Description: Author Posting. © American Meteorological Society, 2012. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 93 (2012): 1547–1566, doi:10.1175/BAMS-D-11-00201.1.

Description: The Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission was recommended by the National Research Council's (NRC's) Earth Science Decadal Survey to measure tropospheric trace gases and aerosols and coastal ocean phytoplankton, water quality, and biogeochemistry from geostationary orbit, providing continuous observations within the field of view. To fulfill the mandate and address the challenge put forth by the NRC, two GEO-CAPE Science Working Groups (SWGs), representing the atmospheric composition and ocean color disciplines, have developed realistic science objectives using input drawn from several community workshops. The GEO-CAPE mission will take advantage of this revolutionary advance in temporal frequency for both of these disciplines. Multiple observations per day are required to explore the physical, chemical, and dynamical processes that determine tropospheric composition and air quality over spatial scales ranging from urban to continental, and over temporal scales ranging from diurnal to seasonal. Likewise, high-frequency satellite observations are critical to studying and quantifying biological, chemical, and physical processes within the coastal ocean. These observations are to be achieved from a vantage point near 95°–100°W, providing a complete view of North America as well as the adjacent oceans. The SWGs have also endorsed the concept of phased implementation using commercial satellites to reduce mission risk and cost. GEO-CAPE will join the global constellation of geostationary atmospheric chemistry and coastal ocean color sensors planned to be in orbit in the 2020 time frame.

Description: Funding for GEO-CAPE definition activities is provided by the Earth Science Division of the National Aeronautics and Space Administration.

Description: 2013-04-01

Description: © The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Geophysical Research: Oceans 118 (2013): 5439–5460, doi:10.1002/jgrc.20369.

Description: Underway and in situ observations of surface ocean pCO2, combined with satellite data, were used to develop pCO2 regional algorithms to analyze the seasonal and interannual variability of surface ocean pCO2 and sea-air CO2 flux for five physically and biologically distinct regions of the eastern North American continental shelf: the South Atlantic Bight (SAB), the Mid-Atlantic Bight (MAB), the Gulf of Maine (GoM), Nantucket Shoals and Georges Bank (NS+GB), and the Scotian Shelf (SS). Temperature and dissolved inorganic carbon variability are the most influential factors driving the seasonality of pCO2. Estimates of the sea-air CO2 flux were derived from the available pCO2 data, as well as from the pCO2 reconstructed by the algorithm. Two different gas exchange parameterizations were used. The SS, GB+NS, MAB, and SAB regions are net sinks of atmospheric CO2 while the GoM is a weak source. The estimates vary depending on the use of surface ocean pCO2 from the data or algorithm, as well as with the use of the two different gas exchange parameterizations. Most of the regional estimates are in general agreement with previous studies when the range of uncertainty and interannual variability are taken into account. According to the algorithm, the average annual uptake of atmospheric CO2 by eastern North American continental shelf waters is found to be between −3.4 and −5.4 Tg C yr−1 (areal average of −0.7 to −1.0 mol CO2 m−2 yr−1) over the period 2003–2010.

Description: We wish to acknowledge the NASA Ocean Biology and Biogeochemistry program for providing funds for this project.

Description: Author Posting. © The Oceanography Society, 2015. This article is posted here by permission of The Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 28, no. 2 (2015): 48-61, doi:10.5670/oceanog.2015.31.

Description: Oceanic and coastal waters are acidifying due to processes dominated in the open ocean by increasing atmospheric CO2 and dominated in estuaries and some coastal waters by nutrient-fueled respiration. The patterns and severity of acidification, as well as its effects, are modified by the host of stressors related to human activities that also influence these habitats. Temperature, deoxygenation, and changes in food webs are particularly important co-stressors because they are pervasive, and both their causes and effects are often mechanistically linked to acidification. Development of a theoretical underpinning to multiple stressor research that considers physiological, ecological, and evolutionary perspectives is needed because testing all combinations of stressors and stressor intensities experimentally is impossible. Nevertheless, use of a wide variety of research approaches is a logical and promising strategy for improving understanding of acidification and its effects. Future research that focuses on spatial and temporal patterns of stressor interactions and on identifying mechanisms by which multiple stressors affect individuals, populations, and ecosystems is critical. It is also necessary to incorporate consideration of multiple stressors into management, mitigation, and adaptation to acidification and to increase public and policy recognition of the importance of addressing acidification in the context of the suite of other stressors with which it potentially interacts.

Description: Funding for research on acidification and multiple stressors was provided by NOAACSCOR NA10NOS4780138 to DLB, NASA NNX14AL8 to JS, NSF OCE-1219948 to JMB, NSF OCE-927445 and OCE-1041062 to LAL, NSF EF-1041070 to W-JC, a Linnaeus grant from the Swedish Research Councils VR and Formas to SD, NSF EF-0424599 to SCD, NSF OCE-1041038 to UP, NSF EF-1316113 to BAS, NSF ANT-1142122 to AET, NSF OCE-1316040 to AMT, and the NOAA Ocean Acidification Program Office to BP, LMM, and WCL.

Description: Author Posting. © The Oceanography Society, 2015. This article is posted here by permission of The Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 28, no. 2 (2015): 182-197, doi:10.5670/oceanog.2015.41.

Description: New England coastal and adjacent Nova Scotia shelf waters have a reduced buffering capacity because of significant freshwater input, making the region’s waters potentially more vulnerable to coastal acidification. Nutrient loading and heavy precipitation events further acidify the region’s poorly buffered coastal waters. Despite the apparent vulnerability of these waters, and fisheries’ and mariculture’s significant dependence on calcifying species, the community lacks the ability to confidently predict how the region’s ecosystems will respond to continued ocean and coastal acidification. Here, we discuss ocean and coastal acidification processes specific to New England coastal and Nova Scotia shelf waters and review current understanding of the biological consequences most relevant to the region. We also identify key research and monitoring needs to be addressed and highlight existing capacities that should be leveraged to advance a regional understanding of ocean and coastal acidification.

Description: This project was supported in part by an appointment to the Internship/Research Participation Program at the Office of Water, US Environmental Protection Agency (EPA), administered by the Oak Ridge Institute for Science and Education through an interagency agreement between the US Department of Energy and the EPA. JS acknowledges support from NASA grant from NNX14AL84G NASA-CCS.

Description: © The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Biogeosciences 13 (2016): 5065-5083, doi:10.5194/bg-13-5065-2016.

Description: One of the major challenges to assessing the impact of ocean acidification on marine life is detecting and interpreting long-term change in the context of natural variability. This study addresses this need through a global synthesis of monthly pH and aragonite saturation state (Ωarag) climatologies for 12 open ocean, coastal, and coral reef locations using 3-hourly moored observations of surface seawater partial pressure of CO2 and pH collected together since as early as 2010. Mooring observations suggest open ocean subtropical and subarctic sites experience present-day surface pH and Ωarag conditions outside the bounds of preindustrial variability throughout most, if not all, of the year. In general, coastal mooring sites experience more natural variability and thus, more overlap with preindustrial conditions; however, present-day Ωarag conditions surpass biologically relevant thresholds associated with ocean acidification impacts on Mytilus californianus (Ωarag 〈 1.8) and Crassostrea gigas (Ωarag 〈 2.0) larvae in the California Current Ecosystem (CCE) and Mya arenaria larvae in the Gulf of Maine (Ωarag 〈 1.6). At the most variable mooring locations in coastal systems of the CCE, subseasonal conditions approached Ωarag =  1. Global and regional models and data syntheses of ship-based observations tended to underestimate seasonal variability compared to mooring observations. Efforts such as this to characterize all patterns of pH and Ωarag variability and change at key locations are fundamental to assessing present-day biological impacts of ocean acidification, further improving experimental design to interrogate organism response under real-world conditions, and improving predictive models and vulnerability assessments seeking to quantify the broader impacts of ocean acidification.

Description: The CO2 and ocean acidification observations were funded by NOAA’s Climate Observation Division (COD) in the Climate Program Office and NOAA’s Ocean Acidification Program. The maintenance of the Stratus and WHOTS Ocean Reference Stations were also supported by NOAA COD (NA09OAR4320129). Additional support for buoy equipment, maintenance, and/or ancillary measurements was provided by NOAA through the US Integrated Ocean Observing System office: for the La Parguera buoy under a Cooperative Agreement (NA11NOS0120035) with the Caribbean Coastal Ocean Observing System, for the Chá b˘a buoy under a Cooperative Agreement (NA11NOS0120036) with the Northwest Association of Networked Ocean Observing System, for the Gray’s Reef buoy under a Cooperative Agreement (NA11NOS0120033) with the Southeast Coastal Ocean Observing Regional Association, and for the Gulf of Main buoy under a Cooperative Agreement (NA11NOS0120034) with the Northeastern Regional Association of Coastal and Ocean Observing Systems.

Description: Author Posting. © American Geophysical Union, 2018. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Global Biogeochemical Cycles 32 (2018): 389-416, doi:10.1002/2017GB005790.

Description: Carbon cycling in the coastal zone affects global carbon budgets and is critical for understanding the urgent issues of hypoxia, acidification, and tidal wetland loss. However, there are no regional carbon budgets spanning the three main ecosystems in coastal waters: tidal wetlands, estuaries, and shelf waters. Here we construct such a budget for eastern North America using historical data, empirical models, remote sensing algorithms, and process‐based models. Considering the net fluxes of total carbon at the domain boundaries, 59 ± 12% (± 2 standard errors) of the carbon entering is from rivers and 41 ± 12% is from the atmosphere, while 80 ± 9% of the carbon leaving is exported to the open ocean and 20 ± 9% is buried. Net lateral carbon transfers between the three main ecosystem types are comparable to fluxes at the domain boundaries. Each ecosystem type contributes substantially to exchange with the atmosphere, with CO2 uptake split evenly between tidal wetlands and shelf waters, and estuarine CO2 outgassing offsetting half of the uptake. Similarly, burial is about equal in tidal wetlands and shelf waters, while estuaries play a smaller but still substantial role. The importance of tidal wetlands and estuaries in the overall budget is remarkable given that they, respectively, make up only 2.4 and 8.9% of the study domain area. This study shows that coastal carbon budgets should explicitly include tidal wetlands, estuaries, shelf waters, and the linkages between them; ignoring any of them may produce a biased picture of coastal carbon cycling.

Description: NASA Interdisciplinary Science program Grant Number: NNX14AF93G; NASA Carbon Cycle Science Program Grant Number: NNX14AM37G; NASA Ocean Biology and Biogeochemistry Program Grant Number: NNX11AD47G; National Science Foundation's Chemical Oceanography Program Grant Number: OCE‐1260574

Description: 2018-10-04

Description: Author Posting. © The Oceanography Society, 2016. This article is posted here by permission of The Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 29, no. 2 (2016): 222–231, doi:10.5670/oceanog.2016.54.

Description: The Bay of Bengal (BoB) is strongly density stratified due to large freshwater input from various rivers and heavy precipitation. This strong vertical stratification, along with physical processes, regulates the transport and vertical exchange of surface and subsurface water, concentrating nutrients and intensifying the oxygen minimum zone (OMZ). Here, we use basinwide measurements to describe the spatial distributions of nutrients, oxygen, and phytoplankton within the BoB during the 2013 northeast monsoon (November–December). By the time riverine water reaches the interior bay, it is depleted in the nutrients nitrate and phosphate, but not silicate. Layering of freshwater in the northern BoB depresses isopycnals, leading to a deepening of the nutricline and oxycline. Oxygen concentrations in the OMZ are lowest in the north (〈5 µM). Weak along-isopycnal nutrient gradients reflect along-isopycnal stirring between ventilated surface water and deep nutrient-replenished water. Picoplankton dominate the phytoplankton population in the north, presumably outcompeting larger phytoplankton species due to their low nutrient requirements. Micro- and nanoplankton numbers are enhanced in regions with deeper mixed layers and weaker stratification, where nutrient replenishment from subsurface waters is more feasible. These are also the regions where marine mammals were sighted. Physical processes and the temperature-salinity structure in the BoB directly influence the OMZ and the depth of the oxycline and nutricline, thereby affecting the phytoplankton and marine mammal communities.

Description: We would like to thank the Director, CSIR-National Institute of Oceanography, for support. CKS acknowledges CSIR/AcSIR for a research fellowship. MFB and KMS were supported by the US Office of Naval Research Marine Mammals and Biology Program.

Description: © The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Jiang, L.-Q., Pierrot, D., Wanninkhof, R., Feely, R. A., Tilbrook, B., Alin, S., Barbero, L., Byrne, R. H., Carter, B. R., Dickson, A. G., Gattuso, J.-P., Greeley, D., Hoppema, M., Humphreys, M. P., Karstensen, J., Lange, N., Lauvset, S. K., Lewis, E. R., Olsen, A., Pérez, F. F., Sabine, C., Sharp, J. D., Tanhua, T., Trull, T. W., Velo, A., Allegra, A. J., Barker, P., Burger, E., Cai, W-J., Chen, C-T. A., Cross, J., Garcia, H., Hernandez-Ayon J. M., Hu, X., Kozyr, A., Langdon, C., Lee., K, Salisbury, J., Wang, Z. A., & Xue, L. Best practice data standards for discrete chemical oceanographic observations. Frontiers in Marine Science, 8, (2022): 705638, https://doi.org/10.3389/fmars.2021.705638.

Description: Effective data management plays a key role in oceanographic research as cruise-based data, collected from different laboratories and expeditions, are commonly compiled to investigate regional to global oceanographic processes. Here we describe new and updated best practice data standards for discrete chemical oceanographic observations, specifically those dealing with column header abbreviations, quality control flags, missing value indicators, and standardized calculation of certain properties. These data standards have been developed with the goals of improving the current practices of the scientific community and promoting their international usage. These guidelines are intended to standardize data files for data sharing and submission into permanent archives. They will facilitate future quality control and synthesis efforts and lead to better data interpretation. In turn, this will promote research in ocean biogeochemistry, such as studies of carbon cycling and ocean acidification, on regional to global scales. These best practice standards are not mandatory. Agencies, institutes, universities, or research vessels can continue using different data standards if it is important for them to maintain historical consistency. However, it is hoped that they will be adopted as widely as possible to facilitate consistency and to achieve the goals stated above.

Description: Funding for L-QJ and AK was from NOAA Ocean Acidification Program (OAP, Project ID: 21047) and NOAA National Centers for Environmental Information (NCEI) through NOAA grant NA19NES4320002 [Cooperative Institute for Satellite Earth System Studies (CISESS)] at the University of Maryland/ESSIC. BT was in part supported by the Australia’s Integrated Marine Observing System (IMOS), enabled through the National Collaborative Research Infrastructure Strategy (NCRIS). AD was supported in part by the United States National Science Foundation. AV and FP were supported by BOCATS2 Project (PID2019-104279GB-C21/AEI/10.13039/501100011033) funded by the Spanish Research Agency and contributing to WATER:iOS CSIC interdisciplinary thematic platform. MH was partly funded by the European Union’s Horizon 2020 Research and Innovation Program under grant agreement N°821001 (SO-CHIC).

Description: © The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Earth System Science Data 7 (2015): 47-85, doi:10.5194/essd-7-47-2015.

Description: 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 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. CO2 emissions from fossil fuel combustion and cement production (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) 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, CO2, 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 (2004–2013), EFF was 8.9 ± 0.4 GtC yr−1, ELUC 0.9 ± 0.5 GtC yr−1, GATM 4.3 ± 0.1 GtC yr−1, SOCEAN 2.6 ± 0.5 GtC yr−1, and SLAND 2.9 ± 0.8 GtC yr−1. For year 2013 alone, EFF grew to 9.9 ± 0.5 GtC yr−1, 2.3% above 2012, continuing the growth trend in these emissions, ELUC was 0.9 ± 0.5 GtC yr−1, GATM was 5.4 ± 0.2 GtC yr−1, SOCEAN was 2.9 ± 0.5 GtC yr−1, and SLAND was 2.5 ± 0.9 GtC yr−1. GATM was high in 2013, reflecting a steady increase in EFF and smaller and opposite changes between SOCEAN and SLAND compared to the past decade (2004–2013). The global atmospheric CO2 concentration reached 395.31 ± 0.10 ppm averaged over 2013. We estimate that EFF will increase by 2.5% (1.3–3.5%) to 10.1 ± 0.6 GtC in 2014 (37.0 ± 2.2 GtCO2 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 EFF and assumed constant ELUC for 2014, cumulative emissions of CO2 will reach about 545 ± 55 GtC (2000 ± 200 GtCO2) for 1870–2014, about 75% from EFF and 25% from ELUC. 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 Quéré et al., 2013, 2014). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2014).

Description: NERC provided funding to C. Le Quéré, R. Moriarty, and the GCP though their International Opportunities Fund specifically to support this publication (NE/103002X/1), and to U. Schuster through UKOARP (NE/H017046/1). G. P. Peters and R. M. Andrews were supported by the Norwegian Research Council (236296). T. A. Boden was supported by US Department of Energy, Office of Science, Biological and Environmental Research (BER) programmes under US Department of Energy contract DEAC05- 00OR22725. Y. Bozec was supported by Region Bretagne, CG29, and INSU (LEFE/MERMEX) for CARBORHONE cruises. J. G. Canadell and M. R. Raupach were supported by the Australian Climate Change Science Programme. M. Hoppema received ICOSD funding through the German Federal Ministry of Education and Research (BMBF) to the AWI (01 LK 1224I). J. I. House was supported by a Leverhulme Early Career Fellowship. A. K. Jain was supported by the US National Science Foundation (NSF AGS 12-43071) the US Department of Energy, Office of Science, and BER programmes (DOE DE-SC0006706) and the NASA LCLUC programme (NASA NNX14AD94G). E. Kato was supported by the Environment Research and Technology Development Fund (S-10) of the Ministry of Environment of Japan. C. Koven was supported by the Director, Office of Science, Office of Biological and Environmental Research, of the US Department of Energy under contract no. DE-AC02-05CH11231 as part of their Regional and Global Climate Modeling Program. I. D. Lima was supported by the U.S. National Science Foundation (NSF AGS-1048827). N. Metzl was supported by Institut National des Sciences de l’Univers (INSU) and Institut Paul Emile Victor (IPEV) for OISO cruises. A. Olsen was supported by the Centre for Climate Dynamics at the Bjerknes Centre for Climate Research. J. E. Salisbury was supported by grants from NOAA/NASA. T. Steinhoff was supported by ICOS-D (BMBF FK 01LK1101C). B. D. Stocker was supported by the Swiss National Science Foundation and FP7 funding through project EMBRACE (282672). A. J. Sutton was supported by NOAA. T. Takahashi was supported by grants from NOAA and the Comer Education and Science Foundation. B. Tilbrook was supported by the Australian Department of the Environment and the Integrated Marine Observing System. A.Wiltshire was supported by the Joint UK DECC/Defra Met Office Hadley Centre Climate Programme (GA01101). P. Ciais,W. Peters, C. Le Quére, P. Regnier, and U. Schuster were supported by the EU FP7 through project GEOCarbon (283080). A. Arneth, P. Ciais, S. Sitch, and A. Wiltshire were supported by COMBINE (226520). V. Kitidis, M. Hoppema, N. Metzl, C. Le Quéré, U. Schuster, J. Schwiger, J. Segschneider, and T. Steinhoff were supported by the EU FP7 through project CARBOCHANGE (264879). A. Arnet, P. Friedlingstein, B. Poulter, and S. Sitch were supported by the EU FP7 through projects LUC4C (GA603542). P. Friedlingstein was also supported by EMBRACE (GA282672). F. Chevallier and G. R. van der Werf were supported by the EU FP7 through project MACC-II (283576).

Description: © The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Earth System Science Data 8 (2016): 605-649, doi:10.5194/essd-8-605-2016.

Description: 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 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 and consistency within and among components, alongside methodology and data limitations. 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 combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models. 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 (2006–2015), EFF was 9.3 ± 0.5 GtC yr−1, ELUC 1.0 ± 0.5 GtC yr−1, GATM 4.5 ± 0.1 GtC yr−1, SOCEAN 2.6 ± 0.5 GtC yr−1, and SLAND 3.1 ± 0.9 GtC yr−1. For year 2015 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1, showing a slowdown in growth of these emissions compared to the average growth of 1.8 % yr−1 that took place during 2006–2015. Also, for 2015, ELUC was 1.3 ± 0.5 GtC yr−1, GATM was 6.3 ± 0.2 GtC yr−1, SOCEAN was 3.0 ± 0.5 GtC yr−1, and SLAND was 1.9 ± 0.9 GtC yr−1. GATM was higher in 2015 compared to the past decade (2006–2015), reflecting a smaller SLAND for that year. The global atmospheric CO2 concentration reached 399.4 ± 0.1 ppm averaged over 2015. For 2016, preliminary data indicate the continuation of low growth in EFF with +0.2 % (range of −1.0 to +1.8 %) based on national emissions projections for China and USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. In spite of the low growth of EFF in 2016, the growth rate in atmospheric CO2 concentration is expected to be relatively high because of the persistence of the smaller residual terrestrial sink (SLAND) in response to El Niño conditions of 2015–2016. From this projection of EFF and assumed constant ELUC for 2016, cumulative emissions of CO2 will reach 565 ± 55 GtC (2075 ± 205 GtCO2) for 1870–2016, about 75 % from EFF and 25 % from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quéré et al., 2015b, a, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2016).

Description: Australia, Integrated Marine Observing System and Antarctic Climate and Ecosystems CRC BT; European Commission (EC) Copernicus Atmosphere Monitoring Service, European Centre for Medium-Range Weather Forecasts (ECMWF) FC; EC H2020 (AtlantOS; grant no. 633211) NL, AO; EC H2020 (CRESCENDO; grant no. 641816) CD, RS, OA, PF; EC H2020 European Research Council (ERC) (QUINCY; grant no. 647204). SZ; EC H2020 ERC Synergy grant (IMBALANCE-P; grant no. ERC-2013-SyG-610028) PC; France, BNP Paribas Foundation grant to support the Global Carbon Atlas PC; French Institut National des Sciences de l’Univers (INSU) and Institut Paul Emile Victor (IPEV) for OISO cruises NM; French Institut de recherche pour le développement (IRD) NL; German Federal Ministry of Education and Research (grant no. 01LK1224I ICOS-D) MH; German Research Foundation’s Emmy Noether Programme (grant no. PO1751/1-1) JN; German Max Planck Society CR, SZ; Germany, Federal Ministry of Education and Research (BMBF) AK; Germany, Helmholtz Postdoc Programme (Initiative and Networking Fund of the Helmholtz Association) JH; Japan Ministry of Agriculture, Forestry and Fisheries (MAFF) OT; Japan Ministry of Environment SN; Japan Ministry of Environment (grant no. ERTDF S-10) EK; NASA LCLUC programme (grant no. NASA NNX14AD94G) AJ; New Zealand National Institute of Water and Atmospheric Research (NIWA) Core Funding KC; Norway Research Council (grant no. 229752) AMO; Norway Research Council (grant no. 569980) GPP, RMA, JIK; Norway Research Council (project EVA; grant no. 229771) JS; Norwegian Environment Agency (grant no. 16078007) IS; Research Fund – Flanders (FWO; formerly Hercules Foundation) TG; South Africa Council for Scientific and Industrial Research (CSIR) PMSM; UK Natural Environment Research Council (RAGANRAoCC; grant no. NE/K002473/1) US; UK Newton Fund through the Met Office Climate Science for Service Partnership Brazil (CSSP Brazil) AJW; US Department of Agriculture, National Institute of Food and Agriculture (grant no. 2015-67003- 23485) DL; US Department of Energy (grant no. DE-FC03-97ER62402/A010) DL; US Department of Energy, Biological and Environmental Research Program, Office of Science (grant no. DE-AC05-00OR22725) APW; US Department of Commerce, NOAA’s Climate Observation Division of the Climate Program Office SRA, AJS; US Department of Energy, Office of Science and BER programme (grant no. DOE DE-SC0016323) AJ; US National Science Foundation (grant no. AGS-1048827) SD; US National Science Foundation (grant no. AOAS-1543457) DRM; US National Science Foundation (grant no. AOAS-1341647) DRM; US NOAA’s Climate Observation Division of the Climate Program Office (grant no. N8R1SE3P00); US NOAA’s Ocean Acidification Program (grant no. N8R3CEAP00) DP, LB; US National Science Foundation (grant no. NSF AGS 12-43071)