Was Australia a sink or source of CO<sub>2</sub> in 2015? Data assimilation using OCO-2 satellite measurements
<p>In this study, we present the assimilation of data from the Orbiting Carbon Observatory-2 (OCO-2) (land nadir and glint data, version 9) to estimate the Australian carbon surface fluxes for the year 2015. To perform this estimation, we used both a regional-scale atmospheric transport–disper...
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2021
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oai:doaj.org-article:098ad9b128ef46a4bb5f39f9f8134edd2021-12-01T14:18:11ZWas Australia a sink or source of CO<sub>2</sub> in 2015? Data assimilation using OCO-2 satellite measurements10.5194/acp-21-17453-20211680-73161680-7324https://doaj.org/article/098ad9b128ef46a4bb5f39f9f8134edd2021-12-01T00:00:00Zhttps://acp.copernicus.org/articles/21/17453/2021/acp-21-17453-2021.pdfhttps://doaj.org/toc/1680-7316https://doaj.org/toc/1680-7324<p>In this study, we present the assimilation of data from the Orbiting Carbon Observatory-2 (OCO-2) (land nadir and glint data, version 9) to estimate the Australian carbon surface fluxes for the year 2015. To perform this estimation, we used both a regional-scale atmospheric transport–dispersion model and a four-dimensional variational assimilation scheme. Our results suggest that Australia was a carbon sink of <span class="inline-formula">−</span>0.41 <span class="inline-formula">±</span> 0.08 PgC yr<span class="inline-formula"><sup>−1</sup></span> compared to the prior estimate 0.09 <span class="inline-formula">±</span> 0.20 PgC yr<span class="inline-formula"><sup>−1</sup></span> (excluding fossil fuel emissions). Most of the carbon uptake occurred in northern Australia over the savanna ecotype and in the western region over areas with sparse vegetation. Analysis of the enhanced vegetation index (EVI) suggests that the majority of the carbon uptake over the savanna ecosystem was due to an increase of vegetation productivity (positive EVI anomalies) amplified by an anomalous increase of rainfall in summer. Further from this, a slight increase of carbon uptake in Western Australia over areas with sparse vegetation (the largest ecosystem in Australia) was noted due to increased land productivity in the area caused by positive rainfall anomalies. The stronger carbon uptake estimate in this ecosystem was partially due to the land surface model (CABLE-BIOS3) underestimating the gross primary productivity of the ecosystem. To evaluate the accuracy of our carbon flux estimates from OCO-2 retrievals, we compare our posterior concentration fields against the column-averaged carbon retrievals from the Total Carbon Column Observing Network (TCCON) and ground-based in situ monitoring sites located around our domain. The validation analysis against TCCON shows that our system is able to reduce bias mainly in the summer season. Comparison with surface in situ observations was less successful, particularly over oceanic monitoring sites that are strongly affected by oceanic fluxes and subject to less freedom by the inversion. For stations located far from the coast, the comparison with in situ data was more variable, suggesting difficulties matching the column-integrated and surface data by the inversion, most likely linked to model vertical transport. Comparison of our fluxes against the OCO-2 model intercomparison (MIP) was encouraging. The annual carbon uptake estimated by our inversion falls within the ensemble of the OCO-2 MIP global inversions and presents a similar seasonal pattern.</p>Y. VillalobosY. VillalobosY. VillalobosP. J. RaynerP. J. RaynerP. J. RaynerJ. D. SilverJ. D. SilverS. ThomasV. HaverdJ. KnauerZ. M. LohN. M. DeutscherD. W. T. GriffithD. F. PollardCopernicus PublicationsarticlePhysicsQC1-999ChemistryQD1-999ENAtmospheric Chemistry and Physics, Vol 21, Pp 17453-17494 (2021) |
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Physics QC1-999 Chemistry QD1-999 |
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Physics QC1-999 Chemistry QD1-999 Y. Villalobos Y. Villalobos Y. Villalobos P. J. Rayner P. J. Rayner P. J. Rayner J. D. Silver J. D. Silver S. Thomas V. Haverd J. Knauer Z. M. Loh N. M. Deutscher D. W. T. Griffith D. F. Pollard Was Australia a sink or source of CO<sub>2</sub> in 2015? Data assimilation using OCO-2 satellite measurements |
| description |
<p>In this study, we present the assimilation of data from the Orbiting Carbon Observatory-2 (OCO-2) (land nadir and glint data, version 9) to estimate the Australian carbon surface fluxes for the year 2015. To perform this estimation, we used both a regional-scale atmospheric transport–dispersion model and a four-dimensional variational assimilation scheme. Our results suggest that Australia was a carbon sink of <span class="inline-formula">−</span>0.41 <span class="inline-formula">±</span> 0.08 PgC yr<span class="inline-formula"><sup>−1</sup></span> compared to the prior estimate 0.09 <span class="inline-formula">±</span> 0.20 PgC yr<span class="inline-formula"><sup>−1</sup></span> (excluding fossil fuel emissions). Most of the carbon uptake occurred in northern Australia over the savanna ecotype and in the western region over areas with sparse vegetation. Analysis of the enhanced vegetation index (EVI) suggests that the majority of the carbon uptake over the savanna ecosystem was due to an increase of vegetation productivity (positive EVI anomalies) amplified by an anomalous increase of rainfall in summer. Further from this, a slight increase of carbon uptake in Western Australia over areas with sparse vegetation (the largest ecosystem in Australia) was noted due to increased land productivity in the area caused by positive rainfall anomalies. The stronger carbon uptake estimate in this ecosystem was partially due to the land surface model (CABLE-BIOS3) underestimating the gross primary productivity of the ecosystem. To evaluate the accuracy of our carbon flux estimates from OCO-2 retrievals, we compare our posterior concentration fields against the column-averaged carbon retrievals from the Total Carbon Column Observing Network (TCCON) and ground-based in situ monitoring sites located around our domain. The validation analysis against TCCON shows that our system is able to reduce bias mainly in the summer season. Comparison with surface in situ observations was less successful, particularly over oceanic monitoring sites that are strongly affected by oceanic fluxes and subject to less freedom by the inversion. For stations located far from the coast, the comparison with in situ data was more variable, suggesting difficulties matching the column-integrated and surface data by the inversion, most likely linked to model vertical transport. Comparison of our fluxes against the OCO-2 model intercomparison (MIP) was encouraging. The annual carbon uptake estimated by our inversion falls within the ensemble of the OCO-2 MIP global inversions and presents a similar seasonal pattern.</p> |
| format |
article |
| author |
Y. Villalobos Y. Villalobos Y. Villalobos P. J. Rayner P. J. Rayner P. J. Rayner J. D. Silver J. D. Silver S. Thomas V. Haverd J. Knauer Z. M. Loh N. M. Deutscher D. W. T. Griffith D. F. Pollard |
| author_facet |
Y. Villalobos Y. Villalobos Y. Villalobos P. J. Rayner P. J. Rayner P. J. Rayner J. D. Silver J. D. Silver S. Thomas V. Haverd J. Knauer Z. M. Loh N. M. Deutscher D. W. T. Griffith D. F. Pollard |
| author_sort |
Y. Villalobos |
| title |
Was Australia a sink or source of CO<sub>2</sub> in 2015? Data assimilation using OCO-2 satellite measurements |
| title_short |
Was Australia a sink or source of CO<sub>2</sub> in 2015? Data assimilation using OCO-2 satellite measurements |
| title_full |
Was Australia a sink or source of CO<sub>2</sub> in 2015? Data assimilation using OCO-2 satellite measurements |
| title_fullStr |
Was Australia a sink or source of CO<sub>2</sub> in 2015? Data assimilation using OCO-2 satellite measurements |
| title_full_unstemmed |
Was Australia a sink or source of CO<sub>2</sub> in 2015? Data assimilation using OCO-2 satellite measurements |
| title_sort |
was australia a sink or source of co<sub>2</sub> in 2015? data assimilation using oco-2 satellite measurements |
| publisher |
Copernicus Publications |
| publishDate |
2021 |
| url |
https://doaj.org/article/098ad9b128ef46a4bb5f39f9f8134edd |
| work_keys_str_mv |
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