Abstract. Accurate assessments of anthropogenic carbon dioxide (CO 2 ) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the climate policy process, and project future climate change. Present-day analysis requires the combination of a range of data, algorithms, statistics and model estimates and their interpretation by a broad scientific community. Here we describe datasets and a methodology developed by the global carbon cycle science community to quantify all major components of the global carbon budget, including their uncertainties. We discuss changes compared to previous estimates, consistency within and among components, and methodology and data limitations. CO 2 emissions from fossil fuel combustion and cement production (E FF ) are based on energy statistics, while emissions from LandUse Change (E LUC ), including deforestation, are based on combined evidence from land cover change data, fire activity in regions undergoing deforestation, and models. The global atmospheric CO 2 concentration is measured directly and its rate of growth (G ATM ) is computed from the concentration. The mean ocean CO 2 sink (S OCEAN ) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models.

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the climate policy process, and project future climate change. Present-day analysis requires the combination of a range of data, algorithms, statistics and model estimates and their interpretation by a broad scientific community. Here we describe datasets and a methodology developed by the global carbon cycle science community to quantify all major components of the global carbon budget, including their uncertainties. We discuss changes compared to previous estimates, consistency within and among components, and methodology and data limitations. Based on energy statistics, we estimate that the global emissions of CO2 from fossil fuel combustion and cement production were 9.5 ± 0.5 PgC yr−1 in 2011, 3.0 percent above 2010 levels. We project these emissions will increase by 2.6% (1.9–3.5%) in 2012 based on projections of Gross World Product and recent changes in the carbon intensity of the economy. Global net CO2 emissions from Land-Use Change, including deforestation, are more difficult to update annually because of data availability, but combined evidence from land cover change data, fire activity in regions undergoing deforestation and models suggests those net emissions were 0.9 ± 0.5 PgC yr−1 in 2011. The global atmospheric CO2 concentration is measured directly and reached 391.38 ± 0.13 ppm at the end of year 2011, increasing 1.70 ± 0.09 ppm yr−1 or 3.6 ± 0.2 PgC yr−1 in 2011. Estimates from four ocean models suggest that the ocean CO2 sink was 2.6 ± 0.5 PgC yr−1 in 2011, implying a global residual terrestrial CO2 sink of 4.1 ± 0.9 PgC yr−1. All uncertainties are reported as ±1 sigma (68% confidence assuming Gaussian error distributions that the real value lies within the given interval), reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. This paper is intended to provide a baseline to keep track of annual carbon budgets in the future. All carbon data presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_V2012).

Abstract. Global ocean biogeochemistry models currently employed in climate change projections use highly simplified representations of pelagic food webs. These food webs do not necessarily include critical pathways by which ecosystems interact with ocean biogeochemistry and climate. Here we present a global biogeochemical model which incorporates ecosystem dynamics based on the representation of ten plankton functional types (PFTs): six types of phytoplankton, three types of zooplankton, and heterotrophic procaryotes. We improved the representation of zooplankton dynamics in our model through (a) the explicit inclusion of large, slow-growing macrozooplankton (e.g. krill), and (b) the introduction of trophic cascades among the three zooplankton types. We use the model to quantitatively assess the relative roles of iron vs. grazing in determining phytoplankton biomass in the Southern Ocean high-nutrient low-chlorophyll (HNLC) region during summer. When model simulations do not include macrozooplankton grazing explicitly, they systematically overestimate Southern Ocean chlorophyll biomass during the summer, even when there is no iron deposition from dust. When model simulations include a slow-growing macrozooplankton and trophic cascades among three zooplankton types, the high-chlorophyll summer bias in the Southern Ocean HNLC region largely disappears. Our model results suggest that the observed low phytoplankton biomass in the Southern Ocean during summer is primarily explained by the dynamics of the Southern Ocean zooplankton community, despite iron limitation of phytoplankton community growth rates. This result has implications for the representation of global biogeochemical cycles in models as zooplankton faecal pellets sink rapidly and partly control the carbon export to the intermediate and deep ocean.