Assimilation of multiple datasets results in large differences in regional- to global-scale NEE and GPP budgets simulated by a terrestrial biosphere model
<p>In spite of the importance of land ecosystems in offsetting carbon dioxide emissions released by anthropogenic activities into the atmosphere, the spatiotemporal dynamics of terrestrial carbon fluxes remain largely uncertain at regional to global scales. Over the past decade, data assimilat...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2023-03-01
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| Series: | Biogeosciences |
| Online Access: | https://bg.copernicus.org/articles/20/1089/2023/bg-20-1089-2023.pdf |
| _version_ | 1797861463841308672 |
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| author | C. Bacour C. Bacour N. MacBean F. Chevallier S. Léonard S. Léonard E. N. Koffi E. N. Koffi P. Peylin |
| author_facet | C. Bacour C. Bacour N. MacBean F. Chevallier S. Léonard S. Léonard E. N. Koffi E. N. Koffi P. Peylin |
| author_sort | C. Bacour |
| collection | DOAJ |
| description | <p>In spite of the importance of land ecosystems in offsetting carbon dioxide
emissions released by anthropogenic activities into the atmosphere, the
spatiotemporal dynamics of terrestrial carbon fluxes remain largely
uncertain at regional to global scales. Over the past decade, data
assimilation (DA) techniques have grown in importance for improving these
fluxes simulated by terrestrial biosphere models (TBMs), by optimizing model
parameter values while also pinpointing possible parameterization
deficiencies. Although the joint assimilation of multiple data streams is
expected to constrain a wider range of model processes, their actual
benefits in terms of reduction in model uncertainty are still
under-researched, also given the technical challenges. In this study, we
investigated with a consistent DA framework and the ORCHIDEE-LMDz
TBM–atmosphere model how the assimilation of different combinations of data
streams may result in different regional to global carbon budgets. To do so,
we performed comprehensive DA experiments where three datasets (in situ measurements
of net carbon exchange and latent heat fluxes, spaceborne estimates of the
normalized difference vegetation index, and atmospheric CO<span class="inline-formula"><sub>2</sub></span>
concentration data measured at stations) were assimilated alone or
simultaneously. We thus evaluated their complementarity and usefulness to
constrain net and gross C land fluxes. We found that a major challenge in
improving the spatial distribution of the land C sinks and sources with
atmospheric CO<span class="inline-formula"><sub>2</sub></span> data relates to the correction of the soil carbon
imbalance.</p> |
| first_indexed | 2024-04-09T22:02:54Z |
| format | Article |
| id | doaj.art-15d950b110ba4472b4f00e807a91041f |
| institution | Directory Open Access Journal |
| issn | 1726-4170 1726-4189 |
| language | English |
| last_indexed | 2024-04-09T22:02:54Z |
| publishDate | 2023-03-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Biogeosciences |
| spelling | doaj.art-15d950b110ba4472b4f00e807a91041f2023-03-23T12:48:16ZengCopernicus PublicationsBiogeosciences1726-41701726-41892023-03-01201089111110.5194/bg-20-1089-2023Assimilation of multiple datasets results in large differences in regional- to global-scale NEE and GPP budgets simulated by a terrestrial biosphere modelC. Bacour0C. Bacour1N. MacBean2F. Chevallier3S. Léonard4S. Léonard5E. N. Koffi6E. N. Koffi7P. Peylin8Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, 91191, Franceformerly at: NOVELTIS, Labège, FranceDepartments of Geography & Environment and Biology, Western University, London, Ontario, CanadaLaboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, 91191, FranceLaboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, 91191, Francenow at: Air Liquide R&D, Innovation Campus Paris, Les-Loges-en-Josas, FranceLaboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, 91191, Francenow at: European Centre for Medium-Range Weather Forecasts, Robert-Schuman-Platz 3, 53175 Bonn, GermanyLaboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, 91191, France<p>In spite of the importance of land ecosystems in offsetting carbon dioxide emissions released by anthropogenic activities into the atmosphere, the spatiotemporal dynamics of terrestrial carbon fluxes remain largely uncertain at regional to global scales. Over the past decade, data assimilation (DA) techniques have grown in importance for improving these fluxes simulated by terrestrial biosphere models (TBMs), by optimizing model parameter values while also pinpointing possible parameterization deficiencies. Although the joint assimilation of multiple data streams is expected to constrain a wider range of model processes, their actual benefits in terms of reduction in model uncertainty are still under-researched, also given the technical challenges. In this study, we investigated with a consistent DA framework and the ORCHIDEE-LMDz TBM–atmosphere model how the assimilation of different combinations of data streams may result in different regional to global carbon budgets. To do so, we performed comprehensive DA experiments where three datasets (in situ measurements of net carbon exchange and latent heat fluxes, spaceborne estimates of the normalized difference vegetation index, and atmospheric CO<span class="inline-formula"><sub>2</sub></span> concentration data measured at stations) were assimilated alone or simultaneously. We thus evaluated their complementarity and usefulness to constrain net and gross C land fluxes. We found that a major challenge in improving the spatial distribution of the land C sinks and sources with atmospheric CO<span class="inline-formula"><sub>2</sub></span> data relates to the correction of the soil carbon imbalance.</p>https://bg.copernicus.org/articles/20/1089/2023/bg-20-1089-2023.pdf |
| spellingShingle | C. Bacour C. Bacour N. MacBean F. Chevallier S. Léonard S. Léonard E. N. Koffi E. N. Koffi P. Peylin Assimilation of multiple datasets results in large differences in regional- to global-scale NEE and GPP budgets simulated by a terrestrial biosphere model Biogeosciences |
| title | Assimilation of multiple datasets results in large differences in regional- to global-scale NEE and GPP budgets simulated by a terrestrial biosphere model |
| title_full | Assimilation of multiple datasets results in large differences in regional- to global-scale NEE and GPP budgets simulated by a terrestrial biosphere model |
| title_fullStr | Assimilation of multiple datasets results in large differences in regional- to global-scale NEE and GPP budgets simulated by a terrestrial biosphere model |
| title_full_unstemmed | Assimilation of multiple datasets results in large differences in regional- to global-scale NEE and GPP budgets simulated by a terrestrial biosphere model |
| title_short | Assimilation of multiple datasets results in large differences in regional- to global-scale NEE and GPP budgets simulated by a terrestrial biosphere model |
| title_sort | assimilation of multiple datasets results in large differences in regional to global scale nee and gpp budgets simulated by a terrestrial biosphere model |
| url | https://bg.copernicus.org/articles/20/1089/2023/bg-20-1089-2023.pdf |
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