the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
On the impact of canopy environmental variables on the diurnal dynamics of the leaf and canopy water and carbon dioxide exchange
Abstract. Quantifying water vapor and carbon dioxide exchange dynamics between land and atmosphere through observations and modelling is necessary to reproduce and project near surface climate in coupled land-atmosphere models. The exchange of water and carbon dioxide (CO2) occurs at the leaf surfaces (leaf level) and in a net manner through the exchanges at all the leaf surfaces composing the vegetation canopy and at the soil surface (canopy level). These exchanges depend on the meteorological forcings imposed by the overlying atmosphere (atmospheric boundary layer level). In this manuscript, we investigate the effect of four canopy environmental variables (photosynthetic active radiation (PAR), water vapor pressure deficit (VPD), air temperature (T) and atmospheric CO2 concentration (Ca)) on the local individual leaf exchange and canopy exchange of water and CO2 at hourly time scales and the effect of atmospheric boundary layer (ABL) processes on the local exchange.
To that end, we simultaneously investigated the exchanges of water and CO2 at leaf level and canopy level for an alfalfa field in Northern Spain during a day in the summer of 2021. We used comprehensive observations ranging from stomatal conductance to ABL measurements collected during the Land Surface Interactions with the Atmosphere in the Iberian Semi-Arid Environment (LIAISE) experiment. To support the observational analysis, we used an integrative mixed-layer atmospheric model (CLASS) that have representations at all considered levels. To relate how temporal changes of the four environmental variables modify the fluxes of water and CO2, we studied tendency equations of the leaf gas exchange. These mathematical expressions quantify the temporal evolution of the leaf gas exchange as a function of the temporal evolution of PAR, VPD, T and Ca. To investigate the effects of ABL processes on the local exchange, we developed three modelling experiments that impose surface radiative perturbations by a cloud passage (which perturbed PAR, T and VPD), entrainment of dry air from the free troposphere (which perturbed VPD) and advection of cold air (which perturbed T and VPD).
Model results and observations matched the leaf gas exchange (with r2 between 0.23 and 0.67) and canopy gas exchange (with r2 between 0.90 and 0.95). The tendency equations of the modelled leaf gas exchange during the studied day revealed that the temporal dynamics of PAR were the main contributor to the temporal dynamics of the leaf gas exchange with atmospheric CO2 temporal dynamics being the least important contributor. From the three modelling experiments with ABL perturbations, the surface radiative changes induced by a cloud perturbed the CO2 exchange the most, whereas all of them perturbed the water exchange to a similar extent. Second order effects on the dynamics of the leaf gas exchange were also identified using the tendency equations. For instance, the decrease of net CO2 assimilation rate during the cloud due to a decrease in surface radiation was further enhanced due to the decrease in air temperature also associated with the cloud. With this research we showcase that the proposed tendency equations can disentangle the effect of environmental variables on the leaf exchange of water and CO2 with the atmosphere as represented in land-surface parameterization schemes and become a useful tool to analyze these schemes in weather and climate models.
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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
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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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Supplement
(267 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-2023-2282', Anonymous Referee #1, 04 Jan 2024
The manuscript by Gonzales-Armas et al. investigates the drivers of diurnal dynamics of land-atmosphere carbon and water exchange in an alfalfa field using one clear-sky observation day from the LIAISE field campaign and a modelling framework. What stands out in this study is the wide range of observations from leaf- to ecosystem- to planetary boundary layer scale that are used in combination with a model that explicitly represents all these scales. Finally, they introduce the concept of tendency equations to analyse the model output with the aim to better understand the underlying drivers of diurnal land-atmosphere exchange dynamics. In my opinion, the manuscript can be an important contribution to further our understanding of and extend our tool set to analyse land-atmosphere interactions. The manuscript is generally well written, and the methodology is described in sufficient detail. However, I have to main comments that the authors could address:
The tendency equations represent a powerful tool to “make sense” of modelling output. Often in the literature, modelling outputs (or differences in modelling outputs) are not sufficiently explained and tendency equations might help in this regard. I was wondering if a framework could be developed to apply this concept to observations or at least to use observations to validate these tendencies in models. In the current study, observations are shown to demonstrate that the model can reproduce the diurnal dynamics in the observations. However, it would for example be even more insightful to test if the opposing An responses at the leaf- and canopy-scale in the VPD-ENT experiment can be validated against field observations. These questions could also be discussed as part of the Discussion.
The authors mention the potential effects of diffuse and direct radiation on carbon and water exchange. I think this is an important issue and should be more discussed in the Discussion section. The authors could go further than just mentioning potential effects and discuss how for example cloud cover and the associated changes in direct and diffuse radiation could affect their results.
Please see below a few more specific comments.
Specific comments
Line 41: Explain what the “phase lag” is.
Line 44-52: The authors refer here to “surface” and “canopy”. Is there a difference between these two definitions?
Line 83: Why do the authors only focus on diurnal dynamics? The model could also be validated against multi-day simulations to explore day-to-day variations in meteorological conditions and their impacts.
Figure 1: This is a great figure conceptualising their research approach.
Line 133: How was it tested if the ABL started to be a CBL?
Line 146: The authors mention here that the initial CO2 jump was chosen to reproduce the diurnal variability in observed CO2. Later, they validate the model against diurnal CO2 dynamics. Would this not by default improve the model output? Is it then justified to compare the model CO2 output to observations.
Line 186: How was the soil respiration derived from the chamber measurements? A reference could be sufficient here.
Line 276: It could be helpful here to also show the actual observation in addition to the idealised modelling experiments.
Line 308 & 309: I am not sure if “acquiring” and “excepting” are the right choice of words here.
Section 3.1.3: Slope and intercept could be also shown for the model validation section.
Line 384-397: It seems as if the different responses described in this paragraph are due to different model representation of photosynthesis. Is there any way to assess which representation is more accurate in this case?
Line 436: The authors could add more details on how the sensitivity analysis was conducted and what the results were.
Citation: https://doi.org/10.5194/egusphere-2023-2282-RC1 - AC3: 'Reply on RC1', Raquel González Armas, 12 Mar 2024
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AC1: 'Comment on egusphere-2023-2282', Raquel González Armas, 08 Feb 2024
Dear editor and anonymous referee # 1,
here I post a response on behalf of the authors to the received review . We thank the anonymous referee for taking the time to provide the review and to help us to refine the manuscript with it.
Best regards,
Raquel
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RC2: 'Comment on egusphere-2023-2282', Anonymous Referee #2, 25 Feb 2024
- AC2: 'Reply on RC2', Raquel González Armas, 12 Mar 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-2282', Anonymous Referee #1, 04 Jan 2024
The manuscript by Gonzales-Armas et al. investigates the drivers of diurnal dynamics of land-atmosphere carbon and water exchange in an alfalfa field using one clear-sky observation day from the LIAISE field campaign and a modelling framework. What stands out in this study is the wide range of observations from leaf- to ecosystem- to planetary boundary layer scale that are used in combination with a model that explicitly represents all these scales. Finally, they introduce the concept of tendency equations to analyse the model output with the aim to better understand the underlying drivers of diurnal land-atmosphere exchange dynamics. In my opinion, the manuscript can be an important contribution to further our understanding of and extend our tool set to analyse land-atmosphere interactions. The manuscript is generally well written, and the methodology is described in sufficient detail. However, I have to main comments that the authors could address:
The tendency equations represent a powerful tool to “make sense” of modelling output. Often in the literature, modelling outputs (or differences in modelling outputs) are not sufficiently explained and tendency equations might help in this regard. I was wondering if a framework could be developed to apply this concept to observations or at least to use observations to validate these tendencies in models. In the current study, observations are shown to demonstrate that the model can reproduce the diurnal dynamics in the observations. However, it would for example be even more insightful to test if the opposing An responses at the leaf- and canopy-scale in the VPD-ENT experiment can be validated against field observations. These questions could also be discussed as part of the Discussion.
The authors mention the potential effects of diffuse and direct radiation on carbon and water exchange. I think this is an important issue and should be more discussed in the Discussion section. The authors could go further than just mentioning potential effects and discuss how for example cloud cover and the associated changes in direct and diffuse radiation could affect their results.
Please see below a few more specific comments.
Specific comments
Line 41: Explain what the “phase lag” is.
Line 44-52: The authors refer here to “surface” and “canopy”. Is there a difference between these two definitions?
Line 83: Why do the authors only focus on diurnal dynamics? The model could also be validated against multi-day simulations to explore day-to-day variations in meteorological conditions and their impacts.
Figure 1: This is a great figure conceptualising their research approach.
Line 133: How was it tested if the ABL started to be a CBL?
Line 146: The authors mention here that the initial CO2 jump was chosen to reproduce the diurnal variability in observed CO2. Later, they validate the model against diurnal CO2 dynamics. Would this not by default improve the model output? Is it then justified to compare the model CO2 output to observations.
Line 186: How was the soil respiration derived from the chamber measurements? A reference could be sufficient here.
Line 276: It could be helpful here to also show the actual observation in addition to the idealised modelling experiments.
Line 308 & 309: I am not sure if “acquiring” and “excepting” are the right choice of words here.
Section 3.1.3: Slope and intercept could be also shown for the model validation section.
Line 384-397: It seems as if the different responses described in this paragraph are due to different model representation of photosynthesis. Is there any way to assess which representation is more accurate in this case?
Line 436: The authors could add more details on how the sensitivity analysis was conducted and what the results were.
Citation: https://doi.org/10.5194/egusphere-2023-2282-RC1 - AC3: 'Reply on RC1', Raquel González Armas, 12 Mar 2024
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AC1: 'Comment on egusphere-2023-2282', Raquel González Armas, 08 Feb 2024
Dear editor and anonymous referee # 1,
here I post a response on behalf of the authors to the received review . We thank the anonymous referee for taking the time to provide the review and to help us to refine the manuscript with it.
Best regards,
Raquel
-
RC2: 'Comment on egusphere-2023-2282', Anonymous Referee #2, 25 Feb 2024
- AC2: 'Reply on RC2', Raquel González Armas, 12 Mar 2024
Peer review completion
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Raquel González-Armas
Jordi Vilà-Guerau de Arellano
Mary Rose Mangan
Oscar Hartogensis
Hugo de Boer
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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(5491 KB) - Metadata XML
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Supplement
(267 KB) - BibTeX
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- Final revised paper