No abstract

No abstract

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

Comparison of eight iron experiments shows that maximum Chl a, the maximum DIC removal, and the overall DIC/Fe efficiency all scale inversely with depth of the wind mixed layer (WML) defining the light environment. Moreover, lateral patch dilution, sea surface irradiance, temperature, and grazing play additional roles. The Southern Ocean experiments were most influenced by very deep WMLs. In contrast, light conditions were most favorable during SEEDS and SERIES as well as during IronEx‐2. The two extreme experiments, EisenEx and SEEDS, can be linked via EisenEx bottle incubations with shallower simulated WML depth. Large diatoms always benefit the most from Fe addition, where a remarkably small group of thriving diatom species is dominated by universal response of Pseudo‐nitzschia spp. Significant response of these moderate (10–30 μm), medium (30–60 μm), and large (>60 μm) diatoms is consistent with growth physiology determined for single species in natural seawater. The minimum level of “dissolved” Fe (filtrate < 0.2 μm) maintained during an experiment determines the dominant diatom size class. However, this is further complicated by continuous transfer of original truly dissolved reduced Fe(II) into the colloidal pool, which may constitute some 75% of the “dissolved” pool. Depth integration of carbon inventory changes partly compensates the adverse effects of a deep WML due to its greater integration depths, decreasing the differences in responses between the eight experiments. About half of depth‐integrated overall primary productivity is reflected in a decrease of DIC. The overall C/Fe efficiency of DIC uptake is DIC/Fe ∼ 5600 for all eight experiments. The increase of particulate organic carbon is about a quarter of the primary production, suggesting food web losses for the other three quarters. Replenishment of DIC by air/sea exchange tends to be a minor few percent of primary CO2 fixation but will continue well after observations have stopped. Export of carbon into deeper waters is difficult to assess and is until now firmly proven and quite modest in only two experiments.

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 as well as consistency within and among components, alongside methodology and data limitations. CO 2 emissions from fossil fuels and industry (E FF ) are based on energy statistics and cement production data, 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-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 ±1σ , reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014), E FF was 9.0 ± 0.5 GtC yr −1 , E LUC was 0.9 ± 0.5 GtC yr −1 , G ATM was 4.4 ± 0.1 GtC yr −1 , S OCEAN was 2.6 ± 0.5 GtC yr −1 , and S LAND was 3.0 ± 0.8 GtC yr −1 . For the year 2014 alone, E FF grew to 9.8 ± 0.5 GtC yr −1 , 0.6 % above 2013, continuing the growth trend in these emissions, albeit at a slower rate compared to the average growth of 2.2 % yr −1 that took place during 2005-2014. Also, for 2014, E LUC was 1.1 ± 0.5 GtC yr −1 , G ATM was 3.9 ± 0.2 GtC yr −1 , S OCEAN was 2.9 ± 0.5 GtC yr −1 , and S LAND was 4.1 ± 0.9 GtC yr −1 . G ATM was lower in 2014 compared to the past decade (2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014), reflecting a larger S LAND for that year. The global atmospheric CO 2 concentration reached 397.15 ± 0.10 ppm averaged over 2014. For 2015, preliminary data indicate that the growth in E FF will be near or slightly below zero, with a projection of −0.6 [range of −1.6 to +0....

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: