the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Effects of denitrification on the distributions of trace gas abundances in the polar regions: a model-data comparison
Abstract. Polar stratospheric clouds (PSCs) play a key role in the polar chemistry of the stratosphere. Nitric acid trihydrate (NAT) particles have been shown to lead to denitrification of the lower stratosphere. While the existence of large NAT particles (NAT "rocks") has been verified by many measurements especially in the Northern Hemisphere (NH), most current chemistry-climate models use simplified parametrizations, often based on evaluations in the Southern Hemisphere where the polar vortex is stable enough that accounting for NAT rocks is not as important as in the NH. Here, we evaluate the probability density functions of various gaseous species in the polar vortex using one such model, the Whole Atmosphere Community Climate Model (WACCM), and compare these with measurements by the Michelson Interferometer for Passive Atmospheric Sounding onboard the Environmental Satellite (MIPAS/Envisat) and two ozonesonde stations for a range of years and in both hemispheres. Using the maximum difference between the distributions of MIPAS and WACCM as a measure of coherence, we find better agreement for HNO3 when reducing the NAT number density from the standard value of 10−2 used in this model to 5 × 10−4 cm−3 for almost all spring seasons during the MIPAS period in both hemispheres. The distributions of ClONO2 and O3 are not greatly affected by the NAT density. The average difference of WACCM to ozonesondes supports the need to reduce the NAT number density in the model. Therefore, this study suggests to use a NAT number density of 5 × 10−4 cm−3 for future simulations with WACCM.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(1986 KB) - Metadata XML
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Supplement
(3664 KB) - BibTeX
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2022-1422', Ingo Wohltmann, 10 Jan 2023
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AC1: 'Reply on RC1', Michael Weimer, 14 Apr 2023
Dear Ingo Wohltmann,
Thank you for your detailed review of our study. Your comments really helped to improve the manuscript. Please find our responses to your comment in the supplement to this reply.
Thank you and on behalf of all authors,
Michael Weimer
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AC1: 'Reply on RC1', Michael Weimer, 14 Apr 2023
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RC2: 'Comment on egusphere-2022-1422', Anonymous Referee #2, 10 Mar 2023
Review on Weimer et al., 2022: Effects of denitrification …
Â
In this manuscript, the effects of denitrification on the distribution of HNO3, ClONO2, and O3 in the Arctic and Antarctic polar vortex during spring are investigated. Essentially, simulations performed with the WACCM model are compared to observations with satellite-based MIPAS and ozonesondes. The main focus is on sensitivity simulations where the NAT number density is varied to improve the agreement with the observational data. Based on the current work, the authors recommend a new value for the NAT density for future simulations with the WACCM model.
The manuscript presents an interesting study of the capabilities and limitations of the WACCM model and how the agreement with trace gas observations can be improved.
I recommend the publication of this manuscript. However, some points should be investigated and discussed in more detail beforehand.
General CommentsThe most important point I would like to address is the lack of comparison of the simulated NAT density with observations. Although this is the most important set screw for this study, no attempt is made to constrain the NAT density used in this modeling study with observational data. Satellite-based observations of NAT density are mentioned in the introduction but are not discussed further. The model results are compared to more than 10 years of trace gas observations. I assume that observations of NAT density are also available during this period, at least temporarily.
The NAT density now recommended as an input parameter differs by a factor of 20 from the previous one. Although the simplifications of the model might not allow direct integration of the measured quantities, it is necessary to relate the model simulations to observations of the NAT density.
The manuscript states that reduced NAT density in the model setup leads to better agreement between model simulations and observations. And this seems to be true for HNO3, ClONO2 and ozone. But why is this so? What are the underlying physical and chemical processes that are responsible? At least a rudimentary attempt should be made to explain this plausibly.
In general, a more detailed discussion of the simplifications of the model would be helpful to better classify the quality of the presented comparisons between model and observations in this study. For example: the statement that "... so observed NAT particle abundances may therefore not be the best guide for this parameter choice ..." (page 3, line 68) should be discussed in a bit more detail.Â
Specific comments
Page 4/line 105: Although the term "maximum difference" might be common in the modeling community, it would be useful for a broader readership to see this concept presented and explained in a bit more detail.
Page 5/line 121: "... Turning off all heterogeneous chemistry except for N2O5 + H2O ..." Why is this reaction not turned off?
Figure 1: The labels in the partial figures take up too much space (HetAll ....). This means that the actual content of the figure is not displayed optimally. Since the color coding of the simulations is the same in all subfigures, it could be placed separately next to the figures. The indication "max(d)" should of course remain in the figure.
Figure 1: What does the indication "nprof:...." at the top of the figure mean?
Figure 1 to 4: The volume mixing ration of nitric acid in the stratosphere varies with altitude, similar as ozone (Figure 5). In addition, sedimentation of PSC particles leads to a change in the height distribution of HNO3. In Figures 1 through 4, only altitude-independent concentration is given. Please explain briefly how this value is obtained. Would it not be possible, at least for one case of HNO3, to choose a similar representation as for ozone in Figure 5?
Page 5/line 124: "... In HetAll.1e-2, larger HNO3 values are more common in all panels compared to the other simulations..." Can you explain this result? Why does a higher density in the particle phase lead to a higher gas phase concentration of HNO3 and vice versa? What processes underlie this behavior?
Page 7, line 148: In the manuscript, the discrepancy between model and measurement is attributed to the lower accuracy of the MIPAS instrument. By how much was the accuracy of the measurement reduced compared to the measurements included in Figure 1? Can model processes be excluded for this discrepancy?
Figure 5: The "interquantile range" is very difficult to see in the figure.Citation: https://doi.org/10.5194/egusphere-2022-1422-RC2 -
AC2: 'Reply on RC2', Michael Weimer, 14 Apr 2023
Dear Referee,
Thank you for your detailed review of our study. Your comments really helped to improve the manuscript. Please find our responses to your comments in the supplement to this reply.
Thank you and on behalf of all authors,
Michael Weimer
-
AC2: 'Reply on RC2', Michael Weimer, 14 Apr 2023
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2022-1422', Ingo Wohltmann, 10 Jan 2023
-
AC1: 'Reply on RC1', Michael Weimer, 14 Apr 2023
Dear Ingo Wohltmann,
Thank you for your detailed review of our study. Your comments really helped to improve the manuscript. Please find our responses to your comment in the supplement to this reply.
Thank you and on behalf of all authors,
Michael Weimer
-
AC1: 'Reply on RC1', Michael Weimer, 14 Apr 2023
-
RC2: 'Comment on egusphere-2022-1422', Anonymous Referee #2, 10 Mar 2023
Review on Weimer et al., 2022: Effects of denitrification …
Â
In this manuscript, the effects of denitrification on the distribution of HNO3, ClONO2, and O3 in the Arctic and Antarctic polar vortex during spring are investigated. Essentially, simulations performed with the WACCM model are compared to observations with satellite-based MIPAS and ozonesondes. The main focus is on sensitivity simulations where the NAT number density is varied to improve the agreement with the observational data. Based on the current work, the authors recommend a new value for the NAT density for future simulations with the WACCM model.
The manuscript presents an interesting study of the capabilities and limitations of the WACCM model and how the agreement with trace gas observations can be improved.
I recommend the publication of this manuscript. However, some points should be investigated and discussed in more detail beforehand.
General CommentsThe most important point I would like to address is the lack of comparison of the simulated NAT density with observations. Although this is the most important set screw for this study, no attempt is made to constrain the NAT density used in this modeling study with observational data. Satellite-based observations of NAT density are mentioned in the introduction but are not discussed further. The model results are compared to more than 10 years of trace gas observations. I assume that observations of NAT density are also available during this period, at least temporarily.
The NAT density now recommended as an input parameter differs by a factor of 20 from the previous one. Although the simplifications of the model might not allow direct integration of the measured quantities, it is necessary to relate the model simulations to observations of the NAT density.
The manuscript states that reduced NAT density in the model setup leads to better agreement between model simulations and observations. And this seems to be true for HNO3, ClONO2 and ozone. But why is this so? What are the underlying physical and chemical processes that are responsible? At least a rudimentary attempt should be made to explain this plausibly.
In general, a more detailed discussion of the simplifications of the model would be helpful to better classify the quality of the presented comparisons between model and observations in this study. For example: the statement that "... so observed NAT particle abundances may therefore not be the best guide for this parameter choice ..." (page 3, line 68) should be discussed in a bit more detail.Â
Specific comments
Page 4/line 105: Although the term "maximum difference" might be common in the modeling community, it would be useful for a broader readership to see this concept presented and explained in a bit more detail.
Page 5/line 121: "... Turning off all heterogeneous chemistry except for N2O5 + H2O ..." Why is this reaction not turned off?
Figure 1: The labels in the partial figures take up too much space (HetAll ....). This means that the actual content of the figure is not displayed optimally. Since the color coding of the simulations is the same in all subfigures, it could be placed separately next to the figures. The indication "max(d)" should of course remain in the figure.
Figure 1: What does the indication "nprof:...." at the top of the figure mean?
Figure 1 to 4: The volume mixing ration of nitric acid in the stratosphere varies with altitude, similar as ozone (Figure 5). In addition, sedimentation of PSC particles leads to a change in the height distribution of HNO3. In Figures 1 through 4, only altitude-independent concentration is given. Please explain briefly how this value is obtained. Would it not be possible, at least for one case of HNO3, to choose a similar representation as for ozone in Figure 5?
Page 5/line 124: "... In HetAll.1e-2, larger HNO3 values are more common in all panels compared to the other simulations..." Can you explain this result? Why does a higher density in the particle phase lead to a higher gas phase concentration of HNO3 and vice versa? What processes underlie this behavior?
Page 7, line 148: In the manuscript, the discrepancy between model and measurement is attributed to the lower accuracy of the MIPAS instrument. By how much was the accuracy of the measurement reduced compared to the measurements included in Figure 1? Can model processes be excluded for this discrepancy?
Figure 5: The "interquantile range" is very difficult to see in the figure.Citation: https://doi.org/10.5194/egusphere-2022-1422-RC2 -
AC2: 'Reply on RC2', Michael Weimer, 14 Apr 2023
Dear Referee,
Thank you for your detailed review of our study. Your comments really helped to improve the manuscript. Please find our responses to your comments in the supplement to this reply.
Thank you and on behalf of all authors,
Michael Weimer
-
AC2: 'Reply on RC2', Michael Weimer, 14 Apr 2023
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Douglas E. Kinnison
Catherine Wilka
Susan Solomon
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(1986 KB) - Metadata XML
-
Supplement
(3664 KB) - BibTeX
- EndNote
- Final revised paper