the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 14 Dec 2023
Atmospheric O2 and CO2 measurements at a single height provide weak constraint on surface carbon exchange
Abstract. The ratios of atmospheric tracers are often used to interpret the local CO2 budget, where measurements at a single height are assumed to represent local flux signatures. Alternatively, these signatures can be derived from direct flux measurements or using fluxes derived from measurements at multiple heights. In this study, we contrast interpretation of surface CO2 exchange from tracer ratio measurements at a single height versus measurements at multiple heights.
Specifically, we analyse the ratio between atmospheric O2 and CO2 (exchange ratio, ER) above a forest canopy. We consider two alternative approaches: the exchange ratio of the forest (ERforest) obtained from the ratio of the surface fluxes of O2 and CO2, derived from their vertical gradients measured at multiple heights, and the exchange ratio of the atmosphere (ERatmos) obtained from changes in the O2 and CO2 mole fractions over time measured at a single measurement height. We investigate the diurnal cycle of both ER signals, with the goal to relate the ERatmos signal to the ERforest signal and to understand the biophysical meaning of the ERatmos signal. We combined CO2 and O2 measurements from Hyytiälä, Finland during spring and summer of 2018 and 2019 with a conceptual land-atmosphere model and a theoretical relationship between ERatmos and ERforest to investigate the behavior of ERatmos and ERforest during different environmental conditions. We show that the ERatmos signal rarely directly represents the forest exchange, mainly because it is influenced by entrainment of air from the free troposphere into the atmospheric boundary layer. The influence of these larger scale signals leads to very high ERatmos values (even larger than 2), especially in the early morning transition. These high values do not directly represent carbon cycle processes, but are rather a mixture of different signals. We show that the resulting ERatmos signal is not the average of the contributing processes, but rather an indication of the influence of large scale processes such as entrainment or advection. Our findings show that these processes are furthermore influenced by climate conditions, such as the 2018 heatwave, through their dependence on soil moisture and temperature.
We conclude that the ERatmos signal obtained from single height measurements rarely directly represents ERforest and therefore only provides a weak constraint on local scale surface CO2 exchange, because large scale processes confound the signal. Single height measurements therefore always require careful selection of the time of day and should be combined with atmospheric modelling to yield a meaningful representation of forest carbon exchange. More generally, we recommend to always measure at multiple heights when using multi-tracer measurements to study surface CO2 exchange.
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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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Preprint
(3631 KB)
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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
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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-2023-2833', Anonymous Referee #1, 28 Jan 2024
Thank you for the opportunity to review this manuscript. The authors present a thorough comparison between ERatmos and ERforest methodologies in quantifying the exchange of O2 and CO2 above a forest canopy. They demonstrate that ERatmos could be significantly influenced by entrainment, which results in unrealistic values. Consequently, the authors recommend against using ERatmos for constraining O2 and CO2 exchanges at a local scale, advocating instead for measurements at multiple heights to more accurately derive ERforest.
Entrainment significantly influences atmospheric composition within the boundary layer and is a well-researched phenomenon. However, this study stands out as the first, to my knowledge, that specifically addresses the impact of entrainment on O2 and CO2 exchanges. This represents a notable contribution to the field. This study suggests careful selection of O2 and CO2 measurements at single heights is required to correctly represent the biological exchange between O2 and CO2 in forest setting. This consideration is equally important in urban and other backgrounds, particularly for studies focusing on exchange ratios over smaller spatio-temporal scales. Given its importance and novelty, I recommend the acceptance of this study after the following issues are addressed.
Major comments:
1. Is it possible for the effects of advection to be counterbalanced by those of entrainment? The observed discrepancies between ERatmos and ERforest might stem from both entrainment and advection processes (Equation 8). In Appendix A1, the authors analyze the influence of the entrainment coefficient (β) on ERatmos signals and discuss instances where ERatmos aligns with ERforest. However, the role of advection remains unclear. Can we rely on measurements taken at a single height when advection's impact is potentially neutralized by entrainment? This interaction might explain why ERatmos and ERforest yield similar results.2. Does entrainment exert a more pronounced impact during typical days? This modelling study is generally based on the mixed layer theory. In studies by Ishidoya et al. (2013, 2015), their analysis did not specifically distinguish between measurements on ‘typical days’ and ‘non-typical days’, and derive similar ERatmos and ERforest values. After reading this work, I am fully convinced the impact of entrainment should be considered on ‘typical day’. However, it remains uncertain how this applies to specific instances, such as heavily polluted urban days or during extraordinary events like COVID-19 lockdowns, where mixed layer theory may not always hold. It would be beneficial for readers to understand the frequency and significance of entrainment during these atypical periods. When assessing single-height measurements on non-typical days, can we still depend on ERatmos for accurate representation? While modeling these atypical days using the CLASS model might be challenging, I suggest the authors discuss these considerations, possibly in Section 5.2, to provide a more comprehensive perspective.
Citation: https://doi.org/10.5194/egusphere-2023-2833-RC1 - AC1: 'Reply on RC1', Kim Faassen, 29 Apr 2024
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RC2: 'Comment on egusphere-2023-2833', Anonymous Referee #2, 10 Mar 2024
The O2/CO2 exchange ratio above a forest canopy is a valuable tracer for understanding carbon exchange at the air-sea and air-land interfaces. We conventionally used a constant for global application, but this ratio can change significantly on a regional scale, and the mechanisms are still unclear. This manuscript presents an insightful analysis of the dominant mechanisms that determine the O2/CO2 exchange ratio by either using observations from a single height or from multiple heights. This study highlights the complexity of only using CO2 and O2 measurements at a single height to quantify ecosystem carbon flux, pointing out the advantage of using measurements from multiple heights for a precise ratio estimate.
The manuscript provides a comprehensive study, and the line of thought is mostly clear. I believe this paper is of interest to the general audience of Biogeosciences. I only have several concerns regarding the model experiment designs and the readability of the paper. I recommend a minor revision before this paper can be considered for publication.
Main concerns:
- It appears to me that the CLASS model was run for only one day with a prescribed initial condition. These runs clearly do not reach a steady state. In this case, the result strongly stands on the initial condition (e.g., the initial jump). I am curious about the rationale for the initial jumps used in this study. I am also curious if the authors have tried to run the model for multiple days to reach a semi-steady-state and check if there are different results.
- I appreciate the detailed study on factors modulating the ERatmos and ERforest. The result part, however, contains too many details and reads more like a technical report. I suggest improving the readability, by either revising the leading sentence of each section to sharply focus on the main result or adding a leading paragraph summarizing the main findings. The abstract section also contains too many technical details. I suggest shortening it significantly.
Minor comments:
- Figure 1 is a little bit unclear. Could you label thick arrows with F(O2)s and F(CO2)s. It is also not clear in the figure that ERforest is actually calculated from the gradient. The two-sided arrow across BL seems to suggest that O2 and CO2 entrainment are of similar magnitude.
- L61: Expand on 'small scale process' upon its first mention for clarity.
- L74: Please elaborate on extreme conditions (i.e., low SMI, etc.)
- L132: Modify Eq. 5 to reflect that ERforest is derived from a gradient.
- L139: It is not clear how you calculate DtO2 and DtCO2. Based on fit to high-resolution data? What’s the time window?
- L336- 339: According to Fig. 4b, 2018 features a very low ERforest during the night. Could you comment on whether it is related to elevated soil temperatures that only matter at night?
- Figure 8: This figure needs extra details. Arrows indicate sunrise to sunset. Better labeled on the figure to make this point clear.
- L527-528: The finding that ERatmos can be so large compared to ERforest stands on the assumption that there is no vertical gradient in CO2 and O2 within the BL. If the resolved ERatmos is based on using data that is very close to the top of the BL, this ERatmos can be more sensitive to entrainment, compared to other studies.
- Figure A2: Why the model results are not extended toward the beginning and the end of the day
- Figure A3: It seems like the model overestimates the BL height in the afternoon and around the sunset. The simulated O2 concentration also seems to have a clear phase lag compared to observation. How would these affect the simulated ER?
- The title reads like the paper is trying to falsify the idea of using single-height CO2 and O2 observations to constrain surface carbon exchange. However, this approach is still valid if it only uses nighttime data. Given the detailed model experiments conducted in this study, I suggest modifying the title to better represent the comprehensive details of this work.
Citation: https://doi.org/10.5194/egusphere-2023-2833-RC2 - AC2: 'Reply on RC2', Kim Faassen, 29 Apr 2024
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EC1: 'Comment on egusphere-2023-2833', Paul Stoy, 25 Mar 2024
I am in receipt of a third review, attached. Please also consider the recommendations of this Referee and I am looking forward to the revised manuscript.
Sincerely,
Paul Stoy
- AC3: 'Reply on EC1', Kim Faassen, 29 Apr 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-2833', Anonymous Referee #1, 28 Jan 2024
Thank you for the opportunity to review this manuscript. The authors present a thorough comparison between ERatmos and ERforest methodologies in quantifying the exchange of O2 and CO2 above a forest canopy. They demonstrate that ERatmos could be significantly influenced by entrainment, which results in unrealistic values. Consequently, the authors recommend against using ERatmos for constraining O2 and CO2 exchanges at a local scale, advocating instead for measurements at multiple heights to more accurately derive ERforest.
Entrainment significantly influences atmospheric composition within the boundary layer and is a well-researched phenomenon. However, this study stands out as the first, to my knowledge, that specifically addresses the impact of entrainment on O2 and CO2 exchanges. This represents a notable contribution to the field. This study suggests careful selection of O2 and CO2 measurements at single heights is required to correctly represent the biological exchange between O2 and CO2 in forest setting. This consideration is equally important in urban and other backgrounds, particularly for studies focusing on exchange ratios over smaller spatio-temporal scales. Given its importance and novelty, I recommend the acceptance of this study after the following issues are addressed.
Major comments:
1. Is it possible for the effects of advection to be counterbalanced by those of entrainment? The observed discrepancies between ERatmos and ERforest might stem from both entrainment and advection processes (Equation 8). In Appendix A1, the authors analyze the influence of the entrainment coefficient (β) on ERatmos signals and discuss instances where ERatmos aligns with ERforest. However, the role of advection remains unclear. Can we rely on measurements taken at a single height when advection's impact is potentially neutralized by entrainment? This interaction might explain why ERatmos and ERforest yield similar results.2. Does entrainment exert a more pronounced impact during typical days? This modelling study is generally based on the mixed layer theory. In studies by Ishidoya et al. (2013, 2015), their analysis did not specifically distinguish between measurements on ‘typical days’ and ‘non-typical days’, and derive similar ERatmos and ERforest values. After reading this work, I am fully convinced the impact of entrainment should be considered on ‘typical day’. However, it remains uncertain how this applies to specific instances, such as heavily polluted urban days or during extraordinary events like COVID-19 lockdowns, where mixed layer theory may not always hold. It would be beneficial for readers to understand the frequency and significance of entrainment during these atypical periods. When assessing single-height measurements on non-typical days, can we still depend on ERatmos for accurate representation? While modeling these atypical days using the CLASS model might be challenging, I suggest the authors discuss these considerations, possibly in Section 5.2, to provide a more comprehensive perspective.
Citation: https://doi.org/10.5194/egusphere-2023-2833-RC1 - AC1: 'Reply on RC1', Kim Faassen, 29 Apr 2024
-
RC2: 'Comment on egusphere-2023-2833', Anonymous Referee #2, 10 Mar 2024
The O2/CO2 exchange ratio above a forest canopy is a valuable tracer for understanding carbon exchange at the air-sea and air-land interfaces. We conventionally used a constant for global application, but this ratio can change significantly on a regional scale, and the mechanisms are still unclear. This manuscript presents an insightful analysis of the dominant mechanisms that determine the O2/CO2 exchange ratio by either using observations from a single height or from multiple heights. This study highlights the complexity of only using CO2 and O2 measurements at a single height to quantify ecosystem carbon flux, pointing out the advantage of using measurements from multiple heights for a precise ratio estimate.
The manuscript provides a comprehensive study, and the line of thought is mostly clear. I believe this paper is of interest to the general audience of Biogeosciences. I only have several concerns regarding the model experiment designs and the readability of the paper. I recommend a minor revision before this paper can be considered for publication.
Main concerns:
- It appears to me that the CLASS model was run for only one day with a prescribed initial condition. These runs clearly do not reach a steady state. In this case, the result strongly stands on the initial condition (e.g., the initial jump). I am curious about the rationale for the initial jumps used in this study. I am also curious if the authors have tried to run the model for multiple days to reach a semi-steady-state and check if there are different results.
- I appreciate the detailed study on factors modulating the ERatmos and ERforest. The result part, however, contains too many details and reads more like a technical report. I suggest improving the readability, by either revising the leading sentence of each section to sharply focus on the main result or adding a leading paragraph summarizing the main findings. The abstract section also contains too many technical details. I suggest shortening it significantly.
Minor comments:
- Figure 1 is a little bit unclear. Could you label thick arrows with F(O2)s and F(CO2)s. It is also not clear in the figure that ERforest is actually calculated from the gradient. The two-sided arrow across BL seems to suggest that O2 and CO2 entrainment are of similar magnitude.
- L61: Expand on 'small scale process' upon its first mention for clarity.
- L74: Please elaborate on extreme conditions (i.e., low SMI, etc.)
- L132: Modify Eq. 5 to reflect that ERforest is derived from a gradient.
- L139: It is not clear how you calculate DtO2 and DtCO2. Based on fit to high-resolution data? What’s the time window?
- L336- 339: According to Fig. 4b, 2018 features a very low ERforest during the night. Could you comment on whether it is related to elevated soil temperatures that only matter at night?
- Figure 8: This figure needs extra details. Arrows indicate sunrise to sunset. Better labeled on the figure to make this point clear.
- L527-528: The finding that ERatmos can be so large compared to ERforest stands on the assumption that there is no vertical gradient in CO2 and O2 within the BL. If the resolved ERatmos is based on using data that is very close to the top of the BL, this ERatmos can be more sensitive to entrainment, compared to other studies.
- Figure A2: Why the model results are not extended toward the beginning and the end of the day
- Figure A3: It seems like the model overestimates the BL height in the afternoon and around the sunset. The simulated O2 concentration also seems to have a clear phase lag compared to observation. How would these affect the simulated ER?
- The title reads like the paper is trying to falsify the idea of using single-height CO2 and O2 observations to constrain surface carbon exchange. However, this approach is still valid if it only uses nighttime data. Given the detailed model experiments conducted in this study, I suggest modifying the title to better represent the comprehensive details of this work.
Citation: https://doi.org/10.5194/egusphere-2023-2833-RC2 - AC2: 'Reply on RC2', Kim Faassen, 29 Apr 2024
-
EC1: 'Comment on egusphere-2023-2833', Paul Stoy, 25 Mar 2024
I am in receipt of a third review, attached. Please also consider the recommendations of this Referee and I am looking forward to the revised manuscript.
Sincerely,
Paul Stoy
- AC3: 'Reply on EC1', Kim Faassen, 29 Apr 2024
Peer review completion
Journal article(s) based on this preprint
Data sets
Atmospheric measurements results archive, Hyytiälä Ingrid Luijkx and Kim Faassen https://doi.org/10.18160/SJ3J-PD38
Model code and software
CLASS model, explanation and model code Jordi Vilà-Guerau de Arellano, Chiel van Heerwaarden, Bart van Stratum, and Kees van den Dries https://classmodel.github.io/
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Jordi Vilà-Guerau de Arellano
Raquel González-Armas
Bert G. Heusinkveld
Ivan Mammarella
Wouter Peters
Ingrid T. Luijkx
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(3631 KB) - Metadata XML