the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Atmospheric Distribution of HCN from Satellite Observations and 3-D Model Simulations
Abstract. We use a tracer version of the TOMCAT global 3-D chemical transport model to investigate the physical and chemical processes driving the abundance of hydrogen cyanide (HCN) in the troposphere and stratosphere over the period 2004–2016. The modelled HCN distribution is compared with version 4.1 of the Atmospheric Chemistry Experiment - Fourier Transform Spectrometer (ACE-FTS) HCN satellite data, which provides profiles up to around 42 km, and with ground-based column measurements from the Network for the Detection of Atmospheric Composition Change (NDACC). ACE-FTS has so far provided over 17 years of data, from 2004, which allow us to monitor both the seasonal and interannual variations of HCN and its transport through the atmosphere. In particular, by analysing the long time series, we are able to detect the effects on atmospheric composition of large wildfire events like those observed in 2006 and 2015 in Indonesia. Our 3-D model simulations confirm previous lower altitude balloon comparisons that the currently recommended NASA Jet Propulsion Laboratory (JPL) reaction rate coefficient of HCN with OH greatly overestimates the HCN loss. The use of the rate coefficient proposed by Kleinböhl et al. (2006) in combination with the HCN oxidation by O(1D) gives good agreement between ACE-FTS observations and the model. Furthermore, investigation of the individual photochemical loss terms shows that the reduction of the HCN mixing ratio with height in the middle stratosphere is mainly driven by the O(1D) sink with only a small contribution from reaction with OH. From comparisons of the model tracers with ground-based HCN observations we test the magnitude of the ocean sink in two different published schemes (Li et al. 2000, 2003). We find that in our 3-D model the two schemes produce HCN abundances which are very different to the NDACC observations but in different directions. A model HCN tracer using the Li et al. (2000) scheme overestimates the HCN concentration by almost a factor two, while a HCN tracer using the Li et al. (2003) scheme underestimates the observations by about one-third. To obtain good agreement between the model and observations we need to scale the magnitudes of the global ocean sinks by the factors of 0.25 and 2 for the schemes of Li et al. (2000) and Li et al. (2003), respectively. This work shows that the atmospheric photochemical sinks of HCN now appear well constrained but improvements are needed in parameterising the major ocean uptake sink.
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Notice on discussion status
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Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2022-1404', Hugh C. Pumphrey, 19 Dec 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-1404/egusphere-2022-1404-RC1-supplement.pdf
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RC2: 'Review of ‘Atmospheric distribution of HCN from satellite observations and 3-D model simulations’ by A. G. Bruno et al. (2022)', Anonymous Referee #2, 09 Jan 2023
This study presents much improved understanding of the atmospheric processes that are controlling the HCN budget using the observational data sets and the global chemical transport model simulations. There are big uncertainties in the atmospheric loss processes and ocean update of HCN and this study certainly is valuable in better representation of those processes. The use of both the NDACC and the ACE-FTS satellite measurements supports the robustness of the comparison. In terms of methodology, I have little to suggest for improvements. However, I personally think that by adding a little bit more scientific background this paper will become more interesting to a broader community. Below are my comments for the authors may take into consideration.
Major Comments:
- I would like to see clearer description of what we do and do not understand about the HCN budget in introduction. All the references included in introduction seem to suggest we have good understanding about HCN in the troposphere and stratosphere and the last sentence seems to suggest otherwise. For instance, including a statement saying all the model simulations show different results would help supporting this argument.
- The motivation of this study has to be mentioned clearly. Both observational data and the model simulations are used as tools but it is not clear what the main goal of this study is.
- It is a reasonable approach to compare the model outputs to the NDACC in-situ However, can we trust the ACE-FTS measurements quantitatively? Are there any in-situ measurements of HCN in the upper troposphere and lower stratosphere to confirm that the ACE-FTS measurements are reasonable?
Minor Comments:
- L2-22 (Abstract): I would recommend moving some of the contents explaining the background to introduction, which would make abstract a little more compact. Also put emphasis on the key findings and significance of this study. For instance, why is simulating the HCN amount using the global model correctly important?
- L2: It is mentioned that the physical and chemical processes are investigated. Are the HCN removal processes considered to be physical?
- L6-9: I would recommend combining these into one simple sentence. My recommendation for a replacement would be, ‘We detected the changes in the atmospheric composition due to large wildfire events over Indonesia in 2006 and 2015 using long-term measurements from the ACE-FTS’.
- L10: ‘previous lower altitude balloon comparisons’ can be removed.
- L49: A citation for NDACC could be included here.
- L 67: I think this is a good place to make a statement of why a global transport model is being used to understand specific aspects of the HCN budget. Is TOMCAT model proved to be a good tool for this study?
- L70: Do Burkholder et al. (2015 & 2019) papers have the same rate coefficient for HCN oxidation?
- L83: This sentence can be augmented or replaced by a statement of the ACE-FTS sampling pattern being densely located in high latitudes.
- P4, Fig. 1: A couple of solid contours can be added to show the distributions in the stratosphere more clearly. The current color scheme makes it hard to distinguish the blue and the green area.
- L92: A reason why only 2008-2009 are used in the seasonal mean could be given here. Have there been any studies showing the HCN climatology in the past? Is ACE-FTS climatology reasonable compare to other data set quantitatively?
- P5, Fig. 2: The color scheme can be revisited to show the variability in the stratosphere clearly. Also, what is the maximum value in 2015? The color bar Is saturated at 600 pptv.
- L133: What is the sampling frequency of HCN through the NDACC?
- L120: with a higher concentration -> with higher concentrations
- L134: A citation is needed for the ECMWF meteorological inputs. Also, does TOMCAT reproduce reasonable climatology of other tracers, such as carbon monoxide?
- P8, Fig. 3: The yellow lines are almost invisible on screen. A replacement color is recommended.
- P14 (Conclusion): I would recommend adding a statement what role HCN is playing in our current climate and how this study will contribute predicting future climate better related to the results presented in this work.
Citation: https://doi.org/10.5194/egusphere-2022-1404-RC2 - AC1: 'Comment on egusphere-2022-1404', Antonio Giovanni Bruno, 24 Feb 2023
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2022-1404', Hugh C. Pumphrey, 19 Dec 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-1404/egusphere-2022-1404-RC1-supplement.pdf
-
RC2: 'Review of ‘Atmospheric distribution of HCN from satellite observations and 3-D model simulations’ by A. G. Bruno et al. (2022)', Anonymous Referee #2, 09 Jan 2023
This study presents much improved understanding of the atmospheric processes that are controlling the HCN budget using the observational data sets and the global chemical transport model simulations. There are big uncertainties in the atmospheric loss processes and ocean update of HCN and this study certainly is valuable in better representation of those processes. The use of both the NDACC and the ACE-FTS satellite measurements supports the robustness of the comparison. In terms of methodology, I have little to suggest for improvements. However, I personally think that by adding a little bit more scientific background this paper will become more interesting to a broader community. Below are my comments for the authors may take into consideration.
Major Comments:
- I would like to see clearer description of what we do and do not understand about the HCN budget in introduction. All the references included in introduction seem to suggest we have good understanding about HCN in the troposphere and stratosphere and the last sentence seems to suggest otherwise. For instance, including a statement saying all the model simulations show different results would help supporting this argument.
- The motivation of this study has to be mentioned clearly. Both observational data and the model simulations are used as tools but it is not clear what the main goal of this study is.
- It is a reasonable approach to compare the model outputs to the NDACC in-situ However, can we trust the ACE-FTS measurements quantitatively? Are there any in-situ measurements of HCN in the upper troposphere and lower stratosphere to confirm that the ACE-FTS measurements are reasonable?
Minor Comments:
- L2-22 (Abstract): I would recommend moving some of the contents explaining the background to introduction, which would make abstract a little more compact. Also put emphasis on the key findings and significance of this study. For instance, why is simulating the HCN amount using the global model correctly important?
- L2: It is mentioned that the physical and chemical processes are investigated. Are the HCN removal processes considered to be physical?
- L6-9: I would recommend combining these into one simple sentence. My recommendation for a replacement would be, ‘We detected the changes in the atmospheric composition due to large wildfire events over Indonesia in 2006 and 2015 using long-term measurements from the ACE-FTS’.
- L10: ‘previous lower altitude balloon comparisons’ can be removed.
- L49: A citation for NDACC could be included here.
- L 67: I think this is a good place to make a statement of why a global transport model is being used to understand specific aspects of the HCN budget. Is TOMCAT model proved to be a good tool for this study?
- L70: Do Burkholder et al. (2015 & 2019) papers have the same rate coefficient for HCN oxidation?
- L83: This sentence can be augmented or replaced by a statement of the ACE-FTS sampling pattern being densely located in high latitudes.
- P4, Fig. 1: A couple of solid contours can be added to show the distributions in the stratosphere more clearly. The current color scheme makes it hard to distinguish the blue and the green area.
- L92: A reason why only 2008-2009 are used in the seasonal mean could be given here. Have there been any studies showing the HCN climatology in the past? Is ACE-FTS climatology reasonable compare to other data set quantitatively?
- P5, Fig. 2: The color scheme can be revisited to show the variability in the stratosphere clearly. Also, what is the maximum value in 2015? The color bar Is saturated at 600 pptv.
- L133: What is the sampling frequency of HCN through the NDACC?
- L120: with a higher concentration -> with higher concentrations
- L134: A citation is needed for the ECMWF meteorological inputs. Also, does TOMCAT reproduce reasonable climatology of other tracers, such as carbon monoxide?
- P8, Fig. 3: The yellow lines are almost invisible on screen. A replacement color is recommended.
- P14 (Conclusion): I would recommend adding a statement what role HCN is playing in our current climate and how this study will contribute predicting future climate better related to the results presented in this work.
Citation: https://doi.org/10.5194/egusphere-2022-1404-RC2 - AC1: 'Comment on egusphere-2022-1404', Antonio Giovanni Bruno, 24 Feb 2023
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Antonio Giovanni Bruno
Jeremy J. Harrison
Martyn P. Chipperfield
David P. Moore
Richard J. Pope
Christopher Wilson
Emmanuel Mahieu
Justus Notholt
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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