the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 18 Dec 2023
How the meteorological spectral nudging impacts on aerosol radiation clouds interactions?
Abstract. Meteorological and chemical modelling at the regional scale involve nudging to remain consistent with large-scale meteorology and meteo-chemical coupling to properly consider the interactions between aerosols, clouds and radiations. Both types of process can change meteorology, but not for the same reasons and not necessarily in the same way. To assess the possible interactions between nudging and coupling, several simulations are carried out with the WRF-CHIMERE coupled model. By comparison with measurements, we show that the use of nudging significantly improves the model performances. We also show that coupling changes the results much less than nudging. Finally, we show that when nudging is used, it limits the variability in the results due to coupling.
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RC1: 'Reviewer comments on Menut et al. (gmd-2023-209)', Anonymous Referee #1, 09 Jan 2024
This paper presents an analysis on the impact of meteorological nudging and online coupling of aerosol microphysics on selected simulated variables in a regional model.
The results are not very surprising, but still useful for model applications, e.g., for assessment studies. In that sense, I find this study within the scope of GMD.
There are, however, several issues that should be addressed before the paper can be accepted for publication:
- The Results section (Sect. 3) is rather descriptive and no attempt is done by the authors to interpret the results. Some specific features noted on the plots need to be explained in view of the model parametrizations and configurations. This is done only for a few specific cases, but it is missing otherwise.
- Although the authors have access to a quite comprehensive set of stations data (Table A1) they choose to show and discuss only a few stations and their choice is not very well motivated. I think it would be valuable to consider the data from all available stations and try to derive a synthesis from them, for example by applying some kind of statistical metrics to summarize the results and trying to derive a more general conclusion.
- The terminology used to distinguish the coupled / uncoupled model configuration is not consistent, sometimes different terms are used (online/offline, direct/indirect effects). The authors should aim at a more consistent definition of the tested configurations.
- I find the title misleading: the study is not addressing the impact of nudding on aerosol-cloud-radiation interactions, but rather the impact of model coupling on meteorological variables, pollutants concentrations and aerosol optical properties. Please consider a more precise title.
- The presentation quality should be improved: several sentences are unclear and/or hard to read and some of the figures have small fonts or unconvenient colors (see detailed suggestions below).
Specific comments
L5: WRF-CHIMERE coupled model: I would rather write WRF-CHIMERE regional model, in its coupled and uncoupled configuration.
L13: I would explain why, or for which use case, a forcing inside the domain is needed.
L18-19: it would be good to explain how aerosol can modify the meteorology in the model.
L20: it is not clear which forcing is meant here.
Fig. 1: the caption needs to provide more details to help the reader understanding the figure. For example, what is the meaning of the different colors and dashes of the arrows?
L30: this methodological alternative should be discussed again in the conclusions in view of the analysis presented in the paper. Since the paper is mainly addressed to the users of this model, a key-message should be formulated to help them choosing the propert methodology in the future.
L50: in this paragraph, you may consider mentioning Chrysanthou et al. (2019) too (https://doi.org/10.5194/acp-19-11559-2019).
Fig. 2: the two letters identifying the stations are hard to read. It might be wiser numbering the stations instead (here and in Table A1). The choice of the colors is not optimal for color-blinded readers. Please consider alternative colors.
L84: I would suggest naming Sect. 2.1 Model parameterizations and providing a few more details about the parametrizations themselves. For example, about the cloud scheme and how this can be coupled to the aerosol microphysics (which I guess is part of CHIMERE described below).
L96: I am not sure that grid nudging applied over all grid cells is necessarily an advantage, since this does not allow to limit the nudging to certain scales. Moreover, the fact that spectral nudging is less intrusive depends on its configuration and whether, for instance, wave-0 nudging is considered or not. Please clarify.
L103: what do you mean with perturbation of the geopotential? What is the source of this perturbation? Please specify.
L113: I find the remaining of this section quite hard to follow. I would suggest providing clear mathematical definitions for the nudging coefficients and to be more specific on how the calculations of the wave numbers (Eq. 1) are considered in the nudging scheme. Is this a maximum wave number for which spectral nudging is applied?
L133: I would add an introductory sentence to make clear the CHIMERE is an aerosol-chemistry scheme which is used when running WRF in online mode (if I understood correctly). Is this online mode only considering the impact of aerosol or also the impact of chemistry (e.g. ozone impact on radiation)?
L133: to take into account the direct effects of aerosol on clouds and radiation. This sentence is unclear, also in relation with the following sentence. If I interpreted it correctly, you mean that CHIMERE can account for both aerosol-radiation and aerosol-cloud interactions. If this is the case, I would also add a short explanation on how this is achieved technically. Referring to other publications is not enough, the text should be self explanatory, at least concerning the basic functionalities of the model.
L140: the aerosol microphysics simulated by the model should also be mentioned (which processes and species are considered?).
L158: please list the applied statistical scores here with their full name (the table just show their symbol).
L162: please provide an example of such local features (orography?).
L165: the last sentence of this paragraph is unclear. Please consider rephrasing.
Table 2: please be more specific on the procedure applied to aggregate the statistical scores.
L174: The impact of the coupling is less important and the scores are more or less the less with and without the coupling. Do you mean, the scores are quite similar independently of the coupling mode?
L179: ...there is no clear impact of the use of the direct effects or nor on the scores. This is an example where the use of different terminology (main comment 3 above) makes the text hard to understand. What do you mean with the use of the direct effects? Are you referring to coupled vs. uncoupled model? Please clarify.
L188: what is the reason for showing and discussing only the stations data for Orléans and Bordeaux? As noted in the main comment 2 above, you have a valuable set of measurements and you should take full advantage of them.
L190: I would consider adding the results for the other stations to a supplement.
Fig. 3: the left and right panels have the same titles, but show different variables. Please add the variable name to the title, e.g. Bordeaux (daily mean) - Temperature or similar. Do the right panels show the 10m wind speed or only its u-component (as indicated on the y-axis)? Please specify. The legend is very small and hard to read: since it is the same for all panels, you may consider a common legend at the bottom of the plot. Please also use more friendly colors (see above comment on Fig. 1). The same applies to Fig. 4.
L199: what is meant with interface here?
L203: why do the nudged simulations performed better, given that wind nudging is not effective at small scales? Or am I missing something?
L214: It is difficult to disentangle the several simulations and to diagnose the best scores without statistical calculations. Why not performing such analysis? These scores have been computed for temperature and wind speed, it should not be too difficult to repeat the analysis for ozone, PM and AOD.
L234: as above, please motivate the choice of these three stations. Although, I note again that including all stations would significantly improve the analysis.
L240: How are the direct/indirect effects impact the AOD? It is actually the other way around, the AOD determines the direct effect. Or do you mean that the coupled model version has an impact on AOD, due to the different representation of aerosols? This is unclear. Using consistent terminology, as noted above, would help understanding this.
L241: please try to elaborate on the possible reasons for these differences.
L256: same here, please include some insights to support the interpretation of the model results.
L269: this paragraph is also quite descriptive and more interpretation would be useful.
Fig. 9: please speficy that this histogram considers surface values.
L368: these values are not very useful, without a reference to compare with. You may consider showing their relative counterparts as well.Table A1: the caption says that the characteristics of the stations are shown, but it actually shows only their location. If the information about the characteristics (e.g., urban, rural, etc.) is available, please add it.
Technical corrections
L3: radiations → radiation.
L51: the nudging → nudging.
L68: at → on.
L73: modelled pollutants surface concentrations → modelled surface concentration of the pollutants.
L73 and following: The Section → Section.
L97: when → while.
L97: The measurements data → Measurement data.
L209: mi-July → mid-July.
L210: mi-August → mid-August.
L272: may → may be.
L351: strictly speaking, AOD is not a pollutant.
L383: the authors → the authors thank.Citation: https://doi.org/10.5194/gmd-2023-209-RC1 -
RC2: 'Comment on gmd-2023-209', Anonymous Referee #2, 12 Feb 2024
General Comments:
This study compares the impacts of two forcing mechanisms for meteorological fields generated for regional air quality simulations, i.e. spectral nudging of modeled meteorology towards reanalysis fields and feedbacks from aerosols modeled by the air quality model on radiation calculations performed by the meteorological model when air quality and meteorology models are coupled. This topic is of interest to the regional air quality modeling community and very few earlier studies have attempted to address it. The general dominance of the nudging effect over the feedback effect is not unexpected but nevertheless valuable to document in a manuscript, though as suggested in one of my comments below some additional analysis could be performed to assess whether there are exceptions to this general conclusion. The modeling approach employed in this study is straightforward and sound. My main concern with the manuscript is that there is only limited motivation for many of the analysis choices made in Sections 3-4 (i.e. the selection of stations, time periods, latitudinal cross-sections, etc.) and insufficient interpretation of the results shown in the Figures and Tables in terms of the physical and chemical processes causing these results. I would also suggest including a comparison of the four simulations for time periods and locations with the largest aerosol coupling effects (as simulated by the no-nudging configuration). Stratifying results by hour-of-day may provide further mechanistic insights. Finally, the writing of the manuscript would benefit from careful proofreading for language and grammar to improve its clarity and readability.
Specific Comments
Line 2: “nudging”: for readers not familiar with this term, it might be useful to expand this to “nudging of modeled meteorology towards reanalysis fields”. It might also be worth considering to add “often” before “involve” because not all regional-scale model applications utilize either nudging (many applications use frequent meteorological restarts instead) or meteo-chemical coupling.
Figure 1: the interpretation of the arrow and associated text boxes (“resolution”, “species”, “size distrib”) between the pink aerosol boxes is a bit unclear. Is it meant to imply a contradiction between the representation of these aspects in the regional scale vs. global scale context?
Line 152: Does “daily average” imply averaging over zero nighttime values? Or are nighttime values simply not reported and modeled?
Lines 153-154: Are no meteorological observations with higher precision reporting available for this analysis?
Lines 161 – 165: These sentences are an example of where the writing of the manuscript could benefit from careful proofreading for language and grammar.
Table 2 and associated discussion: Please clearly define and distinguish Rs and Ra.
Line 203: Which time period(s) does the statement beginning with “There is no evidence” refer to?
Lines 229 – 231: The results presented later in Table 4 which clearly show a suppressed coupling effect when nudging is employed seem to contradict the conclusion that spectral nudging does not interfere with the effects of aerosol-meteorology coupling. Are the conclusions presented here only applicable to the specific time period and handful of locations analyzed in Section 3.3? If so, a strong caveat to that effect is needed. In addition, it would be interesting to perform this analysis for the locations and time periods where the coupling effect is strongest in the no-nudging case, to quantify the dampening impacts of nudging when and where aerosol feedback effects are most pronounced. It might also help to stratify the analysis by time of day.
Lines 248 – 250. Can you provide a hypothesis or explanation for how nudging impacts aerosol size distributions in this case?
Lines 273 – 275: Can you provide a hypothesis or explanation for these patterns?
Lines 276 – 282 / Figure 8: Please show and discuss all four cases for ozone, just like for water vapor mixing ratio Figure 7
Figure 9 and Table 4: in addition to visualizing and summarizing these time-averaged data points, it might be interesting to prepare a scatter plot of (nonudg_online – nonudg_offline) on the x-axis and (nudg_online – nonudg_online) on the y-axis, with each datapoint in the scatter plot representing one specific hour and grid cell. Such a plot may reveal whether the dampening effect of nudging is potentially more or less pronounced depending on the strength of the undampened coupling effect.
Section 3.6: Aside from some discussion of latitudinal gradients at the end of this section, it is not clear why a latitudinal cross-section was chosen and why it was set up at this particular longitude. The discussion of vertical differences in interesting, but since this analysis is limited to one specific longitude it is unclear how representative these differences are across the domain. It is also not clear how to relate the results for the 3-day period discussed in this section to the rest of the modeling period and the longer-term averages analyzed in the previous sections. An additional way to present results for upper layers across a wider range of conditions might be to calculate vertical profiles averaged over all horizontal grid cells, along with their standard deviations for each layer.
Line 310: I am unclear about the meaning of “The most important changes are in altitude”
Line 331: To help interpret the results for mineral dust emissions, could you please summarize the approach for calculating these emissions and their dependence on meteorology (e.g. wind speed, ambient and/or soil moisture, etc.)?
Lines 336 – 343: Please add some discussion of the mechanisms and processes linking the temperature, wind speed, emissions, and AOD difference patterns shown in Figure 13.
Technical Corrections
Line 4: “processes” instead of “process”
Line 12: “model” instead of “modeling”
Line 14: suggest inserting “for this purpose” after “is used”
Line 18: suggest rephrasing as “On the other hand, for chemistry-transport modeling (CTM) in online mode …”
Line 51: remove comma after “Using the WRF model”
Line 61: change “that” to “than”
Line 68 – 69 and elsewhere in the manuscript: change “pollutants concentrations” to “pollutant concentrations”
Line 71: suggest changing “interplay” to “interact”
Line 72: suggest changing “then it is important” to “making it important”
Lines 73 – 75: remove “the” before “Section”
Lines 82-83: suggest rewording to “The model was configured with and without spectral nudging and with and without taking into account aerosol direct and indirect effects”.
Line 133: suggest replacing “is to date the last distributed one” with “currently is the latest distributed one”
Lines 171 – 172: move “ozone, PM2.5, and PM10” after “the three modeled chemical components”
Line 175: “is less important and the scores are more or less the less” – this is unclear
Line 198: change “contrarily” to “contrary” or “in contrast to”
Line 199: please clarify “at the interface”
Line 207: suggest changing “precise” with “detailed”
Line 210: change “mi-August” to “mid-August”
Line 238: change “that for the surface” to “as for the surface”
Line 249: change “simulation” at the end of the line to “simulations”
Lines 269 – 270: please avoid double occurrence of “particularly”
Line 272: change “may negative” to “may be negative”
Line 328: suggest changing “online or offline” to “online vs. offline”
Line 371: change “lies on the fact” to “lies in the fact”
Lines 373 – 374: suggest rewording “not only because emissions change but also because of feedbacks of aerosols on meteorology”
Citation: https://doi.org/10.5194/gmd-2023-209-RC2 - AC1: 'Comment on gmd-2023-209', Laurent Menut, 11 Mar 2024
Status: closed
-
RC1: 'Reviewer comments on Menut et al. (gmd-2023-209)', Anonymous Referee #1, 09 Jan 2024
This paper presents an analysis on the impact of meteorological nudging and online coupling of aerosol microphysics on selected simulated variables in a regional model.
The results are not very surprising, but still useful for model applications, e.g., for assessment studies. In that sense, I find this study within the scope of GMD.
There are, however, several issues that should be addressed before the paper can be accepted for publication:
- The Results section (Sect. 3) is rather descriptive and no attempt is done by the authors to interpret the results. Some specific features noted on the plots need to be explained in view of the model parametrizations and configurations. This is done only for a few specific cases, but it is missing otherwise.
- Although the authors have access to a quite comprehensive set of stations data (Table A1) they choose to show and discuss only a few stations and their choice is not very well motivated. I think it would be valuable to consider the data from all available stations and try to derive a synthesis from them, for example by applying some kind of statistical metrics to summarize the results and trying to derive a more general conclusion.
- The terminology used to distinguish the coupled / uncoupled model configuration is not consistent, sometimes different terms are used (online/offline, direct/indirect effects). The authors should aim at a more consistent definition of the tested configurations.
- I find the title misleading: the study is not addressing the impact of nudding on aerosol-cloud-radiation interactions, but rather the impact of model coupling on meteorological variables, pollutants concentrations and aerosol optical properties. Please consider a more precise title.
- The presentation quality should be improved: several sentences are unclear and/or hard to read and some of the figures have small fonts or unconvenient colors (see detailed suggestions below).
Specific comments
L5: WRF-CHIMERE coupled model: I would rather write WRF-CHIMERE regional model, in its coupled and uncoupled configuration.
L13: I would explain why, or for which use case, a forcing inside the domain is needed.
L18-19: it would be good to explain how aerosol can modify the meteorology in the model.
L20: it is not clear which forcing is meant here.
Fig. 1: the caption needs to provide more details to help the reader understanding the figure. For example, what is the meaning of the different colors and dashes of the arrows?
L30: this methodological alternative should be discussed again in the conclusions in view of the analysis presented in the paper. Since the paper is mainly addressed to the users of this model, a key-message should be formulated to help them choosing the propert methodology in the future.
L50: in this paragraph, you may consider mentioning Chrysanthou et al. (2019) too (https://doi.org/10.5194/acp-19-11559-2019).
Fig. 2: the two letters identifying the stations are hard to read. It might be wiser numbering the stations instead (here and in Table A1). The choice of the colors is not optimal for color-blinded readers. Please consider alternative colors.
L84: I would suggest naming Sect. 2.1 Model parameterizations and providing a few more details about the parametrizations themselves. For example, about the cloud scheme and how this can be coupled to the aerosol microphysics (which I guess is part of CHIMERE described below).
L96: I am not sure that grid nudging applied over all grid cells is necessarily an advantage, since this does not allow to limit the nudging to certain scales. Moreover, the fact that spectral nudging is less intrusive depends on its configuration and whether, for instance, wave-0 nudging is considered or not. Please clarify.
L103: what do you mean with perturbation of the geopotential? What is the source of this perturbation? Please specify.
L113: I find the remaining of this section quite hard to follow. I would suggest providing clear mathematical definitions for the nudging coefficients and to be more specific on how the calculations of the wave numbers (Eq. 1) are considered in the nudging scheme. Is this a maximum wave number for which spectral nudging is applied?
L133: I would add an introductory sentence to make clear the CHIMERE is an aerosol-chemistry scheme which is used when running WRF in online mode (if I understood correctly). Is this online mode only considering the impact of aerosol or also the impact of chemistry (e.g. ozone impact on radiation)?
L133: to take into account the direct effects of aerosol on clouds and radiation. This sentence is unclear, also in relation with the following sentence. If I interpreted it correctly, you mean that CHIMERE can account for both aerosol-radiation and aerosol-cloud interactions. If this is the case, I would also add a short explanation on how this is achieved technically. Referring to other publications is not enough, the text should be self explanatory, at least concerning the basic functionalities of the model.
L140: the aerosol microphysics simulated by the model should also be mentioned (which processes and species are considered?).
L158: please list the applied statistical scores here with their full name (the table just show their symbol).
L162: please provide an example of such local features (orography?).
L165: the last sentence of this paragraph is unclear. Please consider rephrasing.
Table 2: please be more specific on the procedure applied to aggregate the statistical scores.
L174: The impact of the coupling is less important and the scores are more or less the less with and without the coupling. Do you mean, the scores are quite similar independently of the coupling mode?
L179: ...there is no clear impact of the use of the direct effects or nor on the scores. This is an example where the use of different terminology (main comment 3 above) makes the text hard to understand. What do you mean with the use of the direct effects? Are you referring to coupled vs. uncoupled model? Please clarify.
L188: what is the reason for showing and discussing only the stations data for Orléans and Bordeaux? As noted in the main comment 2 above, you have a valuable set of measurements and you should take full advantage of them.
L190: I would consider adding the results for the other stations to a supplement.
Fig. 3: the left and right panels have the same titles, but show different variables. Please add the variable name to the title, e.g. Bordeaux (daily mean) - Temperature or similar. Do the right panels show the 10m wind speed or only its u-component (as indicated on the y-axis)? Please specify. The legend is very small and hard to read: since it is the same for all panels, you may consider a common legend at the bottom of the plot. Please also use more friendly colors (see above comment on Fig. 1). The same applies to Fig. 4.
L199: what is meant with interface here?
L203: why do the nudged simulations performed better, given that wind nudging is not effective at small scales? Or am I missing something?
L214: It is difficult to disentangle the several simulations and to diagnose the best scores without statistical calculations. Why not performing such analysis? These scores have been computed for temperature and wind speed, it should not be too difficult to repeat the analysis for ozone, PM and AOD.
L234: as above, please motivate the choice of these three stations. Although, I note again that including all stations would significantly improve the analysis.
L240: How are the direct/indirect effects impact the AOD? It is actually the other way around, the AOD determines the direct effect. Or do you mean that the coupled model version has an impact on AOD, due to the different representation of aerosols? This is unclear. Using consistent terminology, as noted above, would help understanding this.
L241: please try to elaborate on the possible reasons for these differences.
L256: same here, please include some insights to support the interpretation of the model results.
L269: this paragraph is also quite descriptive and more interpretation would be useful.
Fig. 9: please speficy that this histogram considers surface values.
L368: these values are not very useful, without a reference to compare with. You may consider showing their relative counterparts as well.Table A1: the caption says that the characteristics of the stations are shown, but it actually shows only their location. If the information about the characteristics (e.g., urban, rural, etc.) is available, please add it.
Technical corrections
L3: radiations → radiation.
L51: the nudging → nudging.
L68: at → on.
L73: modelled pollutants surface concentrations → modelled surface concentration of the pollutants.
L73 and following: The Section → Section.
L97: when → while.
L97: The measurements data → Measurement data.
L209: mi-July → mid-July.
L210: mi-August → mid-August.
L272: may → may be.
L351: strictly speaking, AOD is not a pollutant.
L383: the authors → the authors thank.Citation: https://doi.org/10.5194/gmd-2023-209-RC1 -
RC2: 'Comment on gmd-2023-209', Anonymous Referee #2, 12 Feb 2024
General Comments:
This study compares the impacts of two forcing mechanisms for meteorological fields generated for regional air quality simulations, i.e. spectral nudging of modeled meteorology towards reanalysis fields and feedbacks from aerosols modeled by the air quality model on radiation calculations performed by the meteorological model when air quality and meteorology models are coupled. This topic is of interest to the regional air quality modeling community and very few earlier studies have attempted to address it. The general dominance of the nudging effect over the feedback effect is not unexpected but nevertheless valuable to document in a manuscript, though as suggested in one of my comments below some additional analysis could be performed to assess whether there are exceptions to this general conclusion. The modeling approach employed in this study is straightforward and sound. My main concern with the manuscript is that there is only limited motivation for many of the analysis choices made in Sections 3-4 (i.e. the selection of stations, time periods, latitudinal cross-sections, etc.) and insufficient interpretation of the results shown in the Figures and Tables in terms of the physical and chemical processes causing these results. I would also suggest including a comparison of the four simulations for time periods and locations with the largest aerosol coupling effects (as simulated by the no-nudging configuration). Stratifying results by hour-of-day may provide further mechanistic insights. Finally, the writing of the manuscript would benefit from careful proofreading for language and grammar to improve its clarity and readability.
Specific Comments
Line 2: “nudging”: for readers not familiar with this term, it might be useful to expand this to “nudging of modeled meteorology towards reanalysis fields”. It might also be worth considering to add “often” before “involve” because not all regional-scale model applications utilize either nudging (many applications use frequent meteorological restarts instead) or meteo-chemical coupling.
Figure 1: the interpretation of the arrow and associated text boxes (“resolution”, “species”, “size distrib”) between the pink aerosol boxes is a bit unclear. Is it meant to imply a contradiction between the representation of these aspects in the regional scale vs. global scale context?
Line 152: Does “daily average” imply averaging over zero nighttime values? Or are nighttime values simply not reported and modeled?
Lines 153-154: Are no meteorological observations with higher precision reporting available for this analysis?
Lines 161 – 165: These sentences are an example of where the writing of the manuscript could benefit from careful proofreading for language and grammar.
Table 2 and associated discussion: Please clearly define and distinguish Rs and Ra.
Line 203: Which time period(s) does the statement beginning with “There is no evidence” refer to?
Lines 229 – 231: The results presented later in Table 4 which clearly show a suppressed coupling effect when nudging is employed seem to contradict the conclusion that spectral nudging does not interfere with the effects of aerosol-meteorology coupling. Are the conclusions presented here only applicable to the specific time period and handful of locations analyzed in Section 3.3? If so, a strong caveat to that effect is needed. In addition, it would be interesting to perform this analysis for the locations and time periods where the coupling effect is strongest in the no-nudging case, to quantify the dampening impacts of nudging when and where aerosol feedback effects are most pronounced. It might also help to stratify the analysis by time of day.
Lines 248 – 250. Can you provide a hypothesis or explanation for how nudging impacts aerosol size distributions in this case?
Lines 273 – 275: Can you provide a hypothesis or explanation for these patterns?
Lines 276 – 282 / Figure 8: Please show and discuss all four cases for ozone, just like for water vapor mixing ratio Figure 7
Figure 9 and Table 4: in addition to visualizing and summarizing these time-averaged data points, it might be interesting to prepare a scatter plot of (nonudg_online – nonudg_offline) on the x-axis and (nudg_online – nonudg_online) on the y-axis, with each datapoint in the scatter plot representing one specific hour and grid cell. Such a plot may reveal whether the dampening effect of nudging is potentially more or less pronounced depending on the strength of the undampened coupling effect.
Section 3.6: Aside from some discussion of latitudinal gradients at the end of this section, it is not clear why a latitudinal cross-section was chosen and why it was set up at this particular longitude. The discussion of vertical differences in interesting, but since this analysis is limited to one specific longitude it is unclear how representative these differences are across the domain. It is also not clear how to relate the results for the 3-day period discussed in this section to the rest of the modeling period and the longer-term averages analyzed in the previous sections. An additional way to present results for upper layers across a wider range of conditions might be to calculate vertical profiles averaged over all horizontal grid cells, along with their standard deviations for each layer.
Line 310: I am unclear about the meaning of “The most important changes are in altitude”
Line 331: To help interpret the results for mineral dust emissions, could you please summarize the approach for calculating these emissions and their dependence on meteorology (e.g. wind speed, ambient and/or soil moisture, etc.)?
Lines 336 – 343: Please add some discussion of the mechanisms and processes linking the temperature, wind speed, emissions, and AOD difference patterns shown in Figure 13.
Technical Corrections
Line 4: “processes” instead of “process”
Line 12: “model” instead of “modeling”
Line 14: suggest inserting “for this purpose” after “is used”
Line 18: suggest rephrasing as “On the other hand, for chemistry-transport modeling (CTM) in online mode …”
Line 51: remove comma after “Using the WRF model”
Line 61: change “that” to “than”
Line 68 – 69 and elsewhere in the manuscript: change “pollutants concentrations” to “pollutant concentrations”
Line 71: suggest changing “interplay” to “interact”
Line 72: suggest changing “then it is important” to “making it important”
Lines 73 – 75: remove “the” before “Section”
Lines 82-83: suggest rewording to “The model was configured with and without spectral nudging and with and without taking into account aerosol direct and indirect effects”.
Line 133: suggest replacing “is to date the last distributed one” with “currently is the latest distributed one”
Lines 171 – 172: move “ozone, PM2.5, and PM10” after “the three modeled chemical components”
Line 175: “is less important and the scores are more or less the less” – this is unclear
Line 198: change “contrarily” to “contrary” or “in contrast to”
Line 199: please clarify “at the interface”
Line 207: suggest changing “precise” with “detailed”
Line 210: change “mi-August” to “mid-August”
Line 238: change “that for the surface” to “as for the surface”
Line 249: change “simulation” at the end of the line to “simulations”
Lines 269 – 270: please avoid double occurrence of “particularly”
Line 272: change “may negative” to “may be negative”
Line 328: suggest changing “online or offline” to “online vs. offline”
Line 371: change “lies on the fact” to “lies in the fact”
Lines 373 – 374: suggest rewording “not only because emissions change but also because of feedbacks of aerosols on meteorology”
Citation: https://doi.org/10.5194/gmd-2023-209-RC2 - AC1: 'Comment on gmd-2023-209', Laurent Menut, 11 Mar 2024
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