Abstract. Accurate assessment of anthropogenic carbon dioxide (CO 2 ) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere -the "global carbon budget" -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 methodology to quantify the five major components of the global carbon budget and their uncertainties. CO 2 emissions from fossil fuels and industry (E FF ) are based on energy statistics and cement production data, respectively, while emissions from land-use change (E LUC ), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO 2 concentration is measured directly and its rate of growth (G ATM ) is computed from the annual changes in concentration. The ocean CO 2 sink (S OCEAN ) and terrestrial CO 2 sink (S LAND ) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (B IM ), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ . For the last decade available (2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016), E FF was 9.4 ± 0.5 GtC yr −1 , E LUC 1.3 ± 0.7 GtC yr −1 , G ATM 4.7 ± 0.1 GtC yr −1 , S OCEAN 2.4 ± 0.5 GtC yr −1 , and S LAND 3.0 ± 0.8 GtC yr −1 , with a budget imbalance B IM of 0.6 GtC yr −1 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in E FF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr −1 . Also for 2016, E LUC was 1.3 ± 0.7 GtC yr −1 , G ATM was 6.1 ± 0.2 GtC yr −1 , S OCEAN was 2.6 ± 0.5 GtC yr −1 , and S LAND was 2.7 ± 1.0 GtC yr −1 , with a small B IM of −0.3 GtC. G ATM continued to be higher in 2016 compared to the past decade (2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016), reflecting in part the high fossil emissions and the small S LAND consistent with El Niño conditions. The global atmospheric CO 2 concentration reached 402.8 ± 0.1 ppm averaged over 2016. For 2017, preliminary data for the first 6-9 months indicate a renewed growth in E FF of +2.0 % (range of 0.8 to 3.0 %) based on national emissions projections for China, USA, and India, and projections of gross domestic product (GDP) corrected for recent changes in the carbon intensity of the economy for the rest of the world. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Quéré et al

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the "global carbon budget" – 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 methodology to quantify the five major components of the global carbon budget and their uncertainties. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of our imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2007–2016), EFF was 9.4 ± 0.5 GtC yr−1, ELUC 1.3 ± 0.7 GtC yr−1, GATM 4.7 ± 0.1 GtC yr−1, SOCEAN 2.4 ± 0.5 GtC yr−1, and SLAND 3.0 ± 0.8 GtC yr−1, with a budget imbalance BIM of 0.6 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1. Also for 2016, ELUC was 1.3 ± 0.7 GtC yr−1, GATM was 6.1 ± 0.2 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1 and SLAND was 2.7 ± 1.0 GtC yr−1, with a small BIM of −0.3 GtC. GATM continued to be higher in 2016 compared to the past decade (2007–2016), reflecting in part the higher fossil emissions and smaller SLAND for that year consistent with El Niño conditions. The global atmospheric CO2 concentration reached 402.8 ± 0.1 ppm averaged over 2016. For 2017, preliminary data indicate a renewed growth in EFF of +2.0 % (range of 0.8 % to 3.0 %) based on national emissions projections for China, USA, and India, and projections of Gross Domestic Product corrected for recent changes in the carbon intensity of the economy for the rest of the world. For 2017, initial data indicate an increase in atmospheric CO2 concentration of around 5.3 GtC (2.5 ppm), attributed to a combination of increasing emissions and receding El Niño conditions. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set

Abstract. Accurate assessment 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 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 2 emissions from fossil Earth Syst. Sci. Data, 7, 47-85, 2015 www.earth-syst-sci-data.net/7/47/2015/ C. Le Quéré et al.: Global carbon budget 2014 49 fuel combustion and cement production (E FF ) are based on energy statistics and cement production data, respectively, while emissions from land-use change (E LUC ), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO 2 concentration is measured directly and its rate of growth (G ATM ) is computed from the annual changes in 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. The variability in S OCEAN is evaluated with data products based on surveys of ocean CO 2 measurements. The global residual terrestrial CO 2 sink (S LAND ) 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 2 , and land-coverchange (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 ±1σ , reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013), E FF was 8.9 ± 0.4 GtC yr −1 , E LUC 0.9 ± 0.5 GtC yr −1 , G ATM 4.3 ± 0.1 GtC yr −1 , S OCEAN 2.6 ± 0.5 GtC yr −1 , and S LAND 2.9 ± 0.8 GtC yr −1 . For year 2013 alone, E FF grew to 9.9 ± 0.5 GtC yr −1 , 2.3 % above 2012, continuing the growth trend in these emissions, E LUC was 0.9 ± 0.5 GtC yr −1 , G ATM was 5.4 ± 0.2 GtC yr −1 , S OCEAN was 2.9 ± 0.5 GtC yr −1 , and S LAND was 2.5 ± 0.9 GtC yr −1 . G ATM was high in 2013, reflecting a steady increase in E FF and smaller and opposite changes between S OCEAN and S LAND compared to the past decade (2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013). The global atmospheric CO 2 concentration reached 395.31 ± 0.10 ppm averaged over 2013. We estimate that E FF will increase by 2.5 % (1.3-3.5 %) to 10.1 ± 0.6 GtC in 2...

A new feature is the data set quality control (QC) flag of E for data from alternative sensors and platforms. The accuracy of surface water f CO 2 has been defined for all data set QC flags. Automated range checking has been carried out for all data sets during their upload into SOCAT. The upgrade of the interactive Data Set Viewer (previously known as the Cruise Data Viewer) allows better interrogation of the SOCAT data collection and rapid creation of high-quality figures for scientific presentations. Automated data upload has been launched for version 4 and will enable more frequent SOCAT releases in the future. Highprofile scientific applications of SOCAT include quantification of the ocean sink for atmospheric carbon dioxide and its long-term variation, detection of ocean acidification, as well as evaluation of coupled-climate and ocean-only biogeochemical models. Users of SOCAT data products are urged to acknowledge the contribution of data providers, as stated in the SOCAT Fair Data Use Statement. This ESSD (Earth System Science Data) "living data" publication documents the methods and data sets used for the assembly of this new version of the SOCAT data collection and compares these with those used for earlier versions of the data collection Sabine et al., 2013;Bakker et al., 2014). Individual data set files, included in the synthesis product, can be downloaded here: doi:10.1594/PANGAEA.849770. The gridded products are available here:

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[1] In order to determine the interannual and decadal changes in the air-sea carbon fluxes of the equatorial Pacific, we developed seasonal and interannual relationships between the fugacity of CO 2 (fCO 2 ) and sea surface temperature (SST) from shipboard data that were applied to high-resolution temperature fields deduced from satellite data to obtain high-resolution large-scale estimates of the regional fluxes. The data were gathered on board research ships from November 1981 through June 2004 between 95°W and 165°E. The distribution of fCO 2sw during five El Niño periods and four La Niña periods were documented. Observations made during the warm boreal winter-spring season and during the cooler boreal summer-fall season of each year enabled us to examine the interannual and seasonal variability of the fCO 2sw -SST relationships. A linear fit through all of the data sets yields an inverse correlation between SST and fCO 2sw , with both interannual and seasonal differences in slope. On average, the surface water fCO 2 in the equatorial region has been increasing at a rate similar to the atmospheric CO 2 increase. In addition, there appears to be a slight increase ($27%) in the outgassing flux of CO 2 after the 1997-1998 Pacific Decadal Oscillation (PDO) regime shift. Most of this flux increase is due to increase in wind speeds after the spring of 1998, although increases in fCO 2sw after 1998 are also important. These increases are coincident with the recent rebound of the shallow water meridional overturning circulation in the tropical and subtropical Pacific after the regime shift.

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Abstract.A well-documented, publicly available, global data set of surface ocean carbon dioxide (CO 2 ) parameters has been called for by international groups for nearly two decades. The Surface Ocean CO 2 Atlas (SOCAT) project was initiated by the international marine carbon science community in 2007 with the aim of providing a comprehensive, publicly available, regularly updated, global data set of marine surface CO 2 , which had been subject to quality control (QC). Many additional CO 2 data, not yet made public via the Carbon Dioxide Information Analysis Center (CDIAC), were retrieved from data originators, public websites and other data centres. All data were put in a uniform format following a strict protocol. Quality control was carried out according to clearly defined criteria. Regional specialists performed the quality control, using state-of-the-art web-based tools, specially developed for accomplishing this global team effort. SOCAT version 1.5 was made public in September 2011 and holds 6.3 million quality controlled surface CO 2 data points from the global oceans and coastal seas, spanning four decades . Three types of data products are available: individual cruise files, a merged complete data set and gridded products. With the rapid expansion of marine CO 2 data collection and the importance of quantifying net global oceanic CO 2 uptake and its changes, sustained data synthesis and data access are priorities. Data coverage MotivationThe net absorption of CO 2 by the oceans, caused by rising atmospheric CO 2 concentrations since the industrial revolution, has been responsible for removing CO 2 equivalent to approximately 50 % of the fossil fuel and cement manufacturing emissions or about 30 % of the total anthropogenic emissions, including land use change (Sabine et al., 2004). Because of the availability of the carbonate ion, an important species of the dissolved inorganic carbon pool, and carbonate sediments, the oceans have a tremendous CO 2 uptake capacity and will, on timescales of ten to hundred thousand years, absorb all but a small fraction of the fossil CO 2 that has been and will be emitted (Archer et al., 1997). Meanwhile the changes in ocean CO 2 uptake, relying on factors such as ocean circulation and biology, will be among the decisive factors for the evolution of future atmospheric CO 2 concentrations and climate development (e.g., Friedlingstein et al., 2006;Riebesell et al., 2009). Presently there are two types of globally coordinated efforts that seek to resolve the dynamics of ocean CO 2 uptake through observations: repeat hydrography and surface ocean CO 2 observations (Gruber et al., 2010;Sabine et al., 2010). While repeat hydrography aims to assess variations in the ocean inventory of CO 2 on decadal timescales, surface ocean observations may resolve variations on seasonal to interannual timescales due to the higher sampling frequency. This high sampling frequency has been made possible by the advent of autonomous instruments and sensors for the nearcontinuous determination o...