Analysis of CO2, CH4 and CO surface and column concentrations observed at Reunion Island by assessing WRF-Chem simulations
- 1Royal Belgian Institute for Spacy Aeronomy (BIRA-IASB), Brussels, Belgium
- 2Laboratoire de l’Atmosphère et des Cyclones (LACy), UMR8105, Saint-Denis, Reunion Island, France
- 3UAR 3365 - OSU Réunion, Université de La Réunion, Saint-Denis, Reunion Island, France
- 4UR SPHERES, Department of Astrophysics, Geophysics and Oceanography, University of Liège, Liège, Belgium
- 1Royal Belgian Institute for Spacy Aeronomy (BIRA-IASB), Brussels, Belgium
- 2Laboratoire de l’Atmosphère et des Cyclones (LACy), UMR8105, Saint-Denis, Reunion Island, France
- 3UAR 3365 - OSU Réunion, Université de La Réunion, Saint-Denis, Reunion Island, France
- 4UR SPHERES, Department of Astrophysics, Geophysics and Oceanography, University of Liège, Liège, Belgium
Abstract. Reunion Island is situated in the Indian Ocean and holds one of the very few atmospheric observatories in the tropical Southern Hemisphere. Moreover, it hosts experiments providing both ground-based surface and column observations of CO2, CH4 and CO atmospheric concentrations. This work presents a comprehensive study of these observations made in the capital Saint-Denis and at the high-altitude Maïdo Observatory. We used simulations of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), in its passive tracer option (WRF-GHG), to gain more insight in the factors that determine the observed concentrations. Additionally, this study provides an evaluation of the WRF-GHG performance in a region of the globe where it has not yet been applied.
A comparison of the basic meteorological fields near the surface and along atmospheric profiles showed that WRF-GHG has decent skill in reproducing these meteorological measurements, especially temperature. Furthermore, a distinct diurnal CO2 cycle with values up to 450 ppm was found near the surface in Saint-Denis, driven by local anthropogenic emissions, boundary layer dynamics and accumulation due to low wind speed at night. Due to an overestimation of local wind speed, WRF-GHG underestimates this nocturnal buildup. At Maïdo, a similar diurnal cycle is found but with much smaller amplitude. There, surface CO2 is essentially driven by the surrounding vegetation. The hourly column-averaged mole fractions of CO2 (XCO2) of WRF-GHG and the corresponding TCCON observations were highly correlated with a coefficient of 0.90. These observations represent different air masses than those near the surface, they are influenced by processes from Madagascar, Africa and further away. The model shows contributions from fires during the Southern Hemisphere biomass burning season, but also biogenic enhancements associated with the dry season. Due to a seasonal bias in the boundary conditions, WRF-GHG fails to accurately reproduce the CH4 observations at Reunion Island. Further, local anthropogenic fluxes are the largest source influencing the surface CH4 observations. However, these are likely overestimated. Further, WRF-GHG is capable of simulating CO levels on Reunion Island with a high precision. As to the observed CO column (XCO), we confirmed that biomass burning plumes from Africa and elsewhere are important for explaining the observed variability. The in situ observations at the Maïdo Observatory can characterize both anthropogenic signals from the coastal regions and biomass burning enhancements from afar. Finally, we found that a high model resolution of 2 km is needed to accurately represent the surface observations. At Maïdo an even higher resolution might be needed because of the complex topography and local wind patterns. To simulate the column FTIR observations on the other hand, a model resolution of 50 km might already be sufficient.
Sieglinde Callewaert et al.
Status: closed
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RC1: 'Comment on acp-2022-106', Anonymous Referee #1, 16 Mar 2022
The comment was uploaded in the form of a supplement: https://acp.copernicus.org/preprints/acp-2022-106/acp-2022-106-RC1-supplement.pdf
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AC1: 'Final author comments', Sieglinde Callewaert, 20 May 2022
The comment was uploaded in the form of a supplement: https://acp.copernicus.org/preprints/acp-2022-106/acp-2022-106-RC1-supplement.pdf
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AC1: 'Final author comments', Sieglinde Callewaert, 20 May 2022
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RC2: 'Comment on acp-2022-106', Anonymous Referee #2, 15 Apr 2022
Callewaert et al. present a comparison of modelled and observed in-situ dry air mole fraction and the total column-averaged dry-air mole fraction of CO2, CO and CH4 at two sites on Reunion Island (St-Denis and Maido observatory). The atmospheric composition is modelled using a nested version of WRF-GHG with different emission priors, while observations are performed using cavity ring-down spectrometers and solar tracking FTIR systems.
The study demonstrates a good ability for WRF-GHG to reproduce atmospheric temperature and a limited ability to reconstruct atmospheric wind patterns (with a significant high bias in wind speed). Total column and in-situ observations correlate well for atmospheric CO and CO2, while CH4 data shows a surprisingly low correlation coefficient.
Overall, the paper is well written and nicely structured, so readers can follow the logic of the comparison. It presents and discusses atmospheric data from a chronically under-sampled region (Indian Ocean) with the aid of a state of the art atmospheric transport model. The analysis is sound and the scope of the paper well suited for ACP and its readers. After addressing the suggestions and technical correction below, I can fully recommend the paper for publication.
General comments:
Some results warrant a more detailed discussion, especially the issue of the low correlation of CH4. Looking at Figure 6 (b) and (d) seems to suggest that there could be two apparent distributions for CH4 that, if fitted separately, could produce much more reasonable slopes and improved coefficients. Have you attempted to separate the data based on external drivers that could explain the two distributions?
Minor and technical comments:
L1: The authors should consider changing the title as they report modelling result using WRF-GHG (passive tracer) rather than the version of WRF with active chemistry (WRF-CHEM).
L14: please add that the Pearson’s correlation coefficient was used here.
L67: please correct “etc…”
L83: please elaborate on what “…” refers to or just give the elements in the brackets as an example.
L225, Figure 2: please consider adding the information on the vertical resolution and top of the domain in the caption of Figure 2
L309: please change to “… agree less well …”
L337: Please elaborate on the assumption that there is “no vegetation within the city”.
A simple search of aerial photos of St. Denis reveals multiple parks and vegetation along the shoreline. Maybe the assumption is rather that the impact of local vegetation is negligible compared to fossil fuel combustion?
L368: Is the statement related to the nighttime respiration true in general or here specifically for a local imbalance in the boundary layer.
-
AC1: 'Final author comments', Sieglinde Callewaert, 20 May 2022
Callewaert et al. present a comparison of modelled and observed in-situ dry air mole fraction and the total column-averaged dry-air mole fraction of CO2, CO and CH4 at two sites on Reunion Island (St-Denis and Maido observatory). The atmospheric composition is modelled using a nested version of WRF-GHG with different emission priors, while observations are performed using cavity ring-down spectrometers and solar tracking FTIR systems.
The study demonstrates a good ability for WRF-GHG to reproduce atmospheric temperature and a limited ability to reconstruct atmospheric wind patterns (with a significant high bias in wind speed). Total column and in-situ observations correlate well for atmospheric CO and CO2, while CH4 data shows a surprisingly low correlation coefficient.
Overall, the paper is well written and nicely structured, so readers can follow the logic of the comparison. It presents and discusses atmospheric data from a chronically under-sampled region (Indian Ocean) with the aid of a state of the art atmospheric transport model. The analysis is sound and the scope of the paper well suited for ACP and its readers. After addressing the suggestions and technical correction below, I can fully recommend the paper for publication.
General comments:
Some results warrant a more detailed discussion, especially the issue of the low correlation of CH4. Looking at Figure 6 (b) and (d) seems to suggest that there could be two apparent distributions for CH4 that, if fitted separately, could produce much more reasonable slopes and improved coefficients. Have you attempted to separate the data based on external drivers that could explain the two distributions?
Minor and technical comments:
L1: The authors should consider changing the title as they report modelling result using WRF-GHG (passive tracer) rather than the version of WRF with active chemistry (WRF-CHEM).
L14: please add that the Pearson’s correlation coefficient was used here.
L67: please correct “etc…”
L83: please elaborate on what “…” refers to or just give the elements in the brackets as an example.
L225, Figure 2: please consider adding the information on the vertical resolution and top of the domain in the caption of Figure 2
L309: please change to “… agree less well …”
L337: Please elaborate on the assumption that there is “no vegetation within the city”.
A simple search of aerial photos of St. Denis reveals multiple parks and vegetation along the shoreline. Maybe the assumption is rather that the impact of local vegetation is negligible compared to fossil fuel combustion?
L368: Is the statement related to the nighttime respiration true in general or here specifically for a local imbalance in the boundary layer.
-
AC1: 'Final author comments', Sieglinde Callewaert, 20 May 2022
- AC1: 'Final author comments', Sieglinde Callewaert, 20 May 2022
Status: closed
-
RC1: 'Comment on acp-2022-106', Anonymous Referee #1, 16 Mar 2022
The comment was uploaded in the form of a supplement: https://acp.copernicus.org/preprints/acp-2022-106/acp-2022-106-RC1-supplement.pdf
-
AC1: 'Final author comments', Sieglinde Callewaert, 20 May 2022
The comment was uploaded in the form of a supplement: https://acp.copernicus.org/preprints/acp-2022-106/acp-2022-106-RC1-supplement.pdf
-
AC1: 'Final author comments', Sieglinde Callewaert, 20 May 2022
-
RC2: 'Comment on acp-2022-106', Anonymous Referee #2, 15 Apr 2022
Callewaert et al. present a comparison of modelled and observed in-situ dry air mole fraction and the total column-averaged dry-air mole fraction of CO2, CO and CH4 at two sites on Reunion Island (St-Denis and Maido observatory). The atmospheric composition is modelled using a nested version of WRF-GHG with different emission priors, while observations are performed using cavity ring-down spectrometers and solar tracking FTIR systems.
The study demonstrates a good ability for WRF-GHG to reproduce atmospheric temperature and a limited ability to reconstruct atmospheric wind patterns (with a significant high bias in wind speed). Total column and in-situ observations correlate well for atmospheric CO and CO2, while CH4 data shows a surprisingly low correlation coefficient.
Overall, the paper is well written and nicely structured, so readers can follow the logic of the comparison. It presents and discusses atmospheric data from a chronically under-sampled region (Indian Ocean) with the aid of a state of the art atmospheric transport model. The analysis is sound and the scope of the paper well suited for ACP and its readers. After addressing the suggestions and technical correction below, I can fully recommend the paper for publication.
General comments:
Some results warrant a more detailed discussion, especially the issue of the low correlation of CH4. Looking at Figure 6 (b) and (d) seems to suggest that there could be two apparent distributions for CH4 that, if fitted separately, could produce much more reasonable slopes and improved coefficients. Have you attempted to separate the data based on external drivers that could explain the two distributions?
Minor and technical comments:
L1: The authors should consider changing the title as they report modelling result using WRF-GHG (passive tracer) rather than the version of WRF with active chemistry (WRF-CHEM).
L14: please add that the Pearson’s correlation coefficient was used here.
L67: please correct “etc…”
L83: please elaborate on what “…” refers to or just give the elements in the brackets as an example.
L225, Figure 2: please consider adding the information on the vertical resolution and top of the domain in the caption of Figure 2
L309: please change to “… agree less well …”
L337: Please elaborate on the assumption that there is “no vegetation within the city”.
A simple search of aerial photos of St. Denis reveals multiple parks and vegetation along the shoreline. Maybe the assumption is rather that the impact of local vegetation is negligible compared to fossil fuel combustion?
L368: Is the statement related to the nighttime respiration true in general or here specifically for a local imbalance in the boundary layer.
-
AC1: 'Final author comments', Sieglinde Callewaert, 20 May 2022
Callewaert et al. present a comparison of modelled and observed in-situ dry air mole fraction and the total column-averaged dry-air mole fraction of CO2, CO and CH4 at two sites on Reunion Island (St-Denis and Maido observatory). The atmospheric composition is modelled using a nested version of WRF-GHG with different emission priors, while observations are performed using cavity ring-down spectrometers and solar tracking FTIR systems.
The study demonstrates a good ability for WRF-GHG to reproduce atmospheric temperature and a limited ability to reconstruct atmospheric wind patterns (with a significant high bias in wind speed). Total column and in-situ observations correlate well for atmospheric CO and CO2, while CH4 data shows a surprisingly low correlation coefficient.
Overall, the paper is well written and nicely structured, so readers can follow the logic of the comparison. It presents and discusses atmospheric data from a chronically under-sampled region (Indian Ocean) with the aid of a state of the art atmospheric transport model. The analysis is sound and the scope of the paper well suited for ACP and its readers. After addressing the suggestions and technical correction below, I can fully recommend the paper for publication.
General comments:
Some results warrant a more detailed discussion, especially the issue of the low correlation of CH4. Looking at Figure 6 (b) and (d) seems to suggest that there could be two apparent distributions for CH4 that, if fitted separately, could produce much more reasonable slopes and improved coefficients. Have you attempted to separate the data based on external drivers that could explain the two distributions?
Minor and technical comments:
L1: The authors should consider changing the title as they report modelling result using WRF-GHG (passive tracer) rather than the version of WRF with active chemistry (WRF-CHEM).
L14: please add that the Pearson’s correlation coefficient was used here.
L67: please correct “etc…”
L83: please elaborate on what “…” refers to or just give the elements in the brackets as an example.
L225, Figure 2: please consider adding the information on the vertical resolution and top of the domain in the caption of Figure 2
L309: please change to “… agree less well …”
L337: Please elaborate on the assumption that there is “no vegetation within the city”.
A simple search of aerial photos of St. Denis reveals multiple parks and vegetation along the shoreline. Maybe the assumption is rather that the impact of local vegetation is negligible compared to fossil fuel combustion?
L368: Is the statement related to the nighttime respiration true in general or here specifically for a local imbalance in the boundary layer.
-
AC1: 'Final author comments', Sieglinde Callewaert, 20 May 2022
- AC1: 'Final author comments', Sieglinde Callewaert, 20 May 2022
Sieglinde Callewaert et al.
Sieglinde Callewaert et al.
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