Reviews and syntheses: An empirical spatiotemporal description of the global surface–atmosphere carbon fluxes: opportunities and data limitations
Understanding the global carbon (C) cycle is of crucial importance to map current and future climate dynamics relative to global environmental change. A full characterization of C cycling requires detailed information on spatiotemporal patterns of surface–atmosphere fluxes. However, relevant C c...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-08-01
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| Series: | Biogeosciences |
| Online Access: | https://www.biogeosciences.net/14/3685/2017/bg-14-3685-2017.pdf |
| _version_ | 1818549527780524032 |
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| author | J. Zscheischler J. Zscheischler M. D. Mahecha M. D. Mahecha M. D. Mahecha V. Avitabile L. Calle N. Carvalhais N. Carvalhais P. Ciais F. Gans N. Gruber J. Hartmann M. Herold K. Ichii K. Ichii M. Jung P. Landschützer P. Landschützer G. G. Laruelle R. Lauerwald R. Lauerwald D. Papale P. Peylin B. Poulter B. Poulter D. Ray P. Regnier C. Rödenbeck R. M. Roman-Cuesta C. Schwalm G. Tramontana A. Tyukavina R. Valentini G. van der Werf T. O. West J. E. Wolf M. Reichstein M. Reichstein M. Reichstein |
| author_facet | J. Zscheischler J. Zscheischler M. D. Mahecha M. D. Mahecha M. D. Mahecha V. Avitabile L. Calle N. Carvalhais N. Carvalhais P. Ciais F. Gans N. Gruber J. Hartmann M. Herold K. Ichii K. Ichii M. Jung P. Landschützer P. Landschützer G. G. Laruelle R. Lauerwald R. Lauerwald D. Papale P. Peylin B. Poulter B. Poulter D. Ray P. Regnier C. Rödenbeck R. M. Roman-Cuesta C. Schwalm G. Tramontana A. Tyukavina R. Valentini G. van der Werf T. O. West J. E. Wolf M. Reichstein M. Reichstein M. Reichstein |
| author_sort | J. Zscheischler |
| collection | DOAJ |
| description | Understanding the global carbon (C) cycle is of crucial importance
to map current and future climate dynamics relative to global environmental
change. A full characterization of C cycling requires detailed information on
spatiotemporal patterns of surface–atmosphere fluxes. However, relevant C
cycle observations are highly variable in their coverage and reporting
standards. Especially problematic is the lack of integration of the carbon
dioxide (CO<sub>2</sub>) exchange of the ocean, inland freshwaters and the land
surface with the atmosphere. Here we adopt a data-driven approach to
synthesize a wide range of observation-based spatially explicit
surface–atmosphere CO<sub>2</sub> fluxes from 2001 to 2010, to identify the state
of today's observational opportunities and data limitations. The considered
fluxes include net exchange of open oceans, continental shelves, estuaries,
rivers, and lakes, as well as CO<sub>2</sub> fluxes related to net ecosystem
productivity, fire emissions, loss of tropical aboveground C, harvested wood
and crops, as well as fossil fuel and cement emissions. Spatially explicit
CO<sub>2</sub> fluxes are obtained through geostatistical and/or remote-sensing-based upscaling, thereby minimizing biophysical or biogeochemical
assumptions encoded in process-based models. We estimate a bottom-up net C
exchange (NCE) between the surface (land, ocean, and coastal areas) and the
atmosphere. Though we provide also global estimates, the primary goal of this
study is to identify key uncertainties and observational shortcomings that
need to be prioritized in the expansion of in situ observatories.
Uncertainties for NCE and its components are derived using resampling. In
many regions, our NCE estimates agree well with independent estimates from
other sources such as process-based models and atmospheric inversions. This
holds for Europe (mean ± 1 SD: 0.8 ± 0.1 PgC yr<sup>−1</sup>,
positive numbers are sources to the atmosphere), Russia
(0.1 ± 0.4 PgC yr<sup>−1</sup>), East Asia
(1.6 ± 0.3 PgC yr<sup>−1</sup>), South Asia
(0.3 ± 0.1 PgC yr<sup>−1</sup>), Australia
(0.2 ± 0.3 PgC yr<sup>−1</sup>), and most of the Ocean regions. Our NCE
estimates give a likely too large CO<sub>2</sub> sink in tropical areas such as the
Amazon, Congo, and Indonesia. Overall, and because of the overestimated
CO<sub>2</sub> uptake in tropical lands, our global bottom-up NCE amounts to a net
sink of −5.4 ± 2.0 PgC yr<sup>−1</sup>. By contrast, the accurately
measured mean atmospheric growth rate of CO<sub>2</sub> over 2001–2010 indicates
that the true value of NCE is a net CO<sub>2</sub> source of
4.3 ± 0.1 PgC yr<sup>−1</sup>. This mismatch of nearly 10 PgC yr<sup>−1</sup>
highlights observational gaps and limitations of data-driven models in
tropical lands, but also in North America. Our uncertainty assessment
provides the basis for setting priority regions where to increase carbon
observations in the future. High on the priority list are tropical land
regions, which suffer from a lack of in situ observations. Second, extensive
<i>p</i>CO<sub>2</sub> data are missing in the Southern Ocean. Third, we lack
observations that could enable seasonal estimates of shelf, estuary, and
inland water–atmosphere C exchange. Our consistent derivation of data
uncertainties could serve as prior knowledge in multicriteria optimization
such as the Carbon Cycle Data Assimilation System (CCDAS) and atmospheric
inversions, without over- or under-stating bottom-up data credibility. In the
future, NCE estimates of carbon sinks could be aggregated at national scale
to compare with the official national inventories of CO<sub>2</sub> fluxes in the
land use, land use change, and forestry sector, upon which future emission
reductions are proposed. |
| first_indexed | 2024-12-12T08:34:31Z |
| format | Article |
| id | doaj.art-f4ddd340af654b47a3aa1976405c90f7 |
| institution | Directory Open Access Journal |
| issn | 1726-4170 1726-4189 |
| language | English |
| last_indexed | 2024-12-12T08:34:31Z |
| publishDate | 2017-08-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Biogeosciences |
| spelling | doaj.art-f4ddd340af654b47a3aa1976405c90f72022-12-22T00:31:00ZengCopernicus PublicationsBiogeosciences1726-41701726-41892017-08-01143685370310.5194/bg-14-3685-2017Reviews and syntheses: An empirical spatiotemporal description of the global surface–atmosphere carbon fluxes: opportunities and data limitationsJ. Zscheischler0J. Zscheischler1M. D. Mahecha2M. D. Mahecha3M. D. Mahecha4V. Avitabile5L. Calle6N. Carvalhais7N. Carvalhais8P. Ciais9F. Gans10N. Gruber11J. Hartmann12M. Herold13K. Ichii14K. Ichii15M. Jung16P. Landschützer17P. Landschützer18G. G. Laruelle19R. Lauerwald20R. Lauerwald21D. Papale22P. Peylin23B. Poulter24B. Poulter25D. Ray26P. Regnier27C. Rödenbeck28R. M. Roman-Cuesta29C. Schwalm30G. Tramontana31A. Tyukavina32R. Valentini33G. van der Werf34T. O. West35J. E. Wolf36M. Reichstein37M. Reichstein38M. Reichstein39Institute for Atmospheric and Climate Science, ETH Zurich, Universitätstr. 16, 8092 Zurich, SwitzerlandMax Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, 07745 Jena, GermanyMax Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, 07745 Jena, GermanyGerman Centre for Integrative Biodiversity Research (iDiv), Deutscher Platz 5e, 04103 Leipzig, GermanyMichael Stifel Center Jena for Data-Driven and Simulation Science, 07743 Jena, GermanyWageningen University & Research, Laboratory of Geo-Information Science and Remote Sensing, Droevendaalsesteeg 3, 6708 PB Wageningen, the NetherlandsInstitute on Ecosystems and Department of Ecology, Montana State University, Bozeman, MT 59717, USAMax Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, 07745 Jena, GermanyCENSE, Departamento de Ciências e Engenharia do Ambiente, Faculdade de Ciências e Tecnologia, Universidade NOVA de Lisboa, Caparica, PortugalLaboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, 91191, Gif sur Yvette, FranceMax Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, 07745 Jena, GermanyInstitute of Biogeochemistry and Pollutant Dynamics, ETH Zurich, Zurich, SwitzerlandInstitute for Geology, CEN – Center for Earth System Research and Sustainability, University of Hamburg, Hamburg, Germany 55, 20146 Hamburg, GermanyWageningen University & Research, Laboratory of Geo-Information Science and Remote Sensing, Droevendaalsesteeg 3, 6708 PB Wageningen, the NetherlandsDepartment of Environmental Geochemical Cycle Research, Agency for Marine-Earth Science and Technology, Yokohama, JapanCenter for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, JapanMax Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, 07745 Jena, GermanyInstitute of Biogeochemistry and Pollutant Dynamics, ETH Zurich, Zurich, SwitzerlandMax Planck Institute for Meteorology, Bundesstr. 53, Hamburg, GermanyDept. Geoscience, Environment & Society (DGES), CP160/02, Université Libre de Bruxelles, 1050 Brussels, BelgiumDept. Geoscience, Environment & Society (DGES), CP160/02, Université Libre de Bruxelles, 1050 Brussels, BelgiumCollege of Engineering, Mathematics and Physical Sciences, University of Exeter, EX4 4QE Exeter, Devon, UKDepartment for Innovation in Biological, Agro-food and Forest systems (DIBAF), University of Tuscia, Viterbo, 01100, ItalyCENSE, Departamento de Ciências e Engenharia do Ambiente, Faculdade de Ciências e Tecnologia, Universidade NOVA de Lisboa, Caparica, PortugalInstitute on Ecosystems and Department of Ecology, Montana State University, Bozeman, MT 59717, USANASA Goddard Space Flight Center, Biospheric Sciences Laboratory, Greenbelt, MD 20771, USAInstitute on the Environment (IonE), University of Minnesota, Saint Paul, MN 55108, USADept. Geoscience, Environment & Society (DGES), CP160/02, Université Libre de Bruxelles, 1050 Brussels, BelgiumMax Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, 07745 Jena, GermanyWageningen University & Research, Laboratory of Geo-Information Science and Remote Sensing, Droevendaalsesteeg 3, 6708 PB Wageningen, the NetherlandsWoods Hole Research Center, Falmouth MA 02540, USADepartment for Innovation in Biological, Agro-food and Forest systems (DIBAF), University of Tuscia, Viterbo, 01100, ItalyDepartment of Geographical Sciences, University of Maryland, College Park, MD, USACMCC, Via A. Imperatore, 16, 73100, Lecce, ItalyFaculty of Earth and Life Sciences, Vrije Universiteit Amsterdam, Amsterdam, the NetherlandsJoint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD, USAJoint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD, USAMax Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, 07745 Jena, GermanyGerman Centre for Integrative Biodiversity Research (iDiv), Deutscher Platz 5e, 04103 Leipzig, GermanyMichael Stifel Center Jena for Data-Driven and Simulation Science, 07743 Jena, GermanyUnderstanding the global carbon (C) cycle is of crucial importance to map current and future climate dynamics relative to global environmental change. A full characterization of C cycling requires detailed information on spatiotemporal patterns of surface–atmosphere fluxes. However, relevant C cycle observations are highly variable in their coverage and reporting standards. Especially problematic is the lack of integration of the carbon dioxide (CO<sub>2</sub>) exchange of the ocean, inland freshwaters and the land surface with the atmosphere. Here we adopt a data-driven approach to synthesize a wide range of observation-based spatially explicit surface–atmosphere CO<sub>2</sub> fluxes from 2001 to 2010, to identify the state of today's observational opportunities and data limitations. The considered fluxes include net exchange of open oceans, continental shelves, estuaries, rivers, and lakes, as well as CO<sub>2</sub> fluxes related to net ecosystem productivity, fire emissions, loss of tropical aboveground C, harvested wood and crops, as well as fossil fuel and cement emissions. Spatially explicit CO<sub>2</sub> fluxes are obtained through geostatistical and/or remote-sensing-based upscaling, thereby minimizing biophysical or biogeochemical assumptions encoded in process-based models. We estimate a bottom-up net C exchange (NCE) between the surface (land, ocean, and coastal areas) and the atmosphere. Though we provide also global estimates, the primary goal of this study is to identify key uncertainties and observational shortcomings that need to be prioritized in the expansion of in situ observatories. Uncertainties for NCE and its components are derived using resampling. In many regions, our NCE estimates agree well with independent estimates from other sources such as process-based models and atmospheric inversions. This holds for Europe (mean ± 1 SD: 0.8 ± 0.1 PgC yr<sup>−1</sup>, positive numbers are sources to the atmosphere), Russia (0.1 ± 0.4 PgC yr<sup>−1</sup>), East Asia (1.6 ± 0.3 PgC yr<sup>−1</sup>), South Asia (0.3 ± 0.1 PgC yr<sup>−1</sup>), Australia (0.2 ± 0.3 PgC yr<sup>−1</sup>), and most of the Ocean regions. Our NCE estimates give a likely too large CO<sub>2</sub> sink in tropical areas such as the Amazon, Congo, and Indonesia. Overall, and because of the overestimated CO<sub>2</sub> uptake in tropical lands, our global bottom-up NCE amounts to a net sink of −5.4 ± 2.0 PgC yr<sup>−1</sup>. By contrast, the accurately measured mean atmospheric growth rate of CO<sub>2</sub> over 2001–2010 indicates that the true value of NCE is a net CO<sub>2</sub> source of 4.3 ± 0.1 PgC yr<sup>−1</sup>. This mismatch of nearly 10 PgC yr<sup>−1</sup> highlights observational gaps and limitations of data-driven models in tropical lands, but also in North America. Our uncertainty assessment provides the basis for setting priority regions where to increase carbon observations in the future. High on the priority list are tropical land regions, which suffer from a lack of in situ observations. Second, extensive <i>p</i>CO<sub>2</sub> data are missing in the Southern Ocean. Third, we lack observations that could enable seasonal estimates of shelf, estuary, and inland water–atmosphere C exchange. Our consistent derivation of data uncertainties could serve as prior knowledge in multicriteria optimization such as the Carbon Cycle Data Assimilation System (CCDAS) and atmospheric inversions, without over- or under-stating bottom-up data credibility. In the future, NCE estimates of carbon sinks could be aggregated at national scale to compare with the official national inventories of CO<sub>2</sub> fluxes in the land use, land use change, and forestry sector, upon which future emission reductions are proposed.https://www.biogeosciences.net/14/3685/2017/bg-14-3685-2017.pdf |
| spellingShingle | J. Zscheischler J. Zscheischler M. D. Mahecha M. D. Mahecha M. D. Mahecha V. Avitabile L. Calle N. Carvalhais N. Carvalhais P. Ciais F. Gans N. Gruber J. Hartmann M. Herold K. Ichii K. Ichii M. Jung P. Landschützer P. Landschützer G. G. Laruelle R. Lauerwald R. Lauerwald D. Papale P. Peylin B. Poulter B. Poulter D. Ray P. Regnier C. Rödenbeck R. M. Roman-Cuesta C. Schwalm G. Tramontana A. Tyukavina R. Valentini G. van der Werf T. O. West J. E. Wolf M. Reichstein M. Reichstein M. Reichstein Reviews and syntheses: An empirical spatiotemporal description of the global surface–atmosphere carbon fluxes: opportunities and data limitations Biogeosciences |
| title | Reviews and syntheses: An empirical spatiotemporal description of the global surface–atmosphere carbon fluxes: opportunities and data limitations |
| title_full | Reviews and syntheses: An empirical spatiotemporal description of the global surface–atmosphere carbon fluxes: opportunities and data limitations |
| title_fullStr | Reviews and syntheses: An empirical spatiotemporal description of the global surface–atmosphere carbon fluxes: opportunities and data limitations |
| title_full_unstemmed | Reviews and syntheses: An empirical spatiotemporal description of the global surface–atmosphere carbon fluxes: opportunities and data limitations |
| title_short | Reviews and syntheses: An empirical spatiotemporal description of the global surface–atmosphere carbon fluxes: opportunities and data limitations |
| title_sort | reviews and syntheses an empirical spatiotemporal description of the global surface atmosphere carbon fluxes opportunities and data limitations |
| url | https://www.biogeosciences.net/14/3685/2017/bg-14-3685-2017.pdf |
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