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Biogeosciences An interactive open-access journal of the European Geosciences Union
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Reviews and syntheses
20 Oct 2016
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A revision of this discussion paper was accepted for the journal Biogeosciences (BG) and is expected to appear here in due course.
An empirical spatiotemporal description of the global surface-atmosphere carbon fluxes: opportunities and data limitations
Jakob Zscheischler1,2, Miguel D. Mahecha2,3,4, Valerio Avitabile5, Leonardo Calle6, Nuno Carvalhais2,7, Philippe Ciais8, Fabian Gans2, Nicolas Gruber9, Jens Hartmann10, Martin Herold5, Kazuhito Ichii11,12, Martin Jung2, Peter Landschützer9,13, Goulven G. Laruelle14, Ronny Lauerwald14,15, Dario Papale16, Philippe Peylin7, Benjamin Poulter6,17, Deepak Ray18, Pierre Regnier14, Christian Rödenbeck1, Rosa M. Roman-Cuesta5, Christopher Schwalm19, Gianluca Tramontana16, Alexandra T. Tyukavina20, Ricardo Valentini21, Guido van der Werf22, Tristram O. West23, Julie E. Wolf23, and Markus Reichstein2,3,4 1Institute for Atmospheric and Climate Science, ETH Zurich, Universitätstr. 16, 8092 Zurich, Switzerland
2Max Planck Institute for Biogeochemistry, Hans - Knöll - Str. 10, 07745 Jena, Germany
3German Centre for Integrative Biodiversity Research (iDiv), Deutscher Platz 5e, 04103 Leipzig, Germany
4Michael Stifel Center Jena for Data - Driven and Simulation Science, 07743 Jena, Germany
5Wageningen University & Research, Laboratory of Geo - Information Science and Remote Sensing, Droevendaalsesteeg 3, 6 708 PB Wageningen, the Netherlands
6Institute on Ecosystems and Department of Ecology, Montana State University, Bozeman, MT 59717, USA
7CENSE, Departamento de Ciências e Engenharia do Ambiente, Faculdade de Ciências e Tecnologia, Universidade NOVA de Lisboa, Caparica, Portugal
8Laboratoire des Sciences du Climat et de l’Environnement, CEA - CNRS - UVSQ, F - 91191, Gif sur Yvette, France
9Institute of Biogeochemistry and Pollutant Dynamics, ETH Zurich, Zurich, Switzerland
10Institute for Geology , CEN - Center for Earth System Research and Sustainability, University of Hamburg, Germany 55, D - 20146 Hamburg, Germany
11Department of Environmental Geochemical Cycle Research, Agency for Marine - Earth Science and Technology, Yokohama, Japan
12Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan
13Max Planck Institute for Meteorology, Bundesstr. 53, Hamburg, Germany
14Dept. Geoscience, Environment & Society (DGES), CP160/02, Université Libre de Bruxelles, 1050 Bruxelles, Belgium
15College of Engineering, Mathematics and Physical Sciences, University of Exeter, EX4 4QE Exeter, Devon, UK
16Department for Innovation in Biological, Agro - food and Forest systems (DIBAF), University of Tuscia, Viterbo, 01100, Italy
17NASA Goddard Space Flight Center, Biospheric Sciences Laboratory, Greenbelt, MD 20771, USA
18Institute on the Environment, University of Minnesota Twin - Cities, USA
19Woods Hole Research Center, Falmouth MA 02540, USA
20Department of Geographical Sciences, University of Maryland, College Park, MD, USA
21CMCC, Via A. Imperatore, 16, 73100, Lecce, Italy
22Faculty of Earth and Life Sciences, Vrije Universiteit Amsterdam, the Netherlands
23Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD, USA
Abstract. 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 vertical oceanic, inland freshwaters and terrestrial carbon dioxide (CO2) exchange. Here we adopt a data-driven approach to synthesize a wide range of observation-based spatially explicit surface-atmosphere CO2 fluxes from 2001 and 2010, to identify the state of today’s observational opportunities and data limitation. The considered fluxes include vertical net exchange of open oceans, continental shelves, estuaries, rivers, and lakes, as well as CO2 fluxes related to gross primary productivity, terrestrial ecosystem respiration, fire emissions, loss of tropical aboveground C, harvested wood and crops, as well as fossil fuel and cement emissions. Spatially explicit CO2 fluxes are obtained through geostatistical and/or remote sensing-based upscaling; minimizing biophysical or biogeochemical assumptions encoded in process-based models. We estimate a global bottom-up net C exchange (NCE) between the surface (land, ocean, and coastal areas) and the atmosphere. Uncertainties for NCE and its components are derived using resampling. In most continental regions our NCE estimates agree well with independent estimates from other sources. This holds for Europe (mean ±1 SD: 0.80 ± 0.16 PgC/yr, positive numbers are sources to the atmosphere), Russia (−0.02 ± 0.49 PgC/yr), East Asia (1.76 ± 0.38 PgC/yr), South Asia (0.25 ± 0.16 PgC/yr), and Australia (0.22 ± 0.47 PgC/yr). Our NCE estimates also suggest large C sink in tropical areas. The global NCE estimate is −6.07 ± 3.38 PgC/yr. This global bottom-up value is the opposite direction of what is expected from the atmospheric growth rate of CO2, and would require an offsetting surface C source of 4.27±0.10 PgC/yr. This mismatch highlights large knowledge and observational gaps in tropical areas, particularly in South America, Africa, and Southeast Asia, but also in North America. Our uncertainty assessment provides the basis for designing new observation campaigns. In particular, we lack seasonal monitoring of shelf, estuary and inland water-atmosphere C exchange. Also, extensive pCO2 measurements are missing in the Southern Ocean. Most importantly, tropical land C fluxes suffer from a lack of in-situ observations. The consistent derivation of data uncertainties could serve as prior knowledge in multi-criteria optimization such as the Carbon Cycle Data Assimilation System (CCDAS) without overstating data credibility. Furthermore, the spatially explicit flux estimates may be used as a starting point to assess the validity of countries’ claims of reducing net C emissions in climate change negotiations.

Citation: Zscheischler, J., Mahecha, M. D., Avitabile, V., Calle, L., Carvalhais, N., Ciais, P., Gans, F., Gruber, N., Hartmann, J., Herold, M., Ichii, K., Jung, M., Landschützer, P., Laruelle, G. G., Lauerwald, R., Papale, D., Peylin, P., Poulter, B., Ray, D., Regnier, P., Rödenbeck, C., Roman-Cuesta, R. M., Schwalm, C., Tramontana, G., Tyukavina, A. T., Valentini, R., van der Werf, G., West, T. O., Wolf, J. E., and Reichstein, M.: An empirical spatiotemporal description of the global surface-atmosphere carbon fluxes: opportunities and data limitations, Biogeosciences Discuss.,, in review, 2016.
Jakob Zscheischler et al.

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M. D. Mahecha, J. Zscheischler, F. Gans, and M. Reichstein
Jakob Zscheischler et al.


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Publications Copernicus
Short summary
Here we synthesize all available observational data on carbon exchanges between the Earth surface and the atmosphere. For the first time, we combine observational products of terrestrial and aquatic surfaces. Our primary goal is not providing the best global CO2 flux inventory, but to identify today’s key uncertainties and observational shortcomings that would need to be addressed in future measurement campaigns or expansions of in-situ observatories.
Here we synthesize all available observational data on carbon exchanges between the Earth...