the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 26 Aug 2022
Development of an ecophysiology module in the GEOS-Chem chemical transport model version 12.2.0 to represent biosphere−atmosphere fluxes relevant for ozone air quality
Abstract. Ground-level ozone (O3) is a major air pollutant that adversely affects human health and agricultural productivity. Removal of air pollutants including tropospheric O3 from the atmosphere by vegetation is controlled mostly by the process of dry deposition, an important component of which is plant stomatal uptake that can in turn cause damage to plant tissues with ramifications for ecosystem and crop health. In many atmospheric and land surface models, the openness of plant stomata is represented by a bulk stomatal conductance, which is often semi-empirically parameterized, and highly fitted to historical observations. A lack of mechanistic linkage to ecophysiological processes such as photosynthesis may render models insufficient to represent plant-mediated responses of atmospheric chemistry to long-term changes in CO2, climate and short-lived air pollutant concentrations. A new ecophysiology module was thus developed to mechanistically simulate land−atmosphere exchange of important gas species in GEOS-Chem, a chemical transport model widely used in atmospheric chemistry studies. We adopted the formulations from the Joint UK Land Environmental Simulator (JULES) to couple photosynthesis rate, bulk stomatal conductance and isoprene emission rate dynamically. The implementation not only allows dry deposition to be coupled with plant ecophysiology, but also enables plant and crop productivity and functions to respond dynamically to atmospheric chemical changes. The research questions of this study include: 1) how the new ecophysiology module compares with the prior, semi-empirical parameterization in terms of simulating concentration and dry deposition velocity of O3 with respect to site measurement-based estimates; and 2) whether the ecophysiology module simulates vegetation productivity, dry deposition, isoprene emission rate and O3–vegetation interactions reasonably under a present-day and an elevated CO2 concentration. We conduct simulations to evaluate the effects of the ecophysiology module on simulated dry deposition velocity and concentration of surface O3 against an observation-derived dataset known as SynFlux. Our estimated dry deposition velocity of O3 is close to SynFlux dry deposition velocity with root-mean-squared errors (RMSE) ranging from 0.1 to 0.2 cm s–1 across different plant functional types (PFTs), despite an overall positive bias in surface O3 concentration (by up to 16 ppbv). Representing ecophysiology was found to reduce the simulated biases in deposition fluxes from the prior model, but worsen the positive biases in simulated O3 concentrations. The increase in positive concentration biases is mostly attributable to the ecophysiology-based stomatal conductance being generally smaller (and closer to SynFlux values) than that estimated by the prior semi-empirical formulation, calling for further improvements in non-depositional processes relevant for O3 simulations. Estimated global O3 deposition flux is 864 Tg O3 yr–1 with GEOS-Chem, and the new module decreases this estimate by 92 Tg O3 yr–1. Estimated global gross primary product (GPP) is 119 Pg C yr–1, with an O3-induced damage of 4.2 Pg C yr–1 (3.5 %). An elevated CO2 scenario (580 ppm) yields higher global GPP (+16.8 %) and lower global O3 depositional sink (–3.3 %). Global isoprene emission simulated with a photosynthesis-based scheme is 318 Tg C yr–1, which is 31 Tg C yr−1 (−8.9 %) less than that calculated using the MEGAN emission algorithm. This new model development dynamically represents the two-way interactions between vegetation and air pollutants, and thus provides a unique capability in evaluating pollutant impacts on vegetation health and feedback processes that can shape atmospheric chemistry and air quality especially for any timescales shorter than the multidecadal timescale.
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RC1: 'Comment on egusphere-2022-786', Anonymous Referee #1, 09 Oct 2022
In this work, an ecophysiology module was implemented in the GEOS-Chem model. The dry deposition velocity of O3, vegetation productivity, isoprene emission rate, as well as O3 vegetation damage, were simulated under both present-day and elevated CO2 concentration scenarios. The coupling of vegetation processes with CTM is an important update for studying the interactions between ecosystem and atmospheric chemistry. However, the effectiveness of the ecophysiology module was not sufficiently evaluated. Before the possible publication in GMD, I suggest the authors enrich this manuscript in the following aspects to further strengthen the validations and calibrations of key biophysical processes.
Here are some main concerns:
1. The case 1a experiment is the baseline of this study. It shows some improvements in simulating Vd in Figure 3 compared with case 0. However, the explanation for such changes is almost like no explanations: “The more significant decreases in vd for broadleaf trees and needleleaf trees than for other PFTs are only due to the differences in formulations, but not due to any other physical reasons.” Why it becomes smaller? Differences in what formulations? I think the improvement is limited, as there are still obvious PFT-specific biases in baseline Case 1a. For example, the Vd of needleleaf is much lower than observations. Is it because of the scaling by βt, which turns down the Vd for deciduous trees and consequently decreases the Vd for needleleaf trees as well?
2. In Figure 3, the ecophysiology module seems significantly affected by βt. The larger the parameter, the higher the Vd. This factor is emphasized in the analysis of improvement from Case 0 to Case1a. However, such implementation introduces two problems/uncertainties into the model. First, observations do not always show the dependence of Vd on soil moisture, especially for needleleaf trees and some C3 grassland. Second, the calculation of βt is dependent on data from MERRA2. It’s unclear how accurate are the MERRA2 soil moisture data. For the first point, the updated model will show incorrect responses of Vd to moderate drought. For the second point, both the spatial and temporal biases in the soil moisture of reanalyses data will affect the simulated An, gs, and Vd, but to what extent remains unclear.
3. Figure 4 shows the coupling of the ecophysiology module worsens the simulation of surface ozone. Although the authors tried to explain the causes, these results diminish the meaning of the model improvement with ecophysiology module. Considering that the new module has limited and even negative effects on the ozone simulations, more solid evaluations of carbon cycle modeling is needed rather than three lines of demonstration of “our results demonstrate a seasonal cycle of GPP that peaks at around 130 g C m−2 month−1 in July and falls steadily to around 60 g C m−2 month−1 in February. This resembles with observation-derived datasets like FLUXNET-MTE, as shown in Fig. 3a of Slevin et al. (2017)” (in Line 472-474). For example, site-based evaluations for GPP, stomatal conductance gs, and O3 stomata flux are all crucial. The SynFlux dataset includes these variables in addition O3 concentrations and O3 deposition velocity for further evaluation.
4. The response sensitivity of GPP to CO2 and the damage sensitivity of O3 to GPP highly rely on key parameters originally adapted in JULES rather than the ecophysiology module implemented in this study. Necessary validations or calibrations for these two sensitivities should be conducted within this whole different framework.
5. Line 607: “In particular, LAI does not change dynamically with climatic conditions or O3 damage in the current model”. To what extent the LAI dataset is fixed? Is this a reasonable configuration? LAI is a key parameter regulating carbon fixation, ozone dry deposition, and isoprene emissions. Such omission will likely weaken the interactions between atmosphere chemistry and biosphere especially when CO2 fertilization is considered.
Specific comments:
Abstract: The abstract is too lengthy. It can be truncated by half.
Line 139-141: “This approach is particularly useful for examining how ecosystem structure may respond to long-term atmospheric chemical changes over multidecadal timescales, but may be unnecessarily computationally expensive for problems involving shorter timescales…It also introduces extra uncertainties that arise from the computation of ecosystem structure, which involves complex representation of plant phenology and biogeochemistry”. Biospheric calculation is normally not the resource-consuming part in the atmospheric-chemistry-involved simulations. Are there any comparisons in speed and uncertainty with other CTM with a biosphere model?
Equation 11: How is this related to stomatal conductance and how to get the closed relationships among An, Gs, and Cc from this additional equation?
Line 358-359: “Figure 2 shows the locations of 36 SynFlux sites used in our evaluation of the ecophysiology module”. What are the selection criteria for these sites?
Line 398: “resistance” should be conductance.
Line 461: “We note also that such changes in GPP is entirely due to higher photosynthetic rate, and no changes in LAI are simulated”. Isn’t LAI prescribed? “.. changes in GPP is..”, should be “..are..”.
Figures 3 and 4: The inclusion of ozone damage doesn’t cause significant changes to Vd and ozone. I suggest remove the first two columns.
Figure 8d: Why the O3-damage-induced isoprene emission reduction doesn’t match O3 damage in Figure 5c. For example, the high O3 damages in eastern U.S. show limited impacts on the regional isoprene emissions.
Citation: https://doi.org/10.5194/egusphere-2022-786-RC1 -
RC2: 'Comment on egusphere-2022-786', Anonymous Referee #2, 25 Nov 2022
This is a rather technical paper showing the sensitivity of GEOS-Chem O3 concentrations to the implementation of a ecophysiological module, substituting the 'canonical' Wesely type of model, which is standardly included in GeosChem and many other CTMs. This allows addressing two specific air pollution interactions: O3 damage and isoprene emissions.
A third element of the paper is dealing with issues around appropriately dealing with soil water, and atmospheric water vapor deficit.Overall, explicit/interactive inclusion O3 damage has a relatively small impact on calculated vd. Inclusion of the ecophysiological module (vs conventional) deteriorates the overall performance of GEOSchem, with positive biases further increasing.I have a number of major remarks and a number of minor comments below.
1. the paper is somewhat tedious to read- there is a lot of text, and the paper is trying perhaps to deal with too many issues at the same time, somewhat diluting the story. To reach a wider audience the authors may want to consider to bring somewhat more focus in the paper. If not the current paper is probably fine for a more specialised audience.
A possible suggestion is to move a lot of the detailed information (derived from literature sources) in section 2.1 to appendices.2. Mechanistically the proposed parameterisation is a sensible improvement of the existing deposition scheme. Quantitatively the improvement is less convincing. There is a quantitative comparison to Synflux 'observed' deposition velocities,
suggesting important improvements for some PFT (broadleaf); deterioration for needleleaft, and moderate improvement for C3 grass and shrubs. This comparison assumes that the Synflux database is perfectly suitable for comparison with very coarse grid models
like GEOSCHEM. More attention should be paid to this aspect. And conclusions should be adjusted in view of the uncertainty of the comparison to Synflux.3. Appropriate description of soil water and Watervapor deficit is a well known fact for reliable model performance of ecological and crop models - it is difficult to imagine how a coarse CTM can credibly tackle this issue- where even fine meshed models around 10 km are struggling to get this right. Where the paper is flagging the issue, it is not clear what we learned from this paper.
4. Model simulations and impacts on O3 are performed by one year simulations. If I have understand it correctly, there is no spin-up considered, which can give rise to results that are not yet in equilibrium. Common practice would be to have at least half a year of spin-up for the various simulations to capture the atmospheric feedbacks through components as CO and PAN. I would expect that the results would change somewhat, but the overall qualitative findings wouldn't. If the authors performed the spin-up properly they should mention it.
5. The authors conclude that 'non-depositional' processes must be the root-cause of bias in GEOS-chem, implicitly assuming that the 'stomatal' ozone uptake it calculated perfectly with the new scheme. In my opinion this conclusion should be phrased more carefully, as the performance of GEOSCHEM deposition velocities is not very convincing (and we do not even know to what extent the Synflux points can be compared to 2 degree model). Plenty of factors (e.g. soil moisture) are not well captured in the model that will influence stomatal exchange.
All in all this parameterisation is the right way forward, and I would recommend to accept the paper after adequatly addressing the major and minor comments.
Detailed comments
13 not only agricultural productivity; more generally also ecosystem productivity.
14 The statement depends somewhat on the specific air pollutant- e.g. dry deposition is relatively unimportant for aerosol. It is correct for O3 perse. Please change.
15 openess of stomata is represented by stomatal conductance sounds strange. Suggest: The functionality of stomatal opening
17 insufficient=>inadequate
35 how can we be sure this is 'non-depositional' processes? Non-stomatal deposition can also be important, the comparison to Synflux possibly not correct, etc...
37 the 119 Pg includes the O3 damage or not? Clarify. Same for the CO2 scenario.
45-48 The seminal papers of Mills et al should be included in crop/food security impacts.
68 Not sure what you mean with adhere versus absorb. The most simple definition would be: uptake at the earth surface by soil water or vegetation. Also the turbulent transfer is only partly correct, as there is usually one step that
is determined by molecular diffusion.
84 I do not know to what extent Kavassalis and Murphy talked about causal relationship between O3 and VPD. Did they suggest the vegetation as regulating, or is that yur own connclusion?
115-119 It would be good to clarify in abstract/conclusion which of these your paper has addressed and which not.
198 A lot of text currently in section 2.1 could go to an appendix (as it mostly listing what came from other publications), and instead the section could highlight what particular assumptions were made for this paper.
273 The main problem is that higher resolutions are needed to get reliable soil moisture- 0.5 is insufficient, and the GEOSCHEM 2.5 degree is even more insufficient- in particular when comparing to the fluxnet data.
276 The Sitch et al paper was a seminal paper, but there is much data since then that can give better information than 'high and low' sensitive. I would like to a stronger argument why this is still a viable approach.
300 what is priorGEOS-CHEM?
320-325 There is insufficient information in this paper to understand what was done with the model spin-up. In general one would need at least half of year of spin-up for the atmospheric component. Please clarify.330 case 0 means that in stead the Wesely scheme is used?
333-335 if the authors want to simulate the effect of changing CO2, one should use only vary CO2 and not the meteorology. Please clarify.
339 suggested by whom?
360 The errors in SynFlux have been shown to be modest compared with differences between observations and regional and global CTMs that are frequently a factor of two or more, illustrating its utility for evaluating models (Ducker et al., 2018).
This statement can indeed be found in Ducker et al. To me it is not clear in the original paper what exactly is meant by this statement, which is without discussion copied here.375 The Synflux PFT vd dataset needs to be better described including a description of their uncertainties.
396-404 The discussion of the soil moisture stress factor versus vd shows clearly that the parameteristation is not working well for 3 out of 4 PFTs. The paper should discuss how this limits the analysis and overall conclusions (beyond what is discussed in 407-415 which should be moved to discussion section, because it is a major limitation)
. It also not clear why the issues of VPD was left to 'further investigation'?
415 observed concentrations?
447 range of global depositions from these studies?
450 it would be helpful for Table 3 to give along with the case 2a,2b etc a short descriptor what again the case was (to avoid scrolling up and down all the time).
455 please elucidate whether only CO2 was modified in these scenarios, or also emissions and other climate parameters.
460 to which cases does this refer ?
465 Somewhere it needs to be explained why the comparison to the Franks paper is important? Because it is widely used, or rather comparing something more complex to a very simple approach?
467 this not percent but percent points (leave the -20 to -10; it always helps to explain the concept).
468 this is a strange sentence. Of course it can capture this, because you coded it like this. Propose to rephrase (and move to conclusion). I believe that there have been some other literature estimates of the CO2/O3 damage interactions- please discuss these.
509 what is HEMCOv2.1? A static estimate, a parameterisation, what can we learn from this comparison?
515-520 what is the influence of just 4 PFTs versus more detailed forest types in MEGAN, why do the patterns in S. America look so different (probably not temperature alone).
545-552 is not really for conclusion- but rather a motiviation for this study in an introduction. Cut?
577 Can non-stomatal deposition be excluded as a source of error. How can you be so sure that the deposition is now done 'correctly' Is their some uncrtainty anlysis below this that can corroborate this statement?
578 Not sure what you mean with capable: is this statement based on a quantification of uncertainties, or do you rather mean 'able'?
582 what did Yue and Unger find in %? Explain what you want to say with 'who applied... GPP"
583 elevated CO2 and current O3?
585 difference in global O3 deposition can also be due to assumptions on ocean O3 deposition.
618 This discussion on limitation of using Synflux needs to be expanded. 1) the Synflux method was only tested with 'observed' vd at 3 sites. At these sites the performance was quite good. This is of course the best they could do, but it is not really convicning evidence that the performance elsewhere will also be good. 2) A real issue is how to compare coarse grid output to point measurements.
3) limitations of the soil parameterisation.Citation: https://doi.org/10.5194/egusphere-2022-786-RC2 -
AC1: 'Comment on egusphere-2022-786', Amos Tai, 20 Feb 2023
We would like to thank the reviewers for the thoughtful and insightful comments. The manuscript has been revised accordingly, and our point-by-point responses are provided in the file attached to this comment. The revised manuscript with tracked changes is also included in the linked file below for the Editor’s easy reference:
https://gocuhk-my.sharepoint.com/:b:/g/personal/amostai_cuhk_edu_hk/Eeq-mbYlq8pBvK7Bg-lS6z4B83QzuwiVKUltASZlpMVYxA?e=fvkKJz
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2022-786', Anonymous Referee #1, 09 Oct 2022
In this work, an ecophysiology module was implemented in the GEOS-Chem model. The dry deposition velocity of O3, vegetation productivity, isoprene emission rate, as well as O3 vegetation damage, were simulated under both present-day and elevated CO2 concentration scenarios. The coupling of vegetation processes with CTM is an important update for studying the interactions between ecosystem and atmospheric chemistry. However, the effectiveness of the ecophysiology module was not sufficiently evaluated. Before the possible publication in GMD, I suggest the authors enrich this manuscript in the following aspects to further strengthen the validations and calibrations of key biophysical processes.
Here are some main concerns:
1. The case 1a experiment is the baseline of this study. It shows some improvements in simulating Vd in Figure 3 compared with case 0. However, the explanation for such changes is almost like no explanations: “The more significant decreases in vd for broadleaf trees and needleleaf trees than for other PFTs are only due to the differences in formulations, but not due to any other physical reasons.” Why it becomes smaller? Differences in what formulations? I think the improvement is limited, as there are still obvious PFT-specific biases in baseline Case 1a. For example, the Vd of needleleaf is much lower than observations. Is it because of the scaling by βt, which turns down the Vd for deciduous trees and consequently decreases the Vd for needleleaf trees as well?
2. In Figure 3, the ecophysiology module seems significantly affected by βt. The larger the parameter, the higher the Vd. This factor is emphasized in the analysis of improvement from Case 0 to Case1a. However, such implementation introduces two problems/uncertainties into the model. First, observations do not always show the dependence of Vd on soil moisture, especially for needleleaf trees and some C3 grassland. Second, the calculation of βt is dependent on data from MERRA2. It’s unclear how accurate are the MERRA2 soil moisture data. For the first point, the updated model will show incorrect responses of Vd to moderate drought. For the second point, both the spatial and temporal biases in the soil moisture of reanalyses data will affect the simulated An, gs, and Vd, but to what extent remains unclear.
3. Figure 4 shows the coupling of the ecophysiology module worsens the simulation of surface ozone. Although the authors tried to explain the causes, these results diminish the meaning of the model improvement with ecophysiology module. Considering that the new module has limited and even negative effects on the ozone simulations, more solid evaluations of carbon cycle modeling is needed rather than three lines of demonstration of “our results demonstrate a seasonal cycle of GPP that peaks at around 130 g C m−2 month−1 in July and falls steadily to around 60 g C m−2 month−1 in February. This resembles with observation-derived datasets like FLUXNET-MTE, as shown in Fig. 3a of Slevin et al. (2017)” (in Line 472-474). For example, site-based evaluations for GPP, stomatal conductance gs, and O3 stomata flux are all crucial. The SynFlux dataset includes these variables in addition O3 concentrations and O3 deposition velocity for further evaluation.
4. The response sensitivity of GPP to CO2 and the damage sensitivity of O3 to GPP highly rely on key parameters originally adapted in JULES rather than the ecophysiology module implemented in this study. Necessary validations or calibrations for these two sensitivities should be conducted within this whole different framework.
5. Line 607: “In particular, LAI does not change dynamically with climatic conditions or O3 damage in the current model”. To what extent the LAI dataset is fixed? Is this a reasonable configuration? LAI is a key parameter regulating carbon fixation, ozone dry deposition, and isoprene emissions. Such omission will likely weaken the interactions between atmosphere chemistry and biosphere especially when CO2 fertilization is considered.
Specific comments:
Abstract: The abstract is too lengthy. It can be truncated by half.
Line 139-141: “This approach is particularly useful for examining how ecosystem structure may respond to long-term atmospheric chemical changes over multidecadal timescales, but may be unnecessarily computationally expensive for problems involving shorter timescales…It also introduces extra uncertainties that arise from the computation of ecosystem structure, which involves complex representation of plant phenology and biogeochemistry”. Biospheric calculation is normally not the resource-consuming part in the atmospheric-chemistry-involved simulations. Are there any comparisons in speed and uncertainty with other CTM with a biosphere model?
Equation 11: How is this related to stomatal conductance and how to get the closed relationships among An, Gs, and Cc from this additional equation?
Line 358-359: “Figure 2 shows the locations of 36 SynFlux sites used in our evaluation of the ecophysiology module”. What are the selection criteria for these sites?
Line 398: “resistance” should be conductance.
Line 461: “We note also that such changes in GPP is entirely due to higher photosynthetic rate, and no changes in LAI are simulated”. Isn’t LAI prescribed? “.. changes in GPP is..”, should be “..are..”.
Figures 3 and 4: The inclusion of ozone damage doesn’t cause significant changes to Vd and ozone. I suggest remove the first two columns.
Figure 8d: Why the O3-damage-induced isoprene emission reduction doesn’t match O3 damage in Figure 5c. For example, the high O3 damages in eastern U.S. show limited impacts on the regional isoprene emissions.
Citation: https://doi.org/10.5194/egusphere-2022-786-RC1 -
RC2: 'Comment on egusphere-2022-786', Anonymous Referee #2, 25 Nov 2022
This is a rather technical paper showing the sensitivity of GEOS-Chem O3 concentrations to the implementation of a ecophysiological module, substituting the 'canonical' Wesely type of model, which is standardly included in GeosChem and many other CTMs. This allows addressing two specific air pollution interactions: O3 damage and isoprene emissions.
A third element of the paper is dealing with issues around appropriately dealing with soil water, and atmospheric water vapor deficit.Overall, explicit/interactive inclusion O3 damage has a relatively small impact on calculated vd. Inclusion of the ecophysiological module (vs conventional) deteriorates the overall performance of GEOSchem, with positive biases further increasing.I have a number of major remarks and a number of minor comments below.
1. the paper is somewhat tedious to read- there is a lot of text, and the paper is trying perhaps to deal with too many issues at the same time, somewhat diluting the story. To reach a wider audience the authors may want to consider to bring somewhat more focus in the paper. If not the current paper is probably fine for a more specialised audience.
A possible suggestion is to move a lot of the detailed information (derived from literature sources) in section 2.1 to appendices.2. Mechanistically the proposed parameterisation is a sensible improvement of the existing deposition scheme. Quantitatively the improvement is less convincing. There is a quantitative comparison to Synflux 'observed' deposition velocities,
suggesting important improvements for some PFT (broadleaf); deterioration for needleleaft, and moderate improvement for C3 grass and shrubs. This comparison assumes that the Synflux database is perfectly suitable for comparison with very coarse grid models
like GEOSCHEM. More attention should be paid to this aspect. And conclusions should be adjusted in view of the uncertainty of the comparison to Synflux.3. Appropriate description of soil water and Watervapor deficit is a well known fact for reliable model performance of ecological and crop models - it is difficult to imagine how a coarse CTM can credibly tackle this issue- where even fine meshed models around 10 km are struggling to get this right. Where the paper is flagging the issue, it is not clear what we learned from this paper.
4. Model simulations and impacts on O3 are performed by one year simulations. If I have understand it correctly, there is no spin-up considered, which can give rise to results that are not yet in equilibrium. Common practice would be to have at least half a year of spin-up for the various simulations to capture the atmospheric feedbacks through components as CO and PAN. I would expect that the results would change somewhat, but the overall qualitative findings wouldn't. If the authors performed the spin-up properly they should mention it.
5. The authors conclude that 'non-depositional' processes must be the root-cause of bias in GEOS-chem, implicitly assuming that the 'stomatal' ozone uptake it calculated perfectly with the new scheme. In my opinion this conclusion should be phrased more carefully, as the performance of GEOSCHEM deposition velocities is not very convincing (and we do not even know to what extent the Synflux points can be compared to 2 degree model). Plenty of factors (e.g. soil moisture) are not well captured in the model that will influence stomatal exchange.
All in all this parameterisation is the right way forward, and I would recommend to accept the paper after adequatly addressing the major and minor comments.
Detailed comments
13 not only agricultural productivity; more generally also ecosystem productivity.
14 The statement depends somewhat on the specific air pollutant- e.g. dry deposition is relatively unimportant for aerosol. It is correct for O3 perse. Please change.
15 openess of stomata is represented by stomatal conductance sounds strange. Suggest: The functionality of stomatal opening
17 insufficient=>inadequate
35 how can we be sure this is 'non-depositional' processes? Non-stomatal deposition can also be important, the comparison to Synflux possibly not correct, etc...
37 the 119 Pg includes the O3 damage or not? Clarify. Same for the CO2 scenario.
45-48 The seminal papers of Mills et al should be included in crop/food security impacts.
68 Not sure what you mean with adhere versus absorb. The most simple definition would be: uptake at the earth surface by soil water or vegetation. Also the turbulent transfer is only partly correct, as there is usually one step that
is determined by molecular diffusion.
84 I do not know to what extent Kavassalis and Murphy talked about causal relationship between O3 and VPD. Did they suggest the vegetation as regulating, or is that yur own connclusion?
115-119 It would be good to clarify in abstract/conclusion which of these your paper has addressed and which not.
198 A lot of text currently in section 2.1 could go to an appendix (as it mostly listing what came from other publications), and instead the section could highlight what particular assumptions were made for this paper.
273 The main problem is that higher resolutions are needed to get reliable soil moisture- 0.5 is insufficient, and the GEOSCHEM 2.5 degree is even more insufficient- in particular when comparing to the fluxnet data.
276 The Sitch et al paper was a seminal paper, but there is much data since then that can give better information than 'high and low' sensitive. I would like to a stronger argument why this is still a viable approach.
300 what is priorGEOS-CHEM?
320-325 There is insufficient information in this paper to understand what was done with the model spin-up. In general one would need at least half of year of spin-up for the atmospheric component. Please clarify.330 case 0 means that in stead the Wesely scheme is used?
333-335 if the authors want to simulate the effect of changing CO2, one should use only vary CO2 and not the meteorology. Please clarify.
339 suggested by whom?
360 The errors in SynFlux have been shown to be modest compared with differences between observations and regional and global CTMs that are frequently a factor of two or more, illustrating its utility for evaluating models (Ducker et al., 2018).
This statement can indeed be found in Ducker et al. To me it is not clear in the original paper what exactly is meant by this statement, which is without discussion copied here.375 The Synflux PFT vd dataset needs to be better described including a description of their uncertainties.
396-404 The discussion of the soil moisture stress factor versus vd shows clearly that the parameteristation is not working well for 3 out of 4 PFTs. The paper should discuss how this limits the analysis and overall conclusions (beyond what is discussed in 407-415 which should be moved to discussion section, because it is a major limitation)
. It also not clear why the issues of VPD was left to 'further investigation'?
415 observed concentrations?
447 range of global depositions from these studies?
450 it would be helpful for Table 3 to give along with the case 2a,2b etc a short descriptor what again the case was (to avoid scrolling up and down all the time).
455 please elucidate whether only CO2 was modified in these scenarios, or also emissions and other climate parameters.
460 to which cases does this refer ?
465 Somewhere it needs to be explained why the comparison to the Franks paper is important? Because it is widely used, or rather comparing something more complex to a very simple approach?
467 this not percent but percent points (leave the -20 to -10; it always helps to explain the concept).
468 this is a strange sentence. Of course it can capture this, because you coded it like this. Propose to rephrase (and move to conclusion). I believe that there have been some other literature estimates of the CO2/O3 damage interactions- please discuss these.
509 what is HEMCOv2.1? A static estimate, a parameterisation, what can we learn from this comparison?
515-520 what is the influence of just 4 PFTs versus more detailed forest types in MEGAN, why do the patterns in S. America look so different (probably not temperature alone).
545-552 is not really for conclusion- but rather a motiviation for this study in an introduction. Cut?
577 Can non-stomatal deposition be excluded as a source of error. How can you be so sure that the deposition is now done 'correctly' Is their some uncrtainty anlysis below this that can corroborate this statement?
578 Not sure what you mean with capable: is this statement based on a quantification of uncertainties, or do you rather mean 'able'?
582 what did Yue and Unger find in %? Explain what you want to say with 'who applied... GPP"
583 elevated CO2 and current O3?
585 difference in global O3 deposition can also be due to assumptions on ocean O3 deposition.
618 This discussion on limitation of using Synflux needs to be expanded. 1) the Synflux method was only tested with 'observed' vd at 3 sites. At these sites the performance was quite good. This is of course the best they could do, but it is not really convicning evidence that the performance elsewhere will also be good. 2) A real issue is how to compare coarse grid output to point measurements.
3) limitations of the soil parameterisation.Citation: https://doi.org/10.5194/egusphere-2022-786-RC2 -
AC1: 'Comment on egusphere-2022-786', Amos Tai, 20 Feb 2023
We would like to thank the reviewers for the thoughtful and insightful comments. The manuscript has been revised accordingly, and our point-by-point responses are provided in the file attached to this comment. The revised manuscript with tracked changes is also included in the linked file below for the Editor’s easy reference:
https://gocuhk-my.sharepoint.com/:b:/g/personal/amostai_cuhk_edu_hk/Eeq-mbYlq8pBvK7Bg-lS6z4B83QzuwiVKUltASZlpMVYxA?e=fvkKJz
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- 1
Joey C. Y. Lam
Jason A. Ducker
Christopher D. Holmes
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(4254 KB) - Metadata XML
-
Supplement
(2091 KB) - BibTeX
- EndNote
- Final revised paper