Conventional calculations of the global carbon budget infer the land sink as a residual between emissions, atmospheric accumulation, and the ocean sink. Thus, the land sink accumulates the errors from the other flux terms and bears the largest uncertainty. Here, we present a Bayesian fusion approach that combines multiple observations in different carbon reservoirs to optimize the land (B) and ocean (O) carbon sinks, land use change emissions (L), and indirectly fossil fuel emissions (F) from 1980 to 2014. Compared with the conventional approach, Bayesian optimization decreases the uncertainties in B by 41\% and in O by 46\%. The L uncertainty decreases by 47\%, whereas F uncertainty is marginally improved through the knowledge of natural fluxes. Both ocean and net land uptake (B + L) rates have positive trends of 29 {\textpm} 8 and 37 {\textpm} 17 Tg C{\textperiodcentered}y-2 since 1980, respectively. Our Bayesian fusion of multiple observations reduces uncertainties, thereby allowing us to isolate important variability in global carbon cycle processes.

}, keywords = {Bayesian fusion, Carbon cycle, Decadal variations, Global carbon budget}, doi = {10.1073/pnas.1603956113}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84995653359\&doi=10.1073\%2fpnas.1603956113\&partnerID=40\&md5=8a1035983735980d6d44ed4df45b5233}, author = {Li, W. and Ciais, P and Wang, Y. and Peng, S. and Broquet, G. and Ballantyne, A. P. and Canadell, J and Cooper, L. and Friedlingstein, P and Le Qu{\'e}r{\'e}, C and Myneni, R. and Peters, GP and Piao, S. L. and Pongratz, J.} } @article {1545, title = {Global carbon budget 2014}, journal = {Earth System Science Data}, volume = {7}, year = {2015}, pages = {47-85}, type = {Article}, chapter = {47}, abstract = {Accurate assessment of anthropogenic carbon dioxide (CO\<inf\>2\</inf\>) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates, consistency within and among components, alongside methodology and data limitations. CO\<inf\>2\</inf\> emissions from fossil fuel combustion and cement production (E\<inf\>FF\</inf\>) are based on energy statistics and cement production data, respectively, while emissions from land-use change (E\<inf\>LUC\</inf\>), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO\<inf\>2\</inf\> concentration is measured directly and its rate of growth (G\<inf\>ATM\</inf\>) is computed from the annual changes in concentration. The mean ocean CO\<inf\>2\</inf\> sink (S\<inf\>OCEAN\</inf\>) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in S\<inf\>OCEAN\</inf\> is evaluated with data products based on surveys of ocean CO\<inf\>2\</inf\> measurements. The global residual terrestrial CO\<inf\>2\</inf\> sink (S\<inf\>LAND\</inf\>) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO\<inf\>2\</inf\>, and land-cover-change (some including nitrogen-carbon interactions). We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as {\textpm}1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2004-2013) E\<inf\>FF\</inf\> was 8.9 {\textpm} 0.4 GtC yr-1, E\<inf\>LUC\</inf\> 0.9 {\textpm} 0.5 GtC yr-1, G\<inf\>ATM\</inf\> 4.3 {\textpm} 0.1 GtC yr-1, S\<inf\>OCEAN\</inf\> 2.6 {\textpm} 0.5 GtC yr-1, and S\<inf\>LAND\</inf\> 2.9 {\textpm} 0.8 GtC yr-1. For year 2013 alone, E\<inf\>FF\</inf\> grew to 9.9 {\textpm} 0.5 GtC yr-1, 2.3\% above 2012, continuing the growth trend in these emissions, E\<inf\>LUC\</inf\> was 0.9 {\textpm} 0.5 GtC yr-1, G\<inf\>ATM\</inf\> was 5.4 {\textpm} 0.2 GtC yr-1, S\<inf\>OCEAN\</inf\> was 2.9 {\textpm} 0.5 GtC yr-1, and S\<inf\>LAND\</inf\> was 2.5 {\textpm} 0.9 GtC yr-1. G\<inf\>ATM\</inf\> was high in 2013, reflecting a steady increase in E\<inf\>FF\</inf\> and smaller and opposite changes between S\<inf\>OCEAN\</inf\> and S\<inf\>LAND\</inf\> compared to the past decade (2004-2013). The global atmospheric CO\<inf\>2\</inf\> concentration reached 395.31 {\textpm} 0.10 ppm averaged over 2013. We estimate that E\<inf\>FF\</inf\> will increase by 2.5\% (1.3-3.5\%) to 10.1 {\textpm} 0.6 GtC in 2014 (37.0 {\textpm} 2.2 GtCO\<inf\>2\</inf\> yr-1), 65\% above emissions in 1990, based on projections of world gross domestic product and recent changes in the carbon intensity of the global economy. From this projection of E\<inf\>FF\</inf\> and assumed constant E\<inf\>LUC\</inf\> for 2014, cumulative emissions of CO\<inf\>2\</inf\> will reach about 545 {\textpm} 55 GtC (2000 {\textpm} 200 GtCO\<inf\>2\</inf\>) for 1870-2014, about 75\% from E\<inf\>FF\</inf\> and 25\% from E\<inf\>LUC\</inf\>. This paper documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this living data set (Le Qu{\'e}r{\'e} et al., 2013, 2014). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP-2014). {\textcopyright} Author(s) 2015.

}, doi = {10.5194/essd-7-47-2015}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84929324791\&doi=10.5194\%2fessd-7-47-2015\&partnerID=40\&md5=ec90c683cc30001a3138a74b32cde55d}, author = {Le Qu{\'e}r{\'e}, C and Moriarty, R. and Andrew, R. M. and Peters, GP and Ciais, P and Friedlingstein, P and Jones, SD and Sitch, S. and Tans, P. and Arneth, A. and Boden, TA and Bopp, L and Bozec, Y. and Canadell, J and Chini, L. P. and Chevallier, F and Cosca, CE and Harris, I. and Hoppema, M. and Houghton, RA and House, J. I. and Jain, A. K. and Johansson, T and Kato, E. and Keeling, RF and Kitidis, V. and Klein Goldewijk, K. and Koven, C. and Landa, C. S. and Landschutzer, P and Lenton, A. and Lima, I and Marland, G and Mathis, J. T. and Metzl, N and Nojiri, Y and Olsen, A. and Ono, T. and Peng, S. and Peters, W. and Pfeil, B. and Poulter, B. and Raupach, M. R. and Regnier, P. and R{\"o}denbeck, C and Saito, S. and Salisbury, J. E. and Schuster, U and Schwinger, J. and Seferian, R. and Segschneider, J. and Steinhoff, T. and Stocker, B. D. and Sutton, A. J. and Takahashi, T and Tilbrook, B. and Van der Werf, GR and Viovy, N. and Wang, Y. P. and Wanninkhof, R. and Wiltshire, A. and Zeng, N.} }