aligns with space-based measurements more accurately (Bucsela et al., 2019, Fig. 3(c)) than…’ This is not convincing as there is no way of telling that, given the different colour schemes and scales used in the two studies.
13. Section 3.3: Not sure why the LNOfs_L and CTR_L simulations are not discussed here.
14. Line 206: ‘…where negative values represent a reduced LNOx injection in the LNOfsL simulation’ Check.
15. Page 8: Figures 5–8 are discussed before Figure 4?
16. Line 249: ‘During all the seasons, the LNOfs simulations produce more tropospheric ozone than the corresponding CTR simulations in the tropics, causing more disagreement with measurements…’ I am unable to see this in the difference plots, exacerbated by the fact that the scale is different in the plots.
17. Line 286: ‘Therefore, the results obtained in this study should be regarded as the upper limit…’ Please say this in the abstract too.
18. Line 267: ‘…resulting in a better agreement with measurements (Jockel et al., 2016, Fig. 29).’ I suggest the authors reproduce Fig. 29 of Jockel et al. to make comparison easier.
19. The reference Bucsela et al. (2021) is only an AGU conference abstract. I question the usefulness of it.
20. Both the terms ‘climate-chemistry model’ (e.g. in the title) and ‘chemistry-climate model’ (e.g. in the abstract) have been used. Please keep consistency (I think most researchers use the latter).
21. Lines 354 and 363: The https addresses of these two references seem to have been swapped.
Citation: https://doi.org/10.5194/egusphere-2024-3348-RC2 - AC2: 'Reply on RC2', Francisco Javier Perez-Invernon, 10 Feb 2025
Data sets
Monthly averaged lightning and trace gases data extracted from EMAC simulations (2007, T42L90MA resolution) F. J. Pérez-Invernón et al. https://doi.org/10.5281/zenodo.13968463
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