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Reviews and syntheses: An empirical spatiotemporal description of the global surface–atmosphere carbon fluxes: opportunities and data limitations

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/persons/resource/persons76340

Zscheischler,  Jakob
Empirical Inference of the Earth System, Dr. Miguel D. Mahecha, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

/persons/resource/persons62472

Mahecha,  Miguel D.
Empirical Inference of the Earth System, Dr. Miguel D. Mahecha, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

/persons/resource/persons62352

Carvalhais,  Nuno
Model-Data Integration, Dr. Nuno Carvalhais, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

/persons/resource/persons62378

Gans,  Fabian
Empirical Inference of the Earth System, Dr. Miguel D. Mahecha, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

/persons/resource/persons62425

Jung,  Martin
Global Diagnostic Modelling, Dr. Martin Jung, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

/persons/resource/persons62529

Rödenbeck,  Christian
Inverse Data-driven Estimation, Dr. C. Rödenbeck, Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

/persons/resource/persons62524

Reichstein,  Markus
Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Citation

Zscheischler, J., Mahecha, M. D., Avitabile, V., Calle, L., Carvalhais, N., Ciais, P., et al. (2017). Reviews and syntheses: An empirical spatiotemporal description of the global surface–atmosphere carbon fluxes: opportunities and data limitations. Biogeosciences, 14(15), 3685-3703. doi:10.5194/bg-14-3685-2017.


Cite as: https://hdl.handle.net/11858/00-001M-0000-002B-B08C-4
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.