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1. Regional atmospheric CO2 inversion reveals seasonal and geographic differences in Amazon net biome exchange

Author

Caroline B. Alden, John B. Miller, Luciana V. Gatti, Manuel M. Gloor, Kaiyu Guan, Anna M. Michalak, Ingrid T. van der Laan‐Luijkx, Danielle Touma, Arlyn Andrews, Luana S. Basso, Caio S. C. Correia, Lucas G. Domingues, Joanna Joiner, Maarten C. Krol, Alexei I. Lyapustin, Wouter Peters, Yoichi P. Shiga, Kirk Thoning, Ivar R. van der Velde, Thijs T. van Leeuwen, Vineet Yadav, and Noah S. Diffenbaugh

Published
2016
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3. Global atmospheric CO2 inverse models converging on neutral tropical land exchange, but disagreeing on fossil fuel and atmospheric growth rate

Author

Wouter Peters, Britton B. Stephens, Tazu Saeki, Steven C. Wofsy, Eric A. Kort, Prabir K. Patra, Sourish Basu, Christian Rödenbeck, Feng Deng, David S. Schimel, Yi Yin, Frédéric Chevallier, Ingrid T. van der Laan-Luijkx, and Benjamin Gaubert

Subjects
010504 meteorology & atmospheric sciences, business.industry, Fossil fuel, Northern Hemisphere, Atmospheric carbon cycle, Inversion (meteorology), 04 agricultural and veterinary sciences, 15. Life on land, Atmospheric sciences, 01 natural sciences, Carbon cycle, Flux (metallurgy), 13. Climate action, 040103 agronomy & agriculture, Extratropical cyclone, 0401 agriculture, forestry, and fisheries, Environmental science, Growth rate, business, Ecology, Evolution, Behavior and Systematics, 0105 earth and related environmental sciences, Earth-Surface Processes
Abstract

We have compared a suite of recent global CO2 atmospheric inversion results to independent airborne observations and to each other, to assess their dependence on differences in northern extratropical (NET) vertical transport and to identify some of the drivers of model spread. We evaluate posterior CO2 concentration profiles against observations from the High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) Pole-to-Pole Observations (HIPPO) aircraft campaigns over the mid-Pacific in 2009–2011. Although the models differ in inverse approaches, assimilated observations, prior fluxes, and transport models, their broad latitudinal separation of land fluxes has converged significantly since the Atmospheric Carbon Cycle Inversion Intercomparison (TransCom 3) and the REgional Carbon Cycle Assessment and Processes (RECCAP) projects, with model spread reduced by 80 % since TransCom 3 and 70 % since RECCAP. Most modeled CO2 fields agree reasonably well with the HIPPO observations, specifically for the annual mean vertical gradients in the Northern Hemisphere. Northern Hemisphere vertical mixing no longer appears to be a dominant driver of northern versus tropical (T) annual flux differences. Our newer suite of models still gives northern extratropical land uptake that is modest relative to previous estimates (Gurney et al., 2002; Peylin et al., 2013) and near-neutral tropical land uptake for 2009–2011. Given estimates of emissions from deforestation, this implies a continued uptake in intact tropical forests that is strong relative to historical estimates (Gurney et al., 2002; Peylin et al., 2013). The results from these models for other time periods (2004–2014, 2001–2004, 1992–1996) and re-evaluation of the TransCom 3 Level 2 and RECCAP results confirm that tropical land carbon fluxes including deforestation have been near neutral for several decades. However, models still have large disagreements on ocean–land partitioning. The fossil fuel (FF) and the atmospheric growth rate terms have been thought to be the best-known terms in the global carbon budget, but we show that they currently limit our ability to assess regional-scale terrestrial fluxes and ocean–land partitioning from the model ensemble.

Published
2019
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4. Supplementary material to 'The regional EUROpean atmospheric transport inversion COMparison, EUROCOM: first results on European wide terrestrial carbon fluxes for the period 2006–2015'

Author

Guillaume Monteil, Grégoire Broquet, Marko Scholze, Matthew Lang, Ute Karstens, Christof Gerbig, Frank-Thomas Koch, Naomi E Smith, Rona L. Thompson, Ingrid T. van der Laan-Luijkx, Emily White, Antoon Meesters, Philippe Ciais, Anita L. Ganesan, Alistair Manning, Michael Mischurow, Wouter Peters, Philippe Peylin, Jerôme Tarniewicz, Matt Rigby, Christian Rödenbeck, Alex Vermeulen, and Evie M. Walton

Published
2019
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5. The regional EUROpean atmospheric transport inversion COMparison, EUROCOM: first results on European wide terrestrial carbon fluxes for the period 2006–2015

Author

Guillaume Monteil, Grégoire Broquet, Marko Scholze, Matthew Lang, Ute Karstens, Christof Gerbig, Frank-Thomas Koch, Naomi E Smith, Rona L. Thompson, Ingrid T. van der Laan-Luijkx, Emily White, Antoon Meesters, Philippe Ciais, Anita L. Ganesan, Alistair Manning, Michael Mischurow, Wouter Peters, Philippe Peylin, Jerôme Tarniewicz, Matt Rigby, Christian Rödenbeck, Alex Vermeulen, and Evie M. Walton

Abstract

Atmospheric inversions have been used for the past two decades to derive large scale constraints on the sources and sinks of CO2 into the atmosphere. The development of high density in-situ surface observation networks, such as ICOS in Europe, enables in theory inversions at a resolution close to the country scale in Europe. This has led to the development of many regional inversion systems capable of assimilating these high-resolution data, in Europe and elsewhere. The EUROCOM project (EUROpean atmospheric transport inversion COMparison) is a collaboration between seven European research institutes, which aims at producing a collective assessment of the net carbon flux between the terrestrial ecosystems and the atmosphere in Europe for the period 2006–2015. It aims in particular at investigating the capacity of the inversions to deliver consistent flux estimates from the country scale up to the continental scale. The project participants were provided with a common database of in-situ observed CO2 concentrations (including the observation sites that are now part of the ICOS network), and were tasked with providing their best estimate of the net terrestrial carbon flux for that period, and for a large domain covering the entire European Union. The inversion systems differ by the transport model, the inversion approach and the choice of observation and prior constraints, enabling us to widely explore the space of uncertainties. This paper describes the intercomparison protocol and the participating systems, and it presents the first results from a reference set of inversions, at the continental scale and in four large regions. At the continental scale, the regional inversions support the assumption that European ecosystems are a relatively small sink (−0.21 ± 0.2 PgC/year). We find that the convergence of the regional inversions at this scale is not better than that obtained in state-of-the-art global inversions. However, more robust results are obtained for sub-regions within Europe, and in these areas with dense observational coverage, the objective of delivering robust country scale flux estimates appears achievable in the near future.

Published
2019
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6. Global methane emission estimates for 2000–2012 from CarbonTracker Europe-CH4 v1.0

Author

Edward J. Dlugokencky, Renato Spahni, Rigel Kivi, Christoph Gerbig, A. J. Gomez-Pelaez, Tuula Aalto, Aki Tsuruta, Maarten Krol, Janne Hakkarainen, Jgor Arduini, Leif Backman, F. Apadula, Raymond Ellul, Sander Houweling, Dietrich G. Feist, Ingrid T. van der Laan-Luijkx, Ray L. Langenfelds, Wouter Peters, Yukio Yoshida, Marko Laine, and Marcel van der Schoot

Subjects
010504 meteorology & atmospheric sciences, business.industry, Fossil fuel, Flux, 010502 geochemistry & geophysics, 01 natural sciences, 7. Clean energy, Methane, chemistry.chemical_compound, Data assimilation, chemistry, 13. Climate action, Climatology, Greenhouse gas, Environmental science, Satellite, Sink (computing), Total Carbon Column Observing Network, business, 0105 earth and related environmental sciences
Abstract

We present a global distribution of surface methane (CH4) emission estimates for 2000–2012 derived using the CarbonTracker Europe-CH4 (CTE-CH4) data assimilation system. In CTE-CH4, anthropogenic and biospheric CH4 emissions are simultaneously estimated based on constraints of global atmospheric in situ CH4 observations. The system was configured to either estimate only anthropogenic or biospheric sources per region, or to estimate both categories simultaneously. The latter increased the number of optimizable parameters from 62 to 78. In addition, the differences between two numerical schemes available to perform turbulent vertical mixing in the atmospheric transport model TM5 were examined. Together, the system configurations encompass important axes of uncertainty in inversions and allow us to examine the robustness of the flux estimates. The posterior emission estimates are further evaluated by comparing simulated atmospheric CH4 to surface in situ observations, vertical profiles of CH4 made by aircraft, remotely sensed dry-air total column-averaged mole fraction (XCH4) from the Total Carbon Column Observing Network (TCCON), and XCH4 from the Greenhouse gases Observing Satellite (GOSAT). The evaluation with non-assimilated observations shows that posterior XCH4 is better matched with the retrievals when the vertical mixing scheme with faster interhemispheric exchange is used. Estimated posterior mean total global emissions during 2000–2012 are 516 ± 51 Tg CH4 yr−1, with an increase of 18 Tg CH4 yr−1 from 2000–2006 to 2007–2012. The increase is mainly driven by an increase in emissions from South American temperate, Asian temperate and Asian tropical TransCom regions. In addition, the increase is hardly sensitive to different model configurations (

Published
2017
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7. Global 3-D Simulations of the Triple Oxygen Isotope Signature Δ17O in Atmospheric CO2

Author

Erik van Schaik, Gerbrand Koren, Magdalena E. G. Hofmann, Thomas Röckmann, Sasadhar Mahata, Getachew A. Adnew, Linda Schneider, Maarten Krol, Ingrid T. van der Laan-Luijkx, Ivar R. van der Velde, Wouter Peters, Sergey Gromov, Peter Bergamaschi, Dorota J. Mrozek Martino, Mao-Chang Liang, Isotope Research, and Earth and Climate

Subjects
Meteorologie en Luchtkwaliteit, Atmospheric Science, 010504 meteorology & atmospheric sciences, TRACER, Atmospheric Composition and Structure, Carbon Cycling, Atmospheric sciences, Biogeosciences, 01 natural sciences, 7. Clean energy, Isotopes of oxygen, Troposphere, Biogeochemical Kinetics and Reaction Modeling, Oceanography: Biological and Chemical, DIOXIDE EXCHANGE, 3-DIMENSIONAL SYNTHESIS, carbon dioxide (CO2), ddc:550, Earth and Planetary Sciences (miscellaneous), SDG 13 - Climate Action, O-17 excess (Delta O-17), Research Articles, O-18 CONTENT, mass-independent fractionation (MIF), Stable isotope ratio, Vegetation, Biogeochemistry, Geophysics, Atmospheric Processes, Cryosphere, 17O excess (Δ17O), FIRE EMISSIONS, Biogeochemical Cycles, Processes, and Modeling, Research Article, Stable Isotope Geochemistry, CARBONIC-ANHYDRASE ACTIVITY, Meteorology and Air Quality, δ18O, STRATOSPHERIC CO2, STOMATAL CONDUCTANCE, stable isotopes, MASS, carbon dioxide (CO), Carbon cycle, Atmosphere, Paleoceanography, O excess (ΔO), carbon cycle, SDG 14 - Life Below Water, Global Change, Biosphere/Atmosphere Interactions, Stratosphere/Troposphere Interactions, 0105 earth and related environmental sciences, Isotopic Composition and Chemistry, WIMEK, gross primary production (GPP), Primary production, Composition and Chemistry, mass‐independent fractionation (MIF), Earth sciences, Geochemistry, 13. Climate action, Space and Planetary Science, MODEL TM5, Environmental science
Abstract

The triple oxygen isotope signature Δ17O in atmospheric CO2, also known as its “17O excess,” has been proposed as a tracer for gross primary production (the gross uptake of CO2 by vegetation through photosynthesis). We present the first global 3‐D model simulations for Δ17O in atmospheric CO2 together with a detailed model description and sensitivity analyses. In our 3‐D model framework we include the stratospheric source of Δ17O in CO2 and the surface sinks from vegetation, soils, ocean, biomass burning, and fossil fuel combustion. The effect of oxidation of atmospheric CO on Δ17O in CO2 is also included in our model. We estimate that the global mean Δ17O (defined as Δ17O=ln(δ17O+1)−λRL·ln(δ18O+1) with λ RL = 0.5229) of CO2 in the lowest 500 m of the atmosphere is 39.6 per meg, which is ∼20 per meg lower than estimates from existing box models. We compare our model results with a measured stratospheric Δ17O in CO2 profile from Sodankylä (Finland), which shows good agreement. In addition, we compare our model results with tropospheric measurements of Δ17O in CO2 from Göttingen (Germany) and Taipei (Taiwan), which shows some agreement but we also find substantial discrepancies that are subsequently discussed. Finally, we show model results for Zotino (Russia), Mauna Loa (United States), Manaus (Brazil), and South Pole, which we propose as possible locations for future measurements of Δ17O in tropospheric CO2 that can help to further increase our understanding of the global budget of Δ17O in atmospheric CO2., Key Points This work presents a first view on possible spatial and temporal gradients of Δ17O in CO2 across the globeTropical, boreal, and Southern Hemisphere observations of Δ17O in CO2 could be of great interestWe implemented spatially and temporally explicit sources and sinks of Δ17O in CO2 in a 3‐D model framework

Published
2019
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8. Inferring 222Rn soil fluxes from ambient 222Rn activity and eddy covariance measurements of CO2

Author

Ingrid T. van der Laan-Luijkx, Swagath Navin Manohar, Sander van der Laan, Fred C. Bosveld, Andrew C. Manning, Harro A. J. Meijer, Michiel K. van der Molen, and Alex Vermeulen

Subjects
Atmospheric Science, 010504 meteorology & atmospheric sciences, Meteorology, Eddy covariance, chemistry.chemical_element, Radon, Soil type, Atmospheric sciences, 01 natural sciences, 030218 nuclear medicine & medical imaging, Moment (mathematics), 03 medical and health sciences, 0302 clinical medicine, Flux (metallurgy), chemistry, Greenhouse gas, Calibration, Measurement uncertainty, Environmental science, 0105 earth and related environmental sciences
Abstract

We present a new methodology, which we call Single Pair of Observations Technique with Eddy Covariance (SPOT-EC), to estimate regional-scale surface fluxes of 222Rn from tower-based observations of 222Rn activity concentration, CO2 mole fractions and direct CO2 flux measurements from eddy covariance. For specific events, the regional (222Rn) surface flux is calculated from short-term changes in ambient (222Rn) activity concentration scaled by the ratio of the mean CO2 surface flux for the specific event to the change in its observed mole fraction. The resulting 222Rn surface emissions are integrated in time (between the moment of observation and the last prior background levels) and space (i.e. over the footprint of the observations). The measurement uncertainty obtained is about ±15 % for diurnal events and about ±10 % for longer-term (e.g. seasonal or annual) means. The method does not provide continuous observations, but reliable daily averages can be obtained. We applied our method to in situ observations from two sites in the Netherlands: Cabauw station (CBW) and Lutjewad station (LUT). For LUT, which is an intensive agricultural site, we estimated a mean 222Rn surface flux of (0.29 ± 0.02) atoms cm−2 s−1 with values > 0.5 atoms cm−2 s−1 to the south and south-east. For CBW we estimated a mean 222Rn surface flux of (0.63 ± 0.04) atoms cm−2 s−1. The highest values were observed to the south-west, where the soil type is mainly river clay. For both stations good agreement was found between our results and those from measurements with soil chambers and two recently published 222Rn soil flux maps for Europe. At both sites, large spatial and temporal variability of 222Rn surface fluxes were observed which would be impractical to measure with a soil chamber. SPOT-EC, therefore, offers an important new tool for estimating regional-scale 222Rn surface fluxes. Practical applications furthermore include calibration of process-based 222Rn soil flux models, validation of atmospheric transport models and performing regional-scale inversions, e.g. of greenhouse gases via the SPOT 222Rn-tracer method.

Published
2016
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9. Increased water-use efficiency and reduced CO

Author

Wouter, Peters, Ivar R, van der Velde, Erik, van Schaik, John B, Miller, Philippe, Ciais, Henrique F, Duarte, Ingrid T, van der Laan-Luijkx, Michiel K, van der Molen, Marko, Scholze, Kevin, Schaefer, Pier Luigi, Vidale, Anne, Verhoef, David, Wårlind, Dan, Zhu, Pieter P, Tans, Bruce, Vaughn, and James W C, White

Subjects
fungi, food and beverages, Article
Abstract

Severe droughts in the Northern Hemisphere cause widespread decline of agricultural yield, reduction of forest carbon uptake, and increased CO2 growth rates in the atmosphere. Plants respond to droughts by partially closing their stomata to limit their evaporative water loss, at the expense of carbon uptake by photosynthesis. This trade-off maximizes their water-use efficiency, as measured for many individual plants under laboratory conditions and field experiments. Here we analyze the 13C/12C stable isotope ratio in atmospheric CO2 (reported as δ13C) to provide new observational evidence of the impact of droughts on the water-use efficiency across areas of millions of km2 and spanning one decade of recent climate variability. We find strong and spatially coherent increases in water-use efficiency along with widespread reductions of net carbon uptake over the Northern Hemisphere during severe droughts that affected Europe, Russia, and the United States in 2001-2011. The impact of those droughts on water-use efficiency and carbon uptake by vegetation is substantially larger than simulated by the land-surface schemes of six state-of-the-art climate models. This suggests that drought induced carbon-climate feedbacks may be too small in these models and improvements to their vegetation dynamics using stable isotope observations can help to improve their drought response.

Published
2018

10. Global Carbon Budget 2018

Author

Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Judith Hauck, Julia Pongratz, Penelope Pickers, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Almut Arneth, Vivek K. Arora, Leticia Barbero, Ana Bastos, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Scott C. Doney, Thanos Gkritzalis, Daniel S. Goll, Ian Harris, Vanessa Haverd, Forrest M. Hoffman, Mario Hoppema, Richard A. Houghton, Tatiana Ilyina, Atul K. Jain, Truls Johannesen, Chris D. Jones, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Peter Landschützer, Nathalie Lefèvre, Sebastian Lienert, Danica Lombardozzi, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Craig Neill, Are Olsen, Tsueno Ono, Prabir Patra, Anna Peregon, Wouter Peters, Philippe Peylin, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Matthias Rocher, Christian Rödenbeck, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Tobias Steinhoff, Adrienne Sutton, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, Rebecca Wright, and Sönke Zaehle

Abstract

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. Fossil CO2 emissions (EFF) are based on energy statistics and cement production data, while emissions from land use and land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate (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 imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2008–2017), EFF was 9.4±0.5 GtC yr−1, ELUC 1.5±0.7 GtC yr−1, GATM 4.7±0.02 GtC yr−1, SOCEAN 2.4±0.5 GtC yr−1, and SLAND 3.2±0.8 GtC yr−1, with a budget imbalance BIM of 0.5 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For the year 2017 alone, the growth in EFF was about 1.6 % and emissions increased to 9.9±0.5 GtC yr−1. Also for 2017, ELUC was 1.4±0.7 GtC yr−1, GATM was 4.6±0.2 GtC yr−1, SOCEAN was 2.5±0.5 GtC yr−1, and SLAND was 3.8±0.8 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 405.0±0.1 ppm averaged over 2017. For 2018, preliminary data for the first 6–9 months indicate a renewed growth in EFF of +2.7 % (range of 1.8 % to 3.7 %) based on national emission projections for China, the US, the EU, 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. The analysis presented here shows that the mean and trend in the five components of the global carbon budget are consistently estimated over the period of 1959–2017, but discrepancies of up to 1 GtC yr−1 persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations show (1) no consensus in the mean and trend in land-use change emissions, (2) a persistent low agreement among the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models, originating outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding the global carbon cycle compared with previous publications of this data set (Le Quéré et al., 2018, 2016, 2015a, b, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2018.

Published
2018
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11. CTDAS-Lagrange v1.0: a high-resolution data assimilation system for regional carbon dioxide observations

Author

Thomas Nehrkorn, Colm Sweeney, John B. Miller, Wouter Peters, Wei He, Ingrid T. van der Laan-Luijkx, Huilin Chen, Ivar R. van der Velde, Weimin Ju, Pieter P. Tans, Arlyn E. Andrews, M. E. Mountain, and Isotope Research

Subjects
0106 biological sciences, Meteorologie en Luchtkwaliteit, 010504 meteorology & atmospheric sciences, Meteorology and Air Quality, Atmospheric sciences, 01 natural sciences, Data assimilation, Flux (metallurgy), Range (statistics), ATMOSPHERIC CO2 INVERSIONS, Life Science, Sensitivity (control systems), GREENHOUSE-GAS MEASUREMENTS, EXCHANGE, 0105 earth and related environmental sciences, WIMEK, SATELLITE-OBSERVATIONS, 010604 marine biology & hydrobiology, lcsh:QE1-996.5, TECHNICAL NOTE, Carbon sink, Biosphere, Sampling (statistics), NORTH-AMERICA, Covariance, AIR-SAMPLING-NETWORK, lcsh:Geology, MODEL, 13. Climate action, Environmental science, ANTHROPOGENIC EMISSIONS, INTERANNUAL VARIABILITY
Abstract

We have implemented a regional carbon dioxide data assimilation system based on the CarbonTracker Data Assimilation Shell (CTDAS) and a high-resolution Lagrangian transport model, the Stochastic Time-Inverted Lagrangian Transport model driven by the Weather Forecast and Research meteorological fields (WRF-STILT). With this system, named CTDAS-Lagrange, we simultaneously optimize terrestrial biosphere fluxes and four parameters that adjust the lateral boundary conditions (BCs) against CO2 observations from the NOAA ESRL North America tall tower and aircraft programmable flask packages (PFPs) sampling program. Least-squares optimization is performed with a time-stepping ensemble Kalman smoother, over a time window of 10 days and assimilating sequentially a time series of observations. Because the WRF-STILT footprints are pre-computed, it is computationally efficient to run the CTDAS-Lagrange system. To estimate the uncertainties in the optimized fluxes from the system, we performed sensitivity tests with various a priori biosphere fluxes (SiBCASA, SiB3, CT2013B) and BCs (optimized mole fraction fields from CT2013B and CTE2014, and an empirical dataset derived from aircraft observations), as well as with a variety of choices on the ways that fluxes are adjusted (additive or multiplicative), covariance length scales, biosphere flux covariances, BC parameter uncertainties, and model–data mismatches. In pseudo-data experiments, we show that in our implementation the additive flux adjustment method is more flexible in optimizing net ecosystem exchange (NEE) than the multiplicative flux adjustment method, and our sensitivity tests with real observations show that the CTDAS-Lagrange system has the ability to correct for the potential biases in the lateral BCs and to resolve large biases in the prior biosphere fluxes. Using real observations, we have derived a range of estimates for the optimized carbon fluxes from a series of sensitivity tests, which places the North American carbon sink for the year 2010 in a range from −0.92 to −1.26 PgC yr−1. This is comparable to the TM5-based estimates of CarbonTracker (version CT2016, -0.91±1.10 PgC yr−1) and CarbonTracker Europe (version CTE2016, -0.91±0.31 PgC yr−1). We conclude that CTDAS-Lagrange can offer a versatile and computationally attractive alternative to these global systems for regional estimates of carbon fluxes, which can take advantage of high-resolution Lagrangian footprints that are increasingly easy to obtain.

Published
2018

12. Changes in surface hydrology, soil moisture and gross primary production in the Amazon during the 2015/2016 El Niño

Author

Naomi E. Smith, Lars Killaars, Ingrid T. van der Laan-Luijkx, Gerbrand Koren, Wouter Peters, L. P. H. van Beek, Erik van Schaik, and Isotope Research

Subjects
Meteorologie en Luchtkwaliteit, 010504 meteorology & atmospheric sciences, Meteorology and Air Quality, 0208 environmental biotechnology, 02 engineering and technology, Forests, 01 natural sciences, General Biochemistry, Genetics and Molecular Biology, Carbon Cycle, Carbon cycle, Soil, Hydrology (agriculture), Dry season, Precipitation, El Niño, Amazon, 0105 earth and related environmental sciences, El Nino-Southern Oscillation, Hydrology, WIMEK, Amazon rainforest, Discharge, Tropics, Primary production, Articles, 15. Life on land, tropical terrestrial carbon cycle, Droughts, 020801 environmental engineering, 13. Climate action, Environmental science, Seasons, soil moisture, General Agricultural and Biological Sciences, gross primary productivity, river discharge, Brazil, Research Article
Abstract

The 2015/2016 El Niño event caused severe changes in precipitation across the tropics. This impacted surface hydrology, such as river run-off and soil moisture availability, thereby triggering reductions in gross primary production (GPP). Many biosphere models lack the detailed hydrological component required to accurately quantify anomalies in surface hydrology and GPP during droughts in tropical regions. Here, we take the novel approach of coupling the biosphere model SiBCASA with the advanced hydrological model PCR-GLOBWB to attempt such a quantification across the Amazon basin during the drought in 2015/2016. We calculate 30–40% reduced river discharge in the Amazon starting in October 2015, lagging behind the precipitation anomaly by approximately one month and in good agreement with river gauge observations. Soil moisture shows distinctly asymmetrical spatial anomalies with large reductions across the north-eastern part of the basin, which persisted into the following dry season. This added to drought stress in vegetation, already present owing to vapour pressure deficits at the leaf, resulting in a loss of GPP of 0.95 (0.69 to 1.20) PgC between October 2015 and March 2016 compared with the 2007–2014 average. Only 11% (10–12%) of the reduction in GPP was found in the (wetter) north-western part of the basin, whereas the north-eastern and southern regions were affected more strongly, with 56% (54–56%) and 33% (31–33%) of the total, respectively. Uncertainty on this anomaly mostly reflects the unknown rooting depths of vegetation. This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications’.

Published
2018

13. Increased water-use efficiency and reduced CO2 uptake by plants during droughts at a continental scale

Author

Pier Luigi Vidale, Michiel K. van der Molen, Ingrid T. van der Laan-Luijkx, Bruce H. Vaughn, Henrique F. Duarte, Wouter Peters, Philippe Ciais, Erik van Schaik, James W. C. White, Dan Zhu, David Wårlind, Kevin Schaefer, John B. Miller, Ivar R. van der Velde, Anne Verhoef, Marko Scholze, Pieter Tans, Isotope Research, Wageningen University and Research [Wageningen] (WUR), University of Colorado [Boulder], National Oceanic and Atmospheric Administration (NOAA), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-ATC (ICOS-ATC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)

Subjects
0106 biological sciences, Meteorologie en Luchtkwaliteit, FLUXES, 010504 meteorology & atmospheric sciences, GRASSLAND, Meteorology and Air Quality, MODELS, Atmospheric sciences, CARBON-ISOTOPE DISCRIMINATION, 01 natural sciences, Grassland, Atmosphere, DIOXIDE EXCHANGE, LEAF, Life Science, Water-use efficiency, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, geography, geography.geographical_feature_category, WIMEK, PRODUCTIVITY, Stable isotope ratio, PHOTOSYNTHESIS, fungi, Northern Hemisphere, food and beverages, Vegetation, 15. Life on land, ATMOSPHERE, REDUCTION, Productivity (ecology), 13. Climate action, General Earth and Planetary Sciences, Environmental science, Climate model, 010606 plant biology & botany
Abstract

Severe droughts in the Northern Hemisphere cause a widespread decline of agricultural yield, the reduction of forest carbon uptake, and increased CO2 growth rates in the atmosphere. Plants respond to droughts by partially closing their stomata to limit their evaporative water loss, at the expense of carbon uptake by photosynthesis. This trade-off maximizes their water-use efficiency (WUE), as measured for many individual plants under laboratory conditions and field experiments. Here we analyse the C-13/C-12 stable isotope ratio in atmospheric CO2 to provide new observational evidence of the impact of droughts on the WUE across areas of millions of square kilometres and spanning one decade of recent climate variability. We find strong and spatially coherent increases in WUE along with widespread reductions of net carbon uptake over the Northern Hemisphere during severe droughts that affected Europe, Russia and the United States in 2001-2011. The impact of those droughts on WUE and carbon uptake by vegetation is substantially larger than simulated by the land-surface schemes of six state-of-the-art climate models. This suggests that drought-induced carbon-climate feedbacks may be too small in these models and improvements to their vegetation dynamics using stable isotope observations can help to improve their drought response.

Published
2018
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16. Global Carbon Budget 2016

Author

Ian Harris, Richard A. Houghton, Josep G. Canadell, Pieter P. Tans, Abdirahman M Omar, Thomas A. Boden, Leticia Barbero, Arne Körtzinger, Adrienne J. Sutton, Guido R. van der Werf, Frank J. Millero, Benjamin D. Stocker, Julia E. M. S. Nabel, Louise Chini, Denis Pierrot, Scott C. Doney, Shin-Ichiro Nakaoka, Andrew Lenton, Kim I. Currie, Nicolas Viovy, Pedro M. S. Monteiro, Sönke Zaehle, Oliver Andrews, Philippe Ciais, Peter Landschützer, Ute Schuster, Stephen Sitch, Pierre Friedlingstein, Vanessa Haverd, Simone R. Alin, Judith Hauck, Christian Rödenbeck, Atul K. Jain, Nathalie Lefèvre, Ingrid T. van der Laan-Luijkx, Joe R. Melton, Mario Hoppema, Benjamin Poulter, Frédéric Chevallier, Taro Takahashi, Hanqin Tian, Thanos Gkritzalis, Tsuneo Ono, Etsushi Kato, Andrew C. Manning, Roland Séférian, Danica Lombardozzi, Jörg Schwinger, Jan Ivar Korsbakken, David R. Munro, Corinne Le Quéré, Anthony P. Walker, Laurent Bopp, Peter Anthoni, Bronte Tilbrook, Glen P. Peters, Andy Wiltshire, Sebastian Lienert, Are Olsen, Ralph F. Keeling, Nicolas Metzl, Robbie M. Andrew, Christine Delire, Joe Salisbury, Kees Klein Goldewijk, K. O'Brien, Ingunn Skjelvan, Tyndall Centre for Climate Change Research, University of East Anglia [Norwich] (UEA), Center for International Climate and Environmental Research [Oslo] (CICERO), University of Oslo (UiO), Global Carbon Project (GCP), CSIRO Marine and Atmospheric Research (CSIRO-MAR), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO)-Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), College of Life and Environmental Sciences, University of Exeter, Centre for Ocean and Atmospheric Sciences [Norwich] (COAS), School of Environmental Sciences [Norwich], University of East Anglia [Norwich] (UEA)-University of East Anglia [Norwich] (UEA), Oak Ridge National Laboratory [Oak Ridge] (ORNL), UT-Battelle, LLC, NOAA Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA), Woods Hole Oceanographic Institution (WHOI), University of California [San Diego] (UC San Diego), University of California, NOAA Pacific Marine Environmental Laboratory [Seattle] (PMEL), Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), NOAA Atlantic Oceanographic and Meteorological Laboratory (AOML), Cooperative Institute for Marine and Atmospheric Studies (CIMAS), Rosenstiel School of Marine and Atmospheric Science (RSMAS), University of Miami [Coral Gables]-University of Miami [Coral Gables], Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Department of Geographical Sciences, University of Maryland [College Park], University of Maryland System-University of Maryland System, ICOS-ATC (ICOS-ATC), National Institute of Water and Atmospheric Research [Wellington] (NIWA), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), College of Engineering, Mathematics and Physical Sciences [Exeter] (EMPS), University of Exeter, Flanders Marine Institute, VLIZ, Climatic Research Unit, University of East Anglia, Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), Commonwealth Scientific and Industrial Research Organisation (CSIRO), Oceans and Atmosphere Flagship, PBL Netherlands Environmental Assessment Agency, STMicroelectronics [Crolles] (ST-CROLLES), The Institute of Applied Energy (IAE), Christian-Albrechts-Universität zu Kiel (CAU), Helmholtz Centre for Ocean Research [Kiel] (GEOMAR), Max-Planck-Institut für Meteorologie (MPI-M), Max-Planck-Gesellschaft, Austral, Boréal et Carbone (ABC), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Oceans and Atmosphere Flagship (CSIRO), CSIRO Oceans and Atmosphere Flagship, Équipe CO2 (E-CO2), Department of Ocean Sciences, University of Miami [Coral Gables], Department of Civil and Environmental Engineering [Berkeley] (CEE), University of California [Berkeley], University of California-University of California, University of Wisconsin Whitewater, Max Planck Institute for Meteorology (MPI-M), National Institute for Environmental Studies (NIES), NASA Langley Research Center [Hampton] (LaRC), National Institute of Advanced Industrial Science and Technology (AIST), Entrepôts, Représentation et Ingénierie des Connaissances (ERIC), Université Lumière - Lyon 2 (UL2)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, Max-Planck-Institut, Ocean Process Analysis Laboratory (OPAL), University of New Hampshire (UNH), Bjerknes Centre for Climate Research (BCCR), Department of Biological Sciences [Bergen] (BIO / UiB), University of Bergen (UiB)-University of Bergen (UiB), Imperial College London, Scripps Institution of Oceanography (SIO), Joint Institute for the Study of the Atmosphere and Ocean (JISAO), University of Washington [Seattle], Institute of Space and Astronautical Science (ISAS), Japan Aerospace Exploration Agency [Sagamihara] (JAXA), Shandong Agricultural University (SDAU), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Wageningen University and Research [Wageningen] (WUR), Faculty of Earth and Life Sciences [Amsterdam] (FALW), Vrije Universiteit Amsterdam [Amsterdam] (VU), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), School of Earth and Environment [Leeds] (SEE), University of Leeds, Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Biogeochemical Systems Department [Jena], Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft-Max-Planck-Gesellschaft, Environmental Sciences, Faculty of Earth and Life Sciences, Earth and Climate, University of California (UC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), University of California [Berkeley] (UC Berkeley), University of California (UC)-University of California (UC), and Scripps Institution of Oceanography (SIO - UC San Diego)

Subjects
Meteorologie en Luchtkwaliteit, 010504 meteorology & atmospheric sciences, Meteorology and Air Quality, 530 Physics, Climate change, [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], 02 engineering and technology, 010501 environmental sciences, Atmospheric sciences, 01 natural sciences, 7. Clean energy, Carbon cycle, Latitude, SDG 17 - Partnerships for the Goals, Deforestation, ddc:550, SDG 13 - Climate Action, Life Science, lcsh:Environmental sciences, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, lcsh:GE1-350, WIMEK, business.industry, Fossil fuel, lcsh:QE1-996.5, Biosphere, Vegetation, 15. Life on land, 021001 nanoscience & nanotechnology, lcsh:Geology, Earth sciences, 13. Climate action, General Earth and Planetary Sciences, Environmental science, Sink (computing), 0210 nano-technology, business
Abstract

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).

Published
2016
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17. Supplementary material to 'Development of CarbonTracker Europe-CH4 – Part 2: global methane emission estimates and their evaluation for 2000–2012'

Author

Aki Tsuruta, Tuula Aalto, Leif Backman, Janne Hakkarainen, Ingrid T. van der Laan-Luijkx, Maarten C. krol, Renato Spahni, Sander Houweling, Marko Laine, Ed Dlugokencky, Angel J. Gomez-Pelaez, Marcel van der Schoot, Ray Langenfelds, Raymond Ellul, Jgor Arduini, Francesco Apadula, Christoph Gerbig, Dietrich G. Feist, Rigel Kivi, Yukio Yoshida, and Wouter Peters

Published
2016
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18. Development of CarbonTracker Europe-CH4 – Part 2: global methane emission estimates and their evaluation for 2000–2012

Author

Tuula Aalto, Janne Hakkarainen, Sander Houweling, Maarten Krol, Rigel Kivi, Marcel van der Schoot, A. J. Gomez-Pelaez, Wouter Peters, Yukio Yoshida, Aki Tsuruta, Leif Backman, Edward J. Dlugokencky, Christoph Gerbig, Ray L. Langenfelds, F. Apadula, Renato Spahni, Raymond Ellul, Dietrich G. Feist, Marko Laine, Ingrid T. van der Laan-Luijkx, and Jgor Arduini

Subjects
0106 biological sciences, chemistry.chemical_compound, 010504 meteorology & atmospheric sciences, chemistry, 13. Climate action, 010604 marine biology & hydrobiology, Environmental science, Atmospheric sciences, 7. Clean energy, 01 natural sciences, Methane, 0105 earth and related environmental sciences
Abstract

Gobal methane emissions were estimated for 2000–2012 using the CarbonTracker Europe-CH4 (CTE-CH4) data assimilation system. In CTE-CH4, the anthropogenic and biosphere emissions of CH4 are simultaneously constrained by global atmospheric in-situ methane mole fraction observations. We use three configurations developed in Tsuruta et al. (2016) to assess the sensitivity of the CH4 flux estimates to (a) the number of unknown flux scaling factors to be optimized which in turn depends on the choice of underlying land-ecosystem map, and (b) on the parametrization of vertical mixing in the 30 atmospheric transport model TM5. The posterior emission estimates were evaluated by comparing simulations to surface in-situ observation sites, to profile observations made by aircraft, to dry air total column-averaged mole fractions (XCH4) observations from the Total Carbon Column Observing Network (TCCON), and to XCH4 retrievals from the Greenhouse gases Observing SATellite (GOSAT). Our estimated posterior mean global total emissions during 2000–2012 are 516 ± 51 Tg CH4 yr−1, and emission estimates during 2007–2012 are 18 Tg CH4 yr−1 greater than those from 2001–2006, mainly driven by an 35 increase in emissions from the south America temperate region, the Asia temperate region and Asia tropics. The sensitivity of the flux estimates to the underlying ecosystem map was large for the Asia temperate region and Australia, but not significant in the northern latitude regions, i.e. the north American boreal region, the north American temperate region and Europe. Instead, the posterior estimates for the northern latitude regions show larger sensitivity to the choice of convection scheme in TM5. The Gregory et al. (2000) mixing scheme with faster interhemispheric exchange leads to higher estimated CH4 emissions at northern latitudes, and lower emissions in southern latitudes, compared to the estimates using Tiedtke (1989) convection scheme. Our evaluation with non-assimilated observations showed that posterior mole fractions were better matched with the 5 observations when Gregory et al. (2000) convection scheme was used.

Published
2016
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19. Development of CarbonTracker Europe-CH4 – Part 1: system set-up and sensitivity analyses

Author

Renato Spahni, Ingrid T. van der Laan-Luijkx, Janne Hakkarainen, Marcel van der Schoot, Tuula Aalto, Ray L. Langenfelds, Sander Houweling, Raymond Ellul, Marko Laine, Aki Tsuruta, Leif Backman, Wouter Peters, and Maarten Krol

Subjects
Convection, 010504 meteorology & atmospheric sciences, Meteorology, Covariance matrix, Atmospheric methane, Inverse, Biosphere, Ensemble Kalman filter, Covariance, 010502 geochemistry & geophysics, Spatial distribution, 01 natural sciences, 0105 earth and related environmental sciences
Abstract

CarbonTracker Europe-CH4 (CTE-CH4) inverse model versions 1.0 and 1.1 are presented. The model optimizes global surface methane emissions from biosphere and anthropogenic sources using an ensemble Kalman filter (EnKF) based optimization method, using the TM5 chemistry transport model as an observation operator, and assimilating global in-situ atmospheric methane mole fraction observations. In this study, we examine sensitivity of our CH4 emission estimates on the ensemble size, covariance matrix, prior estimates, observations to be assimilated, assimilation window length, convection scheme in TM5, and model structure in the emission estimates by performing CTE-CH4 with several set-ups. The analyses show that the model is sensitive to most of the parameters and inputs that were examined. Firstly, using a large enough ensemble size stabilises the results. Secondly, using an informative covariance matrix reduces uncertainty estimates. Thirdly, agreement with discrete observations became better when assimilating continuous observations. Finally, the posterior emissions were found sensitive to the choice of prior estimates, convection scheme and model structure, particularly to their spatial distribution. The distribution of posterior mole fractions derived from posterior emissions is consistent with the observations to the extent prescribed in the various covariance estimates, indicating a satisfactory performance of our system.

Published
2016
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20. Warm spring reduced carbon cycle impact of the 2012 US summer drought

Author

Ingrid T. van der Laan-Luijkx, Nathaniel A. Brunsell, Andrew D. Richardson, Russell L. Scott, Beverly E. Law, Sebastian Wolf, Wouter Peters, Ankur R. Desai, Joshua B. Fisher, Marcy E. Litvak, Trevor F. Keenan, Dennis D. Baldocchi, and Isotope Research

Subjects
Meteorologie en Luchtkwaliteit, 010504 meteorology & atmospheric sciences, Biosphere Atmosphere feedbacks, Eddy covariance, 01 natural sciences, Sink (geography), Hot Springs, PREDICTABILITY, chemistry.chemical_compound, ecosystem fluxes, EXCHANGE, Water content, Multidisciplinary, geography.geographical_feature_category, Carbon sink, Climate anomalies, food and beverages, 04 agricultural and veterinary sciences, seasonal climate anomalies, FOREST, Droughts, Climatology, Carbon dioxide, FEEDBACKS, atmosphere feedbacks, biosphere–atmosphere feedbacks, DIOXIDE, Ecosystem fluxes, biosphere, Meteorology and Air Quality, HEAT, SOIL-MOISTURE, Carbon cycle, Carbon Cycle, eddy covariance, Ecosystem, 0105 earth and related environmental sciences, geography, WIMEK, carbon uptake, Carbon uptake, Carbon Dioxide, Carbon, EDDY-COVARIANCE, Climate Action, CLIMATE, REDUCTION, chemistry, Soil water, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science
Abstract

The global terrestrial carbon sink offsets one-third of the world's fossil fuel emissions, but the strength of this sink is highly sensitive to large-scale extreme events. In 2012, the contiguous United States experienced exceptionally warm temperatures and the most severe drought since the Dust Bowl era of the 1930s, resulting in substantial economic damage. It is crucial to understand the dynamics of such events because warmer temperatures and a higher prevalence of drought are projected in a changing climate. Here, we combine an extensive network of direct ecosystem flux measurements with satellite remote sensing and atmospheric inverse modeling to quantify the impact of the warmer spring and summer drought on biosphere-atmosphere carbon and water exchange in 2012. We consistently find that earlier vegetation activity increased spring carbon uptake and compensated for the reduced uptake during the summer drought, which mitigated the impact on net annual carbon uptake. The early phenological development in the Eastern Temperate Forests played a major role for the continental-scale carbon balance in 2012. The warm spring also depleted soilwater resources earlier, and thus exacerbated water limitations during summer. Our results show that the detrimental effects of severe summer drought on ecosystem carbon storage can be mitigated by warming-induced increases in spring carbon uptake. However, the results also suggest that the positive carbon cycle effect of warm spring enhances water limitations and can increase summer heating through biosphere-atmosphere feedbacks.

Published
2016
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21. Etsushi Kato 29 , Markus Kautz 30 , Ralph F. Keeling 31

Author

Nicolas Vuichard, Markus Kautz, Atul K. Jain, Richard A. Houghton, Anthony P. Walker, Bronte Tilbrook, Glen P. Peters, Christian Rödenbeck, Christopher W. Hunt, Nicolas Metzl, Andy Wiltshire, Dan Zhu, Sebastian Lienert, Ingrid T. van der Laan-Luijkx, Benjamin Poulter, Judith Hauck, Frédéric Chevallier, Philippe Ciais, Benjamin D. Stocker, Thomas Gasser, Ralph F. Keeling, Vivek K. Arora, Etsushi Kato, Gregor Rehder, Andrew C. Manning, X. Antonio Padin, Ivan D. Lima, Andrew Lenton, Steven van Heuven, Jessica N. Cross, Leticia Barbero, Robbie M. Andrew, Nathalie Lefèvre, Denis Pierrot, Roland Séférian, Yukihiro Nojiri, Ingunn Skjelvan, Meike Becker, Guido R. van der Werf, George C. Hurtt, Kees Klein Goldewijk, Stephen Sitch, Julia E. M. S. Nabel, Ian Harris, Pieter P. Tans, Robert B. Jackson, Andrew J. Watson, Jan Ivar Korsbakken, Hanqin Tian, Francesco N. Tubiello, Thomas A. Boden, Arne Körtzinger, Frank J. Millero, Benjamin Pfeil, Oliver Andrews, Corinne Le Quéré, Shin-Ichiro Nakaoka, Nicolas Viovy, Anna Peregon, Catherine E Cosca, Vanessa Haverd, Richard Betts, Josep G. Canadell, Janet J. Reimer, Louise Chini, Kim I. Currie, Jörg Schwinger, Laurent Bopp, Tatiana Ilyina, Peter Landschützer, Dorothee C. E. Bakker, Pierre Friedlingstein, Julia Pongratz, David R. Munro, Danica Lombardozzi, Pedro M. S. Monteiro, Sönke Zaehle, Tyndall Centre for Climate Change Research, University of East Anglia [Norwich] (UEA), Center for International Climate and Environmental Research [Oslo] (CICERO), University of Oslo (UiO), College of Engineering, Mathematics and Physical Sciences, University of Exeter, College of Life and Environmental Sciences, University of Exeter, Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Global Carbon Project, CSIRO Marine and Atmospheric Research, Department of Earth System Science [Stanford] (ESS), Stanford EARTH, Stanford University-Stanford University, Climate Change Science Institute [Oak Ridge] (CCSI), Oak Ridge National Laboratory [Oak Ridge] (ORNL), UT-Battelle, LLC-UT-Battelle, LLC, ESRL Chemical Sciences Division [Boulder] (CSD), NOAA Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA)-National Oceanic and Atmospheric Administration (NOAA), Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, Cooperative Institute for Marine and Atmospheric Studies, Rosenstiel School for Marine and Atmospheric Science (CIMAS), Rosenstiel School of Marine and Atmospheric Science (RSMAS), University of Miami [Coral Gables]-University of Miami [Coral Gables], NOAA Atlantic Oceanographic and Meteorological Laboratory (AOML), National Oceanic and Atmospheric Administration (NOAA), Bjerknes Centre for Climate Research (BCCR), Department of Biological Sciences [Bergen] (BIO / UiB), University of Bergen (UiB)-University of Bergen (UiB), Geophysical Institute [Bergen] (GFI / BiU), University of Bergen (UiB), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Department of Geographical Sciences, University of Maryland [College Park], University of Maryland System-University of Maryland System, ICOS-ATC (ICOS-ATC), NOAA Pacific Marine Environmental Laboratory [Seattle] (PMEL), National Institute of Water and Atmospheric Research [Wellington] (NIWA), International Institute for Applied Systems Analysis [Laxenburg] (IIASA), Climatic Research Unit, Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), Commonwealth Scientific and Industrial Research Organisation (CSIRO), Woods Hole Oceanographic Institution (WHOI), Ocean Process Analysis Laboratory, University of New Hampshire (UNH), Department of Atmospheric Sciences [Urbana], University of Illinois at Urbana-Champaign [Urbana], University of Illinois System-University of Illinois System, The Institute of Applied Energy (IAE), Karlsruher Institut für Technologie (KIT), University of California [San Diego] (UC San Diego), University of California, PBL Netherlands Environmental Assessment Agency, Christian-Albrechts-Universität zu Kiel (CAU), Austral, Boréal et Carbone (ABC), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU), CISRO Oceans and Atmosphere, Antarctic Climate & Ecosystem Cooperative Research Centre, University of Tasmania [Hobart, Australia] (UTAS), Climate and Environmental Physics [Bern] (CEP), Physikalisches Institut [Bern], Universität Bern [Bern]-Universität Bern [Bern], Oeschger Centre for Climate Change Research (OCCR), University of Bern, National Center for Atmospheric Research [Boulder] (NCAR), Cycles biogéochimiques marins : processus et perturbations (CYBIOM), Department of Ocean Sciences, University of Miami [Coral Gables], Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento em Lisboa (INESC-ID), Instituto Superior Técnico, Universidade Técnica de Lisboa (IST)-Instituto de Engenharia de Sistemas e Computadores (INESC), University of Wisconsin Whitewater, National Institute for Environmental Studies (NIES), Montana State University (MSU), Max-Planck-Institut für Biogeochemie (MPI-BGC), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Shandong Agricultural University (SDAU), Antarctic Climate and Ecosystems Cooperative Research Centre (ACE-CRC), Wageningen University and Research [Wageningen] (WUR), Faculty of Earth and Life Sciences [Amsterdam] (FALW), Vrije Universiteit Amsterdam [Amsterdam] (VU), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), NASA Ames Research Center (ARC), Biogeochemical Systems Department [Jena], Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft-Max-Planck-Gesellschaft, Huazhong University of Science and Technology [Wuhan] (HUST), Environmental Sciences, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), University of California (UC), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Universität Bern [Bern] (UNIBE)-Universität Bern [Bern] (UNIBE), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), and Earth and Climate

Subjects
Meteorologie en Luchtkwaliteit, ENVIRONMENT SIMULATOR JULES, 010504 meteorology & atmospheric sciences, Epidemiology, Earth science, 010501 environmental sciences, Atmospheric sciences, 01 natural sciences, 7. Clean energy, FOSSIL-FUEL COMBUSTION, chemistry.chemical_compound, 11. Sustainability, ddc:550, Energy statistics, DIOXIDE EMISSIONS, lcsh:Environmental sciences, lcsh:GE1-350, EARTH SYSTEM MODEL, lcsh:QE1-996.5, VEGETATION MODEL, Biosphere, Carbon dioxide, Meteorology and Air Quality, Bioinformatica & Diermodellen, 530 Physics, MIXED-LAYER SCHEME, Earth and Planetary Sciences(all), chemistry.chemical_element, [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], INTERNATIONAL-TRADE, 12. Responsible consumption, Carbon cycle, ANTHROPOGENIC CO2 UPTAKE, Deforestation, Bio-informatics & Animal models, Life Science, Epidemiology, Bio-informatics & Animal models, SDG 14 - Life Below Water, ATMOSPHERIC CO2, 0105 earth and related environmental sciences, Epidemiologie, LAND-COVER CHANGE, WIMEK, business.industry, Fossil fuel, 15. Life on land, Earth system science, lcsh:Geology, Earth sciences, chemistry, 13. Climate action, Epidemiologie, Bioinformatica & Diermodellen, General Earth and Planetary Sciences, Environmental science, Physical geography, Sink (computing), business, Carbon
Abstract

44 pages, 9 tables, 9 figures.-- Corinne Le Quéré ... et al.-- This work is distributed under the Creative Commons Attribution 4.0 License, 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 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 high fossil emissions and the small SLAND consistent with El Niño conditions. The global atmospheric CO2 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 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 (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., 2016, 2015b, a, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017 (GCP, 2017)

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