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1. Changing cropland in changing climates: quantifying two decades of global cropland changes

Author

Jennifer Kennedy, George C Hurtt, Xin-Zhong Liang, Louise Chini, and Lei Ma

Subjects
land use change, climate change, agricultural adaptation, cropland conversion, Environmental technology. Sanitary engineering, TD1-1066, Environmental sciences, GE1-350, Science, Physics, QC1-999
Abstract

Climate change is impacting global crop productivity, and agricultural land suitability is predicted to significantly shift in the future. Responses to changing conditions and increasing yield variability can range from altered management strategies to outright land use conversions that may have significant environmental and socioeconomic ramifications. However, the extent to which agricultural land use changes in response to variations in climate is unclear at larger scales. Improved understanding of these dynamics is important since land use changes will have consequences not only for food security but also for ecosystem health, biodiversity, carbon storage, and regional and global climate. In this study, we combine land use products derived from the Moderate Resolution Imaging Spectroradiometer with climate reanalysis data from the European Centre for Medium-Range Weather Forecasts Reanalysis v5 to analyze correspondence between changes in cropland and changes in temperature and water availability from 2001 to 2018. While climate trends explained little of the variability in land cover changes, increasing temperature, extreme heat days, potential evaporation, and drought severity were associated with higher levels of cropland loss. These patterns were strongest in regions with more cropland change, and generally reflected underlying climate suitability—they were amplified in hotter and drier regions, and reversed direction in cooler and wetter regions. At national scales, climate response patterns varied significantly, reflecting the importance of socioeconomic, political, and geographic factors, as well as differences in adaptation strategies. This global-scale analysis does not attempt to explain local mechanisms of change but identifies climate-cropland patterns that exist in aggregate and may be hard to perceive at local scales. It is intended to supplement regional studies, providing further context for locally-observed phenomena and highlighting patterns that require further analysis.

Published
2023
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2. Harmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6

Author

George C. Hurtt, Louise Chini, Ritvik Sahajpal, Steve Frolking, Benjamin L. Bodirsky, Katherine Calvin, Jonathan C. Doelman, Justin Fisk, Shinichiro Fujimori, Kees Klein Goldewijk, Tomoko Hasegawa, Peter Havlik, Andreas Heinimann, Florian Humpenöder, Johan Jungclaus, Jed O. Kaplan, Jennifer Kennedy, Tamás Krisztin, David Lawrence, Peter Lawrence, Lei Ma, Ole Mertz, Julia Pongratz, Alexander Popp, Benjamin Poulter, Keywan Riahi, Elena Shevliakova, Elke Stehfest, Peter Thornton, Francesco N. Tubiello, Detlef P. van Vuuren, and Xin Zhang

Published
2020
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3. Spatial heterogeneity of global forest aboveground carbon stocks and fluxes constrained by spaceborne lidar data and mechanistic modeling

Author

Lei Ma, George Hurtt, Hao Tang, Rachel Lamb, Andrew Lister, Louise Chini, Ralph Dubayah, John Armston, Elliott Campbell, Laura Duncanson, Sean Healey, Jarlath O'Neil‐Dunne, Lesley Ott, Benjamin Poulter, and Quan Shen

Subjects
Global and Planetary Change, Ecology, Environmental Chemistry, General Environmental Science
Published
2023
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4. Pervasive shifts in forest dynamics in a changing world

Author

Nate G. McDowell, Craig D. Allen, Kristina Anderson-Teixeira, Brian H. Aukema, Ben Bond-Lamberty, Louise Chini, James S. Clark, Michael Dietze, Charlotte Grossiord, Adam Hanbury-Brown, George C. Hurtt, Robert B. Jackson, Daniel J. Johnson, Lara Kueppers, Jeremy W. Lichstein, Kiona Ogle, Benjamin Poulter, Thomas A. M. Pugh, Rupert Seidl, Monica G. Turner, Maria Uriarte, Anthony P. Walker, and Chonggang Xu

Subjects
Earth Resources And Remote Sensing
Abstract

Forest dynamics are the processes of recruitment, growth, death, and turnover of the constituent tree species of the forest community. These processes are driven by disturbances both natural and anthropogenic. McDowell et al. review recent progress in understanding the drivers of forest dynamics and how these are interacting and changing in the context of global climate change. The authors show that shifts in forest dynamics are already occurring, and the emerging pattern is that global forests are tending toward younger stands with faster turnover as old-growth forest with stable dynamics are dwindling.

Published
2020
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5. Importance of land cover scenarios in a low warming world

Author

Steven De Hertog, Felix Havermann, Suqi Guo, Julia Pongratz, Iris Manola, Fei Luo, Dim Coumou, Edouard Léopold Davin, Sonia Isabelle Seneviratne, Quentin Lejeune, Inga Menke, Carl-Friedrich Schleussner, Florian Humpenöder, Peter Lawrence, Louise Chini, George Hurtt, Wim Thiery, and Alexander Popp

Abstract

Land cover and land management changes (LCLMC) have often been highlighted as crucial regarding climate change, both for mitigation (e.g. afforestation) and adaptation (e.g. irrigation). In order to understand this role we present fully coupled Earth System Model (ESM) simulations using external forcing conditions from the SSP1-1.9 scenario, except for land cover and land management scenarios that follow differing trajectories. First we conduct a short 30-year historical simulation (histCTL) and a future (years 2015-2100) simulation under SSP1-1.9 conditions but with present day land cover kept at constant end of 2014 conditions (futCTL). These allow us to isolate climate changes in response to the SSP1-19 forcing, but in the absence of land cover changes. Secondly we conduct two simulations under SSP1-1.9 forcing, but with land cover and land management following two different trajectories. These trajectories are derived from the scenarios presented in Humpenöder et al. (2022) and represent two strongly diverging worlds with regard to socio-economic development, environmental protection, and land-based mitigation: (i) the future sustainability scenario (futSust) in which the land sector experiences sustainable development and application of mitigation strategies (such as greenhouse gas emission pricing) in all countries, (ii) the future inequality scenario (futIneq) in which these developments mostly happen in OECD countries, with the rest of the world continuing on current trends (including massive tropical deforestation). Each of these simulations have been run with three different ESMs (CESM, MPI-ESM and EC-EARTH) in order to identify how robust these results are over different ESMs.The results of these simulations can be used to increase our understanding of the role of land cover scenarios within a low-warming future as prescribed by the Paris agreement. We can compare the effects of all other forcings (futCTL- histCTL; CO2, aerosols etc.) to the effects of land cover changes in the different scenarios (futSust – futCTL or futIneq-futCTL) as well as to the difference between the future sustainability and the inequality narratives (futSust-futIneq). These results will be analysed for temperature and moisture fluxes, mainly focusing on warm and dry extremes and how land cover scenarios affect these. ReferencesHumpenöder, F., Popp, A., Schleussner, C. F., Orlov, A., Windisch, M. G., Menke, I., Pongratz, J., Havermann, F., Thiery, W., Luo, F., Jeetze, P. V., Philipp Dietrich, J., Lotze-Campen, H., Weindl, I. & Lejeune, Q. (2022). Overcoming global inequality is critical for land-based mitigation in line with the Paris Agreement. Nature Communications, 13(1), 1-15.

Published
2023
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6. Harmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6

Author

Hurtt, George C, Louise Chini, Ritvik Sahajpal, Steve Frolking, Benjamin L. Bodirsky, Katherine Calvin, and Jonathan C. Doelman

Abstract

Hurtt, George C., Louise Chini, Ritvik Sahajpal, Steve Frolking, Benjamin L. Bodirsky, Katherine Calvin, Jonathan C. Doelman, et al. 2020. ‘Harmonization of Global Land Use Change and Management for the Period 850–2100 (LUH2) for CMIP6’. Geoscientific Model Development 13 (11): 5425–64. https://doi.org/10.5194/gmd-13-5425-2020.

Published
2022

7. Global Carbon Budget 2021

Author

Nathalie Lefèvre, Thomas Gasser, Bronte Tilbrook, Glen P. Peters, Andy Wiltshire, Eddy Robertson, Frédéric Chevallier, George C. Hurtt, Michael O'Sullivan, Steve D Jones, Kees Klein Goldewijk, Robert B. Jackson, Yosuke Niwa, Benjamin Poulter, Andrew J. Watson, Jan Ivar Korsbakken, Gregor Rehder, T. Chau, Philippe Ciais, Christian Rödenbeck, J. G. Canadell, N. R. Bates, C. Wada, Judith Hauck, Colm Sweeney, Yosuke Iida, Giacomo Grassi, D. Gilfillan, R. Wanninkhof, Thais M. Rosan, Margot Cronin, J. Liu, Peter Anthoni, Robbie M. Andrew, C. Schwingshackl, X. Dou, Ian Harris, T. Ono, Siv K. Lauvset, David R. Willis, Thanos Gkritzalis, Laure Resplandy, C. Le Quéré, N. Vuichard, Gregg Marland, Matthew W. Jones, Richard A. Feely, Patrick C. McGuire, Xu Yue, Pieter P. Tans, Roland Séférian, Liang Feng, Peter Landschützer, Dorothee C. E. Bakker, Julia E. M. S. Nabel, Pierre Friedlingstein, Francesco N. Tubiello, O. Gürses, Sönke Zaehle, Denis Pierrot, G. R. van der Werf, Chao Yue, Arne Körtzinger, Sebastian Lienert, Nicolas Gruber, S. Nakaoka, Jürgen Knauer, D. Kennedy, Luke Gregor, Hanqin Tian, J. Zeng, Wouter Peters, L. Djeutchouang, B. Decharme, Richard A. Houghton, Wenping Yuan, Julia Pongratz, David R. Munro, Atul K. Jain, Joe R. Melton, Nicolas Bellouin, Etsushi Kato, Wiley Evans, Meike Becker, Jörg Schwinger, Toste Tanhua, Laurent Bopp, Tatiana Ilyina, Adrienne J. Sutton, Louise Chini, Kim I. Currie, Ingrid T. Luijkx, Stephen Sitch, and Simone R. Alin

Subjects
010504 meteorology & atmospheric sciences, 0207 environmental engineering, Biosphere, Biogeochemistry, 02 engineering and technology, 15. Life on land, Atmospheric sciences, 7. Clean energy, 01 natural sciences, Carbon cycle, Atmosphere, chemistry.chemical_compound, chemistry, 13. Climate action, Deforestation, Greenhouse gas, 11. Sustainability, Carbon dioxide, Environmental science, Sink (computing), 020701 environmental engineering, 0105 earth and related environmental sciences
Abstract

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from 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) is estimated with global ocean biogeochemistry models and observation-based data-products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. 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 first time, an approach is shown to reconcile the difference in our ELUC estimate with the one from national greenhouse gases inventories, supporting the assessment of collective countries’ climate progress. For the year 2020, EFOS declined by 5.4 % relative to 2019, with fossil emissions at 9.5 ± 0.5 GtC yr−1 (9.3 ± 0.5 GtC yr−1 when the cement carbonation sink is included), ELUC was 0.9 ± 0.7 GtC yr−1, for a total anthropogenic CO2 emission of 10.2 ± 0.8 GtC yr−1 (37.4 ± 2.9 GtCO2). Also, for 2020, GATM was 5.0 ± 0.2 GtC yr−1 (2.4 ± 0.1 ppm yr−1), SOCEAN was 3.0 ± 0.4 GtC yr−1 and SLAND was 2.9 ± 1 GtC yr−1, with a BIM of −0.8 GtC yr−1. The global atmospheric CO2 concentration averaged over 2020 reached 412.45 ± 0.1 ppm. Preliminary data for 2021, suggest a rebound in EFOS relative to 2020 of +4.9 % (4.1 % to 5.7 %) globally. Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2020, but discrepancies of up to 1 GtC yr−1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows: (1) a persistent large uncertainty in the estimate of land-use changes emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra- tropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Friedlingstein et al., 2020; Friedlingstein et al., 2019; Le Quéré et al., 2018b, 2018a, 2016, 2015b, 2015a, 2014, 2013). The data presented in this work are available at https://doi.org/10.18160/gcp-2021 (Friedlingstein et al., 2021).

Published
2022

8. Global evaluation of the Ecosystem Demography model (ED v3.0)

Author

S. Flanagan, Abhishek Chatterjee, Lesley Ott, Rachel L. Lamb, Hao Tang, George C. Hurtt, Justin Fisk, Joe H. Sullivan, Lei Ma, Louise Chini, and Ritvik Sahajpal

Subjects
Process (engineering), Primary production, Biogeochemistry, Environmental science, Ecosystem, Terrestrial ecosystem, Vegetation, Spatial distribution, Demography, Carbon cycle
Abstract

Terrestrial ecosystems play a critical role in the global carbon cycle but have highly uncertain future dynamics. Ecosystem modelling that includes the scaling-up of underlying mechanistic ecological processes has the potential to improve the accuracy of future projections, while retaining key process-level detail. Over the past two decades, multiple modelling advances have been made to meet this challenge, including the Ecosystem Demography (ED) model and its derivatives including ED2 and FATES. Here, we present the global evaluation of the Ecosystem Demography model (ED v3.0), which likes its predecessors features the formal scaling of physiological processes of individual-based vegetation dynamics to ecosystem scales, together with integrated submodules of soil biogeochemistry and soil hydrology, while retaining explicit tracking of vegetation 3-D structure. This new version builds on previous versions and provides the first global calibration and evaluation, global tracking of the effects of climate and land-use change on vegetation 3-D structure, new spin-up process and input datasets, as well as numerous other advances. Model evaluation was performed with respect to a set of important benchmarking datasets, and model estimates were within observational constraints for multiple key variables including: (i) global patterns of dominant plant functional types (broadleaf vs evergreen); (ii) spatial distribution, seasonal cycle, and interannual trends of global Gross Primary Production (GPP); (iii) global interannual variability of Net Biome Production (NBP); and (iv) global patterns of vertical structure including leaf area and canopy height. With this global model version, it is now possible to simulate vegetation dynamics from local to global scales and from seconds to centuries, with a consistent mechanistic modelling framework amendable to data from multiple traditional and new remote sensing sources, including lidar.

Published
2022

11. Net land-use change carbon flux estimates and sensitivities – An assessment with a bookkeeping model based on CMIP6 forcing

Author

Ana Bastos, George C. Hurtt, Felix Havermann, Tammas Loughran, Julia Pongratz, Raphael Ganzenmüller, Louise Chini, Tobias Nützel, Julia E. M. S. Nabel, Kerstin Hartung, and Wolfgang A. Obermeier

Subjects
Single model, Greenhouse gas, Range (statistics), Flux, Environmental science, Land use, land-use change and forestry, Forcing (mathematics), Atmospheric sciences, Baseline (configuration management), Carbon flux
Abstract

The carbon flux due to land-use and land-cover change (net LULCC flux) historically contributed to a large fraction of anthropogenic carbon emissions while at the same time being associated with large uncertainties. This study aims to compare the contribution of several sensitivities underlying the net LULCC flux by assessing their relative importance in a bookkeeping model (BLUE) based on a LULCC dataset including uncertainty estimates (the LUH2 dataset). The sensitivity experiments build upon the approach of Hurtt et al. (2011) and compare the impacts of LULCC uncertainty (a high, baseline and low land- use estimate), the starting time of the bookkeeping model simulation (850, 1700 and 1850), net area transitions versus gross area transitions (shifting cultivation) and neglecting wood harvest on estimates of the net LULCC flux. Additional factorial experiments isolate the impact of uncertainty from initial conditions and transitions on the net LULCC flux. Finally, historical simulations are extended with future land-use scenarios to assess the impact of past LULCC uncertainty in future projections. Over the period 1850–2014, baseline and low LULCC scenarios produce a comparable cumulative net LULCC flux while the high LULCC estimate initially produces a larger net LULCC flux which decreases towards the end of the period and even becomes smaller than in the baseline estimate. LULCC uncertainty leads to slightly higher sensitivity in the cumulative net LULCC flux (up to 22 %, reference are the baseline simulations) compared to the starting year of a model simulation (up to 15 %). The contribution from neglecting wood harvest activities (up to 28 % cumulative net LULCC flux) is larger than from LULCC uncertainty and the implementation of land-cover transitions (gross or net transitions) exhibits the smallest sensitivity (up to 13 %). At the end of the historical LULCC dataset in 2014, the LULCC uncertainty retains some impact on the net LULCC flux (±0.15 PgC yr−1 at an estimate of 1.7 PgC yr−1). Of the past uncertainties in LULCC, a small impact persists in 2099, mainly due to uncertainty of harvest remaining in 2014. However, compared to the uncertainty range of the LULCC flux estimated today, the estimates in 2099 appear to be indistinguishable. These results, albeit from a single model, are important for CMIP6 as they compare the relative importance of starting year, uncertainty of LULCC, applying gross transitions and wood harvest on the net LULCC flux. For the cumulative net LULCC flux over the industrial period the uncertainty of LULCC is as relevant as applying wood harvest and gross transitions. However, LULCC uncertainty matters less (by about a factor three) than the other two factors for the net LULCC flux in 2014 and historical LULCC uncertainty is negligible for estimates of future scenarios.

Published
2021
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12. Bookkeeping estimates of the net land-use change flux — a sensitivity study with the CMIP6 land-use dataset

Author

Ana Bastos, Julia Pongratz, Felix Havermann, George C. Hurtt, Tobias Nützel, Tammas Loughran, Wolfgang A. Obermeier, Kerstin Hartung, Raphael Ganzenmüller, Louise Chini, and Julia E. M. S. Nabel

Subjects
010504 meteorology & atmospheric sciences, Science, Flux, QE500-639.5, 010501 environmental sciences, Atmospheric sciences, 01 natural sciences, Range (statistics), Land use, land-use change and forestry, Sensitivity (control systems), Baseline (configuration management), CMIP6, 0105 earth and related environmental sciences, Unsicherheitsanalyse, QE1-996.5, Single model, Land use, Geology, 15. Life on land, Landnutzungesmissionen, Buchhaltungsmodell, Dynamic and structural geology, 13. Climate action, Greenhouse gas, General Earth and Planetary Sciences, Environmental science
Abstract

The carbon flux due to land-use and land-cover change (net LULCC flux) historically contributed to a large fraction of anthropogenic carbon emissions while at the same time being associated with large uncertainties. This study aims to compare the contribution of several sensitivities underlying the net LULCC flux by assessing their relative importance in a bookkeeping model (Bookkeeping of Land Use Emissions, BLUE) based on a LULCC dataset including uncertainty estimates (the Land-Use Harmonization 2 (LUH2) dataset). The sensitivity experiments build upon the approach of Hurtt et al. (2011) and compare the impacts of LULCC uncertainty (a high, baseline and low land-use estimate), the starting time of the bookkeeping model simulation (850, 1700 and 1850), net area transitions versus gross area transitions (shifting cultivation) and neglecting wood harvest on estimates of the net LULCC flux. Additional factorial experiments isolate the impact of uncertainty from initial conditions and transitions on the net LULCC flux. Finally, historical simulations are extended with future land-use scenarios to assess the impact of past LULCC uncertainty in future projections. Over the period 1850–2014, baseline and low LULCC scenarios produce a comparable cumulative net LULCC flux, while the high LULCC estimate initially produces a larger net LULCC flux which decreases towards the end of the period and even becomes smaller than in the baseline estimate. LULCC uncertainty leads to slightly higher sensitivity in the cumulative net LULCC flux (up to 22 %; references are the baseline simulations) compared to the starting year of a model simulation (up to 15 %). The contribution from neglecting wood harvest activities (up to 28 % cumulative net LULCC flux) is larger than that from LULCC uncertainty, and the implementation of land-cover transitions (gross or net transitions) exhibits the smallest sensitivity (up to 13 %). At the end of the historical LULCC dataset in 2014, the LULCC uncertainty retains some impact on the net LULCC flux (±0.15 PgC yr−1 at an estimate of 1.7 PgC yr−1). Of the past uncertainties in LULCC, a small impact persists in 2099, mainly due to uncertainty of harvest remaining in 2014. However, compared to the uncertainty range of the LULCC flux estimated today, the estimates in 2099 appear to be indistinguishable. These results, albeit from a single model, are important for CMIP6 as they compare the relative importance of starting year, uncertainty of LULCC, applying gross transitions and wood harvest on the net LULCC flux. For the cumulative net LULCC flux over the industrial period, the uncertainty of LULCC is as relevant as applying wood harvest and gross transitions. However, LULCC uncertainty matters less (by about a factor of 3) than the other two factors for the net LULCC flux in 2014, and historical LULCC uncertainty is negligible for estimates of future scenarios.

Published
2021

13. Global trends in biodiversity and ecosystem services from 1900 to 2050

Author

Aafke M. Schipper, Andrew J. Hoskins, F. Di Fulvio, Isabel M.D. Rosa, Haruka Ohashi, Richard Sharp, Kiyoshi Takahashi, Louise Chini, Petr Havlik, Shinichiro Fujimori, Simon Ferrier, Andreas Krause, Henrique M. Pereira, Justin A. Johnson, Andy Purvis, George C. Hurtt, Stefanie Hellweg, Vanessa Haverd, HyeJin Kim, Mike Harfoot, Matthew V. Talluto, Cory Merow, Josef Settele, Jan H. Janse, Alexander Popp, Akiko Hirata, Peter Anthoni, Wilfried Thuiller, M. Di Marco, Nicolas Titeux, Benjamin Poulter, Elke Stehfest, Paul Leadley, Piero Visconti, Carlo Rondinini, Rob Alkemade, Florian Humpenöder, David Leclère, Johan Meijer, Benjamin Quesada, Tomoko Hasegawa, Jelle P. Hilbers, B.N.B. Strassburg, Daniele Baisero, Carlos A. Guerra, Inês S. Martins, Tetsuya Matsui, Chris Ware, Samantha L. L. Hill, Almut Arneth, Tom Harwood, Rebecca Chaplin-Kramer, Michael Obersteiner, Florian Wolf, Walter Jetz, and D.P. van Vuuren

Subjects
Convention on Biological Diversity, Extinction, Geography, Natural resource economics, Sustainability, Biodiversity, Climate change, Scientific consensus, Ecosystem, Ecosystem services
Abstract

Despite the scientific consensus on the extinction crisis and its anthropogenic origin, the quantification of historical trends and of future scenarios of biodiversity and ecosystem services has been limited, due to the lack of inter-model comparisons and harmonized scenarios. Here, we present a multi-model analysis to assess the impacts of land-use and climate change from 1900 to 2050. During the 20th century provisioning services increased, but biodiversity and regulating services decreased. Similar trade-offs are projected for the coming decades, but they may be attenuated in a sustainability scenario. Future biodiversity loss from land-use change is projected to keep up with historical rates or reduce slightly, whereas losses due to climate change are projected to increase greatly. Renewed efforts are needed by governments to meet the 2050 vision of the Convention on Biological Diversity.One Sentence SummaryDevelopment pathways exist that allow for a reduction of the rates of biodiversity loss from land-use change and improvement in regulating services but climate change poses an increasing challenge.

Published
2020
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14. Quantifying the Effects of Historical Land Cover Conversion Uncertainty on Global Carbon and Climate Estimates

Author

Xiaoying Shi, William D. Collins, Jiafu Mao, George C. Hurtt, Louise Chini, and A. V. Di Vittorio

Subjects
geography, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, Land use, chemistry.chemical_element, Global change, Land cover, 010501 environmental sciences, Atmospheric sciences, 01 natural sciences, Shrubland, Earth system science, Geophysics, chemistry, General Earth and Planetary Sciences, Environmental science, Land use, land-use change and forestry, Earth system model, Carbon, 0105 earth and related environmental sciences
Abstract

Author(s): Di Vittorio, AV; Mao, J; Shi, X; Chini, L; Hurtt, G; Collins, WD | Abstract: Previous studies have examined land use change as a driver of global change, but the translation of land use change into land cover conversion has been largely unconstrained. Here we quantify the effects of land cover conversion uncertainty on the global carbon and climate system using the integrated Earth System Model. Our experiments use identical land use change data and vary land cover conversions to quantify associated uncertainty in carbon and climate estimates. Land cover conversion uncertainty is large, constitutes a 5nppmv range in estimated atmospheric CO2 in 2004, and generates carbon uncertainty that is equivalent to 80% of the net effects of CO2 and climate and 124% of the effects of nitrogen deposition during 1850–2004. Additionally, land cover uncertainty generates differences in local surface temperature of over 1°C. We conclude that future studies addressing land use, carbon, and climate need to constrain and reduce land cover conversion uncertainties.

Published
2018
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15. The PMIP4 contribution to CMIP6 – Part 3: The last millennium, scientific objective, and experimental design for the PMIP4 past1000 simulations

Author

Alexander Shapiro, Malte Meinshausen, Anders Moberg, Natalie A. Krivova, Andrew Schurer, Michael N. Evans, Sebastian Wagner, Gavin A. Schmidt, Steven J. Phipps, Matthew Toohey, Christoph Nehrbass-Ahles, Jason E. Smerdon, Edouard Bard, Hugues Goosse, Pascale Braconnot, Claudia Timmreck, Allegra N. LeGrande, Eugene Rozanov, George C. Hurtt, Hauke Schmidt, Myriam Khodri, Jed O. Kaplan, Raimund Muscheler, Amanda C. Maycock, Fortunat Joos, Bette I. Otto-Bliesner, Chi Ju Wu, Werner Schmutz, Jürg Luterbacher, T. Egorova, Jian Cao, Qiong Zhang, Sami K. Solanki, Kok Leng Yeo, Louise Chini, Eduardo Zorita, Mélanie Baroni, Michael Sigl, Julia Pongratz, Wenmin Man, Johann H. Jungclaus, Kees Klein Goldewijk, Davide Zanchettin, Stephan Lorenz, J. Fidel González-Rouco, and Ilya Usoskin

Subjects
Flexibility (engineering), Coupled model intercomparison project, Forcing (recursion theory), 010504 meteorology & atmospheric sciences, Meteorology, Collaborative model, Land cover, 01 natural sciences, Tier 1 network, 13. Climate action, Greenhouse gas, Climatology, Tier 2 network, 0103 physical sciences, 010303 astronomy & astrophysics, 0105 earth and related environmental sciences
Abstract

The pre-industrial millennium is among the periods selected by the Paleoclimate Model Intercomparison Project (PMIP) for experiments contributing to the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and the fourth phase of the PMIP (PMIP4). The past1000 transient simulations serve to investigate the response to (mainly) natural forcing under background conditions not too different from today, and to discriminate between forced and internally generated variability on interannual to centennial timescales. This paper describes the motivation and the experimental set-ups for the PMIP4-CMIP6 past1000 simulations, and discusses the forcing agents orbital, solar, volcanic, and land use/land cover changes, and variations in greenhouse gas concentrations. The past1000 simulations covering the pre-industrial millennium from 850 Common Era (CE) to 1849 CE have to be complemented by historical simulations (1850 to 2014 CE) following the CMIP6 protocol. The external forcings for the past1000 experiments have been adapted to provide a seamless transition across these time periods. Protocols for the past1000 simulations have been divided into three tiers. A default forcing data set has been defined for the Tier 1 (the CMIP6 past1000) experiment. However, the PMIP community has maintained the flexibility to conduct coordinated sensitivity experiments to explore uncertainty in forcing reconstructions as well as parameter uncertainty in dedicated Tier 2 simulations. Additional experiments (Tier 3) are defined to foster collaborative model experiments focusing on the early instrumental period and to extend the temporal range and the scope of the simulations. This paper outlines current and future research foci and common analyses for collaborative work between the PMIP and the observational communities (reconstructions, instrumental data).

Published
2017
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16. Biospheric feedback effects in a synchronously coupled model of human and Earth systems

Author

Peter E. Thornton, Alan Di Vittorio, Marcia L. Branstetter, Jiafu Mao, Jae Edmonds, George C. Hurtt, A. Craig, Allison M. Thomson, William D. Collins, J. E. Truesdale, Ben Bond-Lamberty, Katherine Calvin, Andrew D. Jones, Xiaoying Shi, and Louise Chini

Subjects
010504 meteorology & atmospheric sciences, Land use, Life on Land, Environmental Science and Management, Natural resource economics, business.industry, Biogeochemistry, 010501 environmental sciences, Environmental Science (miscellaneous), 01 natural sciences, Physical Geography and Environmental Geoscience, Atmospheric Sciences, Carbon cycle, Climate Action, Earth system science, Agriculture, Climatology, Environmental science, Climate model, Ecosystem, business, Productivity, Social Sciences (miscellaneous), 0105 earth and related environmental sciences
Abstract

Significant feedbacks in energy, agriculture, land use and the carbon cycle are identified for the twenty-first century when climate impacts on land are factored into climate projections so as to allow for two-way interactions between human and Earth systems. Fossil fuel combustion and land-use change are the two largest contributors to industrial-era increases in atmospheric CO2 concentration1. Projections of these are thus fundamental inputs for coupled Earth system models (ESMs) used to estimate the physical and biological consequences of future climate system forcing2,3. While historical data sets are available to inform past and current climate analyses4,5, assessments of future climate change have relied on projections of energy and land use from energy–economic models, constrained by assumptions about future policy, land-use patterns and socio-economic development trajectories6. Here we show that the climatic impacts on land ecosystems drive significant feedbacks in energy, agriculture, land use and carbon cycle projections for the twenty-first century. We find that exposure of human-appropriated land ecosystem productivity to biospheric change results in reductions of land area used for crops; increases in managed forest area and carbon stocks; decreases in global crop prices; and reduction in fossil fuel emissions for a low–mid-range forcing scenario7. The feedbacks between climate-induced biospheric change and human system forcings to the climate system—demonstrated here—are handled inconsistently, or excluded altogether, in the one-way asynchronous coupling of energy–economic models to ESMs used to date1,8,9.

Published
2017
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17. Pervasive shifts in forest dynamics in a changing world

Author

Thomas A. M. Pugh, Craig D. Allen, Adam Hanbury-Brown, Ben Bond-Lamberty, Jeremy W. Lichstein, Daniel J. Johnson, Rupert Seidl, Louise Chini, James S. Clark, Nate G. McDowell, Lara M. Kueppers, Anthony P. Walker, Kristina J. Anderson-Teixeira, Charlotte Grossiord, María Uriarte, Monica G. Turner, Brian H. Aukema, Michael Dietze, Benjamin Poulter, George C. Hurtt, Kiona Ogle, Chonggang Xu, and Robert B. Jackson

Subjects
0106 biological sciences, 010504 meteorology & atmospheric sciences, Acclimatization, Climate Change, Climate change, Forcing (mathematics), Forests, 010603 evolutionary biology, 01 natural sciences, Models, Biological, Trees, Biomass, 0105 earth and related environmental sciences, Biomass (ecology), Multidisciplinary, Land use, Forest dynamics, business.industry, Environmental resource management, Vegetation, 15. Life on land, Carbon Dioxide, Earth system science, Disturbance (ecology), 13. Climate action, Environmental science, business
Abstract

Shifting forest dynamics Forest dynamics are the processes of recruitment, growth, death, and turnover of the constituent tree species of the forest community. These processes are driven by disturbances both natural and anthropogenic. McDowell et al. review recent progress in understanding the drivers of forest dynamics and how these are interacting and changing in the context of global climate change. The authors show that shifts in forest dynamics are already occurring, and the emerging pattern is that global forests are tending toward younger stands with faster turnover as old-growth forest with stable dynamics are dwindling. Science , this issue p. eaaz9463

Published
2020
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18. Global Transition Rules for Translating Land-use Change (LUH2) To Land-cover Change for CMIP6 using GLM2

Author

Louise Chini, Ritvik Sahajpal, Steve Frolking, Julia Pongratz, George C. Hurtt, Lei Ma, Kees Klein Goldewijk, Donal O’ Leary, Jonathan C. Doelman, and Elke Stehfest

Subjects
Global transition, 010504 meteorology & atmospheric sciences, Selection rule, business.industry, Environmental resource management, Land cover, 010502 geochemistry & geophysics, 01 natural sciences, Earth system science, Remote sensing (archaeology), Environmental science, Land use, land-use change and forestry, business, 0105 earth and related environmental sciences
Abstract

Information on historical land-cover change is important for understanding human impacts on the environment. Over the last decade, global models have characterized historical land-use changes, but few have been able to relate these changes with corresponding changes in land-cover. Utilizing the latest global land-use change data, we make several assumptions about the relationship between land-use and land-cover change, and evaluate each scenario with remote sensing data to identify optimal fit. The resulting transition rule can guide the incorporation of land-cover information within earth system models.

Published
2019
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19. The integrated Earth system model version 1: formulation and functionality

Author

A. Craig, George C. Hurtt, Katherine Calvin, James A. Edmonds, Ben Bond-Lamberty, Xiaoying Shi, J. E. Truesdale, Jiafu Mao, William D. Collins, Andrew D. Jones, Allison M. Thomson, Peter E. Thornton, Yuyu Zhou, Louise Chini, Sonny Kim, A. V. Di Vittorio, and Pralit Patel

Subjects
Scientific instrument, Land use, Meteorology, business.industry, Life on Land, Scale (chemistry), Global warming, Environmental resource management, lcsh:QE1-996.5, Land cover, System dynamics, lcsh:Geology, Climate Action, Greenhouse gas, Earth Sciences, Environmental science, business, Common modeling infrastructure
Abstract

The integrated Earth system model (iESM) has been developed as a new tool for projecting the joint human/climate system. The iESM is based upon coupling an integrated assessment model (IAM) and an Earth system model (ESM) into a common modeling infrastructure. IAMs are the primary tool for describing the human–Earth system, including the sources of global greenhouse gases (GHGs) and short-lived species (SLS), land use and land cover change (LULCC), and other resource-related drivers of anthropogenic climate change. ESMs are the primary scientific tools for examining the physical, chemical, and biogeochemical impacts of human-induced changes to the climate system. The iESM project integrates the economic and human-dimension modeling of an IAM and a fully coupled ESM within a single simulation system while maintaining the separability of each model if needed. Both IAM and ESM codes are developed and used by large communities and have been extensively applied in recent national and international climate assessments. By introducing heretofore-omitted feedbacks between natural and societal drivers, we can improve scientific understanding of the human–Earth system dynamics. Potential applications include studies of the interactions and feedbacks leading to the timing, scale, and geographic distribution of emissions trajectories and other human influences, corresponding climate effects, and the subsequent impacts of a changing climate on human and natural systems. This paper describes the formulation, requirements, implementation, testing, and resulting functionality of the first version of the iESM released to the global climate community.

Published
2018
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20. Supplementary material to 'A protocol for an intercomparison of biodiversity and ecosystem services models using harmonized land-use and climate scenarios'

Author

HyeJin Kim, Isabel M. D. Rosa, Rob Alkemade, Paul Leadley, George Hurtt, Alexander Popp, Detlef P van Vuuren, Peter Anthoni, Almut Arneth, Daniele Baisero, Emma Caton, Rebecca Chaplin-Kramer, Louise Chini, Adriana De Palma, Fulvio Di Fulvio, Moreno Di Marco, Felipe Espinoza, Simon Ferrier, Shinichiro Fujimori, Ricardo E. Gonzalez, Maya Gueguen, Carlos Guerra, Mike Harfoot, Thomas D. Harwood, Tomoko Hasegawa, Vanessa Haverd, Petr Havlík, Stefanie Hellweg, Samantha L. L. Hill, Akiko Hirata, Andrew J. Hoskins, Jan H. Janse, Walter Jetz, Justin A. Johnson, Andreas Krause, David Leclère, Ines S. Martins, Tetsuya Matsui, Cory Merow, Michael Obersteiner, Haruka Ohashi, Benjamin Poulter, Andy Purvis, Benjamin Quesada, Carlo Rondinini, Aafke Schipper, Richard Sharp, Kiyoshi Takahashi, Wilfried Thuiller, Nicolas Titeux, Piero Visconti, Christopher Ware, Florian Wolf, and Henrique M. Pereira

Published
2018
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21. Future habitat loss and extinctions driven by land‐use change in biodiversity hotspots under four scenarios of climate‐change mitigation

Author

Jacob Noel, Thomas M. Brooks, Samuel M. Jantz, Rachel M. Moore, Brian Barker, Louise Chini, George C. Hurtt, and Qiongyu Huang

Subjects
Conservation of Natural Resources, Climate Change, Biodiversity, Climate change, Extinction, Biological, Animals, Land use, land-use change and forestry, Ecosystem, Ecology, Evolution, Behavior and Systematics, Nature and Landscape Conservation, 2. Zero hunger, Extinction, Ecology, business.industry, Environmental resource management, Plants, 15. Life on land, Invertebrates, Biodiversity hotspot, Climate change mitigation, Habitat destruction, 13. Climate action, Vertebrates, Environmental science, business, Global biodiversity
Abstract

Numerous species have been pushed into extinction as an increasing portion of Earth's land surface has been appropriated for human enterprise. In the future, global biodiversity will be affected by both climate change and land-use change, the latter of which is currently the primary driver of species extinctions. How societies address climate change will critically affect biodiversity because climate-change mitigation policies will reduce direct climate-change impacts; however, these policies will influence land-use decisions, which could have negative impacts on habitat for a substantial number of species. We assessed the potential impact future climate policy could have on the loss of habitable area in biodiversity hotspots due to associated land-use changes. We estimated past extinctions from historical land-use changes (1500-2005) based on the global gridded land-use data used for the Intergovernmental Panel on Climate Change Fifth Assessment Report and habitat extent and species data for each hotspot. We then estimated potential extinctions due to future land-use changes under alternative climate-change scenarios (2005-2100). Future land-use changes are projected to reduce natural vegetative cover by 26-58% in the hotspots. As a consequence, the number of additional species extinctions, relative to those already incurred between 1500 and 2005, due to land-use change by 2100 across all hotspots ranged from about 220 to 21000 (0.2% to 16%), depending on the climate-change mitigation scenario and biological factors such as the slope of the species-area relationship and the contribution of wood harvest to extinctions. These estimates of potential future extinctions were driven by land-use change only and likely would have been higher if the direct effects of climate change had been considered. Future extinctions could potentially be reduced by incorporating habitat preservation into scenario development to reduce projected future land-use changes in hotspots or by lessening the impact of future land-use activities on biodiversity within hotspots.La Futura Pérdida de Hábitat y Extinciones Causados por el Cambio en el Uso de Suelo en los Puntos Clave de Biodiversidad bajo Cuatro Escenarios de Mitigación de Cambio Climático Resumen Se ha llevado a numerosas especies a la extinción conforme una porción creciente de la superficie terrestre ha sido adueñada por actividades humanas. En el futuro, la biodiversidad global se verá afectada tanto por el cambio climático como por el cambio en el uso de suelo, de los cuales el último es actualmente el principal conductor de la extinción de especies. La manera en que las sociedades aborden el cambio climático afectará críticamente a la biodiversidad ya que las políticas de mitigación de cambio climático reducirán directamente los impactos del cambio climático; sin embargo, estas políticas influenciarán las decisiones de uso de suelo, lo que podría tener impactos negativos sobre el hábitat de numerosas especies. Evaluamos el impacto potencial que podrían tener las futuras políticas de clima sobre la pérdida del área habitable en los puntos clave de biodiversidad debido al cambio asociado en el uso de suelo. Estimamos las extinciones pasadas a partir de cambios históricos en el uso de suelo (1500 - 2005) con base en la extensión del hábitat, los datos de especies para cada punto clave, y la cuadrícula global de datos sobre uso de suelo, la cual fue utilizada para el Reporte de la Quinta Evaluación del Panel Intergubernamental sobre Cambio Climático. Después estimamos las extinciones potenciales causadas por futuros cambios en el uso de suelo bajo escenarios alternativos de cambio climático (2005 - 2100). El número de extinciones de especies adicionales, en relación con aquellas ya provocadas entre 1500 y 2005, causadas por el cambio en el uso de suelo para 2100 en todos los puntos clave, varió aproximadamente de 220 a 21, 000 (0.2% a 16%), dependiendo del escenario de mitigación de cambio climático y factores biológicos, como la pendiente de la relación especies-área y la contribución de la tala a las extinciones. Estas estimaciones de las extinciones potenciales en el futuro fueron causadas solamente por el cambio en el uso de suelo y probablemente habrían sido más altas si se hubiesen considerado los efectos directos del cambio climático. Las extinciones futuras podrían reducirse potencialmente al incorporar la preservación del hábitat al desarrollo del escenario para reducir los futuros cambios en el uso de suelo en los puntos clave o al disminuir el impacto de las futuras actividades de uso de suelo sobre la biodiversidad dentro de los puntos clave.

Published
2015
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22. Phosphorus in agricultural soils: drivers of its distribution at the global scale

Author

Louise Chini, Thomas Nesme, Sylvain Pellerin, Xiaojuan Yang, Laurent Augusto, Bertrand Decharme, David L. Achat, Bruno Ringeval, Kristof Van Oost, Hervé Monod, Lex Bouwman, Bertrand Guenet, Dirk van Apeldoorn, Rong Wang, Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Mathématiques et Informatique Appliquées du Génome à l'Environnement [Jouy-En-Josas] (MaIAGE), Institut National de la Recherche Agronomique (INRA), Utrecht University [Utrecht], Oak Ridge National Laboratory [Oak Ridge] (ORNL), UT-Battelle, LLC, Department of Geographical Sciences, University of Maryland [College Park], University of Maryland System-University of Maryland System, 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 des Surfaces et Interfaces Continentales (MOSAIC), 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), Peking Univ, Coll Urban & Environm Sci, Lab Earth Surface Proc, Beijing 100871, Peoples R China, 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), 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), Interactions Sol Plante Atmosphère (ISPA), Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS), Interactions Sol Plante Atmosphère ( ISPA ), Institut National de la Recherche Agronomique ( INRA ) -Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine ( Bordeaux Sciences Agro ), Mathématiques et Informatique Appliquées du Génome à l'Environnement [Jouy-En-Josas] ( MaIAGE ), Institut National de la Recherche Agronomique ( INRA ), Oak Ridge National Laboratory [Oak Ridge] ( ORNL ), UI-Battelle, University of Maryland, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] ( LSCE ), Université de Versailles Saint-Quentin-en-Yvelines ( UVSQ ) -Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Saclay-Centre National de la Recherche Scientifique ( CNRS ), Groupe d'étude de l'atmosphère météorologique ( CNRM-GAME ), and Institut national des sciences de l'Univers ( INSU - CNRS ) -Météo France-Centre National de la Recherche Scientifique ( CNRS )

Subjects
Crops, Agricultural, Agroecosystem, 010504 meteorology & atmospheric sciences, Soil science, Spatial distribution, 01 natural sciences, [ SDE ] Environmental Sciences, modelling, Soil, Agricultural land, Environmental Chemistry, Ecosystem, phosphorus, 0105 earth and related environmental sciences, General Environmental Science, 2. Zero hunger, Global and Planetary Change, Ecology, Biogeochemistry, Agriculture, Farm Systems Ecology Group, 04 agricultural and veterinary sciences, biogeochemical cycles, Plants, 15. Life on land, PE&RC, 13. Climate action, global scale, Soil water, [SDE]Environmental Sciences, 040103 agronomy & agriculture, Spatial ecology, 0401 agriculture, forestry, and fisheries, Environmental science, Water Systems and Global Change, Spatial variability, Physical geography, agricultural soils
Abstract

International audience; Phosphorus (P) availability in soils limits crop yields in many regions of the World, while excess of soil P triggers aquatic eutrophication in other regions. Numerous processes drive the global spatial distribution of P in agricultural soils, but their relative roles remain unclear. Here, we combined several global data sets describing these drivers with a soil P dynamics model to simulate the distribution of P in agricultural soils and to assess the contributions of the different drivers at the global scale. We analysed both the labile inorganic P (P ILAB), a proxy of the pool involved in plant nutrition and the total soil P (P TOT). We found that the soil biogeochemical background corresponding to P inherited from natural soils at the conversion to agriculture (BIOG) and farming practices (FARM) were the main drivers of the spatial variability in cropland soil P content but that their contribution varied between P TOT vs. P ILAB. When the spatial variability was computed between grid cells at half-degree resolution, we found that almost all of the P TOT spatial variability could be explained by BIOG, while BIOG and FARM explained 38% and 63% of P ILAB spatial variability, respectively. Our work also showed that the driver contribution was sensitive to the spatial scale characterizing the variability (grid cell vs. continent) and to the region of interest (global vs. tropics for instance). In particular, the heterogeneity of farming practices between continents was large enough to make FARM contribute to the variability in P TOT at that scale. We thus demonstrated how the different drivers were combined to explain the global distribution of agricultural soil P. Our study is also a promising approach to investigate the potential effect of P as a limiting factor for agroecosystems at the global scale.

Published
2017
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23. Global rules for translating land-use change (LUH2) to land-cover change for CMIP6 using GLM2

Author

D. O'Leary, Kees Klein Goldewijk, Jonathan C. Doelman, Elke Stehfest, Steve Frolking, Lei Ma, Ritvik Sahajpal, George C. Hurtt, Louise Chini, Julia Pongratz, and Environmental Sciences

Subjects
Biomass (ecology), geography, geography.geographical_feature_category, lcsh:QE1-996.5, Earth and Planetary Sciences(all), General Medicine, Land cover, Vegetation, Old-growth forest, lcsh:Geology, Greenhouse gas, Modelling and Simulation, Environmental science, Secondary forest, Climate model, Land use, land-use change and forestry, Physical geography
Abstract

Anthropogenic land-use and land-cover change activities play a critical role in Earth system dynamics through significant alterations to biogeophysical and biogeochemical properties at local to global scales. To quantify the magnitude of these impacts, climate models need consistent land-cover change time series at a global scale, based on land-use information from observations or dedicated land-use change models. However, a specific land-use change cannot be unambiguously mapped to a specific land-cover change. Here, nine translation rules are evaluated based on assumptions about the way land-use change could potentially impact land cover. Utilizing the Global Land-use Model 2 (GLM2), the model underlying the latest Land-Use Harmonization dataset (LUH2), the land-cover dynamics resulting from land-use change were simulated based on multiple alternative translation rules from 850 to 2015 globally. For each rule, the resulting forest cover, carbon density and carbon emissions were compared with independent estimates from remote sensing observations, U.N. Food and Agricultural Organization reports, and other studies. The translation rule previously suggested by the authors of the HYDE 3.2 dataset, that underlies LUH2, is consistent with the results of our examinations at global, country and grid scales. This rule recommends that for CMIP6 simulations, models should (1) completely clear vegetation in land-use changes from primary and secondary land (including both forested and non-forested) to cropland, urban land and managed pasture; (2) completely clear vegetation in land-use changes from primary forest and/or secondary forest to rangeland; (3) keep vegetation in land-use changes from primary non-forest and/or secondary non-forest to rangeland. Our analysis shows that this rule is one of three (out of nine) rules that produce comparable estimates of forest cover, vegetation carbon and emissions to independent estimates and also mitigate the anomalously high carbon emissions from land-use change observed in previous studies in the 1950s. According to the three translation rules, contemporary global forest area is estimated to be span classCombining double low line"inline-formula"37.42×106/span kmspan classCombining double low line"inline-formula"2/span, within the range derived from remote sensing products. Likewise, the estimated carbon stock is in close agreement with reference biomass datasets, particularly over regions with more than 50 % forest cover.

Published
2020
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24. From land use to land cover: restoring the afforestation signal in a coupled integrated assessment–earth system model and the implications for CMIP5 RCP simulations

Author

James A. Edmonds, J. E. Truesdale, Katherine Calvin, Louise Chini, Ben Bond-Lamberty, Xiaoying Shi, William D. Collins, Jiafu Mao, Peter E. Thornton, A. Craig, George C. Hurtt, A. V. Di Vittorio, Andrew D. Jones, and Allison M. Thomson

Subjects
Hydrology, Coupled model intercomparison project, Land use, lcsh:QE1-996.5, lcsh:Life, Climate change, Global change, Land cover, Earth system science, lcsh:Geology, lcsh:QH501-531, Climatology, lcsh:QH540-549.5, Environmental science, Afforestation, Land use, land-use change and forestry, lcsh:Ecology, Ecology, Evolution, Behavior and Systematics, Earth-Surface Processes
Abstract

Climate projections depend on scenarios of fossil fuel emissions and land use change, and the Intergovernmental Panel on Climate Change (IPCC) AR5 parallel process assumes consistent climate scenarios across integrated assessment and earth system models (IAMs and ESMs). The CMIP5 (Coupled Model Intercomparison Project Phase 5) project used a novel "land use harmonization" based on the Global Land use Model (GLM) to provide ESMs with consistent 1500–2100 land use trajectories generated by historical data and four IAMs. A direct coupling of the Global Change Assessment Model (GCAM), GLM, and the Community ESM (CESM) has allowed us to characterize and partially address a major gap in the CMIP5 land coupling design: the lack of a corresponding land cover harmonization. For RCP4.5, CESM global afforestation is only 22% of GCAM's 2005 to 2100 afforestation. Likewise, only 17% of GCAM's 2040 afforestation, and zero pasture loss, were transmitted to CESM within the directly coupled model. This is a problem because GCAM relied on afforestation to achieve RCP4.5 climate stabilization. GLM modifications and sharing forest area between GCAM and GLM within the directly coupled model did not increase CESM afforestation. Modifying the land use translator in addition to GLM, however, enabled CESM to include 66% of GCAM's afforestation in 2040, and 94% of GCAM's pasture loss as grassland and shrubland losses. This additional afforestation increases CESM vegetation carbon gain by 19 PgC and decreases atmospheric CO2 gain by 8 ppmv from 2005 to 2040, which demonstrates that CESM without additional afforestation simulates a different RCP4.5 scenario than prescribed by GCAM. Similar land cover inconsistencies exist in other CMIP5 model results, primarily because land cover information is not shared between models. Further work to harmonize land cover among models will be required to increase fidelity between IAM scenarios and ESM simulations and realize the full potential of scenario-based earth system simulations.

Published
2014

25. Global carbon budget 2013

Author

Bronte Tilbrook, Glen P. Peters, Andy Wiltshire, Abdirahman M Omar, Almut Arneth, A. Arvanitis, Joanna Isobel House, Richard A. Houghton, Pieter P. Tans, Benjamin D. Stocker, Josep G. Canadell, Nathalie Lefèvre, S. van Heuven, C. Le Quéré, Steve D Jones, Christian Rödenbeck, Pierre Regnier, R. Moriarty, T. Ono, Robbie M. Andrew, Stephen Sitch, Geun-Ha Park, Louise Chini, Atul K. Jain, Philippe Ciais, Fabienne Maignan, Anna B. Harper, Etsushi Kato, S. Saito, Benjamin Pfeil, Jörg Schwinger, Gregg Marland, Kees Klein Goldewijk, Michael R. Raupach, Ian Harris, Laurent Bopp, Thomas A. Boden, Arne Körtzinger, Sönke Zaehle, Nicolas Viovy, Dorothee C. E. Bakker, Pierre Friedlingstein, Rik Wanninkhof, Benjamin Poulter, Taro Takahashi, Joachim Segschneider, Scott C. Doney, Ralph F. Keeling, Robert J. Andres, Charles D. Koven, Tyndall Centre for Climate Change Research, University of East Anglia [Norwich] (UEA), 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), University of Exeter, Appalachian State University, University, Tyndall Centre for Climate Change Research and School of Environmental Sciences, College of Life and Environmental Sciences [Exeter], NOAA Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA), Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT), Climatic Research Unit, University of East Anglia, University of Illinois at Urbana-Champaign [Urbana], University of Illinois System, The Institute of Applied Energy (IAE), PBL Netherlands Environmental Assessment Agency, Leibniz-Institut für Meereswissenschaften (IFM-GEOMAR), Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research (UFZ), 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), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Netherlands Institute for Radio Astronomy (ASTRON), National Institute of Advanced Industrial Science and Technology (AIST), Chemistry Department [Massachusetts Institute of Technology], Massachusetts Institute of Technology (MIT), Université libre de Bruxelles (ULB), Max-Planck-Institut für Biogeochemie (MPI-BGC), Japan Meteorological Agency (JMA), Bjerknes Centre for Climate Research (BCCR), Department of Biological Sciences [Bergen] (BIO / UiB), University of Bergen (UiB)-University of Bergen (UiB), Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Centre for Isotope Research [Groningen] (CIO), University of Groningen [Groningen], NOAA Atlantic Oceanographic and Meteorological Laboratory (AOML), Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Max Planck Institute for Biogeochemistry (MPI-BGC), 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), 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), and 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))

Subjects
010504 meteorology & atmospheric sciences, 530 Physics, Mathematics and natural scienses: 400::Geosciences: 450::Meteorology: 453 [VDP], MODELS, Matematikk og naturvitenskap: 400::Geofag: 450::Oseanografi: 452 [VDP], Earth and Planetary Sciences(all), [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], 010501 environmental sciences, Atmospheric sciences, 7. Clean energy, 01 natural sciences, 12. Responsible consumption, Carbon cycle, Atmosphere, Matematikk og naturvitenskap: 400::Geofag: 450::Meteorologi: 453 [VDP], carbon budget, chemistry.chemical_compound, METHANE, carbon sinks, Mathematics and natural scienses: 400::Geosciences: 450::Oceanography: 452 [VDP], Deforestation, CARBON DIOXIDE, ddc:550, Climate change, fossil fuels, Energy statistics, Land use change, lcsh:Environmental sciences, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, lcsh:GE1-350, lcsh:QE1-996.5, Biosphere, Généralités, Vegetation, 15. Life on land, lcsh:Geology, Earth sciences, chemistry, 13. Climate action, Carbon dioxide, General Earth and Planetary Sciences, Environmental science, Sink (computing)
Abstract

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the 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, 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 (G ATM) 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 for the first time in this budget 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). 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 (2003-2012), EFF was 8.6±0.4 GtC yr-1, ELUC 0.9±0.5 GtC yr-1, GATM 4.3±0.1 GtC yr-1, SOCEAN 2.5±0.5 GtC yr -1, and SLAND 2.8±0.8 GtC yr-1. For year 2012 alone, EFF grew to 9.7±0.5 GtC yr-1, 2.2% above 2011, reflecting a continued growing trend in these emissions, G ATM was 5.1±0.2 GtC yr-1, SOCEAN was 2.9±0.5 GtC yr-1, and assuming an ELUC of 1.0±0.5 GtC yr-1 (based on the 2001-2010 average), S LAND was 2.7±0.9 GtC yr-1. GATM was high in 2012 compared to the 2003-2012 average, almost entirely reflecting the high EFF. The global atmospheric CO2 concentration reached 392.52±0.10 ppm averaged over 2012. We estimate that EFF will increase by 2.1% (1.1- 3.1 %) to 9.9±0.5 GtC in 2013, 61% above emissions in 1990, based on projections of world gross domestic product and recent changes in the carbon intensity of the economy.With this projection, cumulative emissions ofCO2 will reach about 535±55 GtC for 1870-2013, about 70% from EFF (390±20 GtC) and 30% from ELUC (145±50 GtC). This paper also documents any changes in the methods and data sets used in this new carbon budget from previous budgets (Le Quéré et al. 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP-2013-V2.3). © 2014 Author(s) CC Attribution 3.0 License., 0, SCOPUS: ar.j, info:eu-repo/semantics/published

Published
2014
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26. High-Resolution Global Maps of 21st-Century Forest Cover Change

Author

John R. Townshend, M. Hancher, Rebecca Moore, Thomas R. Loveland, Svetlana Turubanova, Matthew C. Hansen, A. Egorov, Scott J. Goetz, Anil Kommareddy, Christopher O. Justice, Alexandra Tyukavina, David Thau, Peter Potapov, Stephen V. Stehman, and Louise Chini

Subjects
Multidisciplinary, Ecology, Deforestation, Taiga, Forest ecology, Deforestation and climate change, Square (unit), Tropics, Subtropics, Physical geography, Forest transition
Abstract

Forests in Flux Forests worldwide are in a state of flux, with accelerating losses in some regions and gains in others. Hansen et al. (p. 850 ) examined global Landsat data at a 30-meter spatial resolution to characterize forest extent, loss, and gain from 2000 to 2012. Globally, 2.3 million square kilometers of forest were lost during the 12-year study period and 0.8 million square kilometers of new forest were gained. The tropics exhibited both the greatest losses and the greatest gains (through regrowth and plantation), with losses outstripping gains.

Published
2013
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27. Greenhouse Gas Policy Influences Climate via Direct Effects of Land-Use Change

Author

James A. Edmonds, Margaret S. Torn, Peter E. Thornton, Marshall Wise, Andrew D. Jones, Xiaoying Shi, George C. Hurtt, Louise Chini, Katherine Calvin, William D. Collins, Allison M. Thomson, Anthony C. Janetos, and Jiafu Mao

Subjects
Atmospheric Science, Coupled model intercomparison project, Climatology, Greenhouse gas, Environmental science, Climate change, Representative Concentration Pathways, Climate model, Land use, land-use change and forestry, Global change, Radiative forcing
Abstract

Proposed climate mitigation measures do not account for direct biophysical climate impacts of land-use change (LUC), nor do the stabilization targets modeled for phase 5 of the Coupled Model Intercomparison Project (CMIP5) representative concentration pathways (RCPs). To examine the significance of such effects on global and regional patterns of climate change, a baseline and an alternative scenario of future anthropogenic activity are simulated within the Integrated Earth System Model, which couples the Global Change Assessment Model, Global Land-Use Model, and Community Earth System Model. The alternative scenario has high biofuel utilization and approximately 50% less global forest cover than the baseline, standard RCP4.5 scenario. Both scenarios stabilize radiative forcing from atmospheric constituents at 4.5 W m−2 by 2100. Thus, differences between their climate predictions quantify the biophysical effects of LUC. Offline radiative transfer and land model simulations are also utilized to identify forcing and feedback mechanisms driving the coupled response. Boreal deforestation is found to strongly influence climate because of increased albedo coupled with a regional-scale water vapor feedback. Globally, the alternative scenario yields a twenty-first-century warming trend that is 0.5°C cooler than baseline, driven by a 1 W m−2 mean decrease in radiative forcing that is distributed unevenly around the globe. Some regions are cooler in the alternative scenario than in 2005. These results demonstrate that neither climate change nor actual radiative forcing is uniquely related to atmospheric forcing targets such as those found in the RCPs but rather depend on particulars of the socioeconomic pathways followed to meet each target.

Published
2013
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28. Historical carbon dioxide emissions caused by land-use changes are possibly larger than assumed

Author

Benjamin Poulter, Anita D. Bayer, Nicolas Viovy, Leonardo Calle, Almut Arneth, Benjamin D. Stocker, Thomas Gasser, Wenyu Li, Chao Yue, Julia E. M. S. Nabel, Pierre Friedlingstein, Eddy Robertson, Mats Lindeskog, Etsushi Kato, Alberte Bondeau, Stephen Sitch, Marianela Fader, Louise Chini, Julia Pongratz, Thomas A. M. Pugh, Philippe Ciais, Sönke Zaehle, Karlsruhe Institute of Technology (KIT), College of Life and Environmental Sciences [Exeter], University of Exeter, Department of Global Ecology [Carnegie] (DGE), Carnegie Institution for Science [Washington], Imperial College London, 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), Montana State University (MSU), Karlsruher Institut für Technologie (KIT), Institut méditerranéen de biodiversité et d'écologie marine et continentale (IMBE), Avignon Université (AU)-Aix Marseille Université (AMU)-Institut de recherche pour le développement [IRD] : UMR237-Centre National de la Recherche Scientifique (CNRS), NASA Goddard Space Flight Center (GSFC), Department of Geographical Sciences, University of Maryland [College Park], University of Maryland System-University of Maryland System, Institute of Applied Energy (IAE), Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Lancaster Environment Centre, Lancaster University, Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Max-Planck-Institut für Biogeochemie (MPI-BGC), Carnegie Institution for Science, 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), and Centre National de la Recherche Scientifique (CNRS)-Institut de recherche pour le développement [IRD] : UMR237-Aix Marseille Université (AMU)-Avignon Université (AU)

Subjects
geography, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, Land management, Climate change, Carbon sink, Soil science, 010501 environmental sciences, 15. Life on land, Carbon sequestration, Atmospheric sciences, Dynamic global vegetation model, 01 natural sciences, Sink (geography), Carbon cycle, 13. Climate action, [SDU.STU.GC]Sciences of the Universe [physics]/Earth Sciences/Geochemistry, [SDE]Environmental Sciences, General Earth and Planetary Sciences, Environmental science, Terrestrial ecosystem, 0105 earth and related environmental sciences
Abstract

The terrestrial biosphere absorbs about 20% of fossil-fuel CO2 emissions. The overall magnitude of this sink is constrained bythe difference between emissions, the rate of increase in atmospheric CO2 concentrations, and the ocean sink. However, theland sink is actually composed of two largely counteracting fluxes that are poorly quantified: fluxes from land-use change andCO2 uptake by terrestrial ecosystems. Dynamic global vegetation model simulations suggest that CO2 emissions from land-usechange have been substantially underestimated because processes such as tree harvesting and land clearing from shifting cultivationhave not been considered. As the overall terrestrial sink is constrained, a larger net flux as a result of land-use changeimplies that terrestrial uptake of CO2 is also larger, and that terrestrial ecosystems might have greater potential to sequestercarbon in the future. Consequently, reforestation projects and efforts to avoid further deforestation could represent importantmitigation pathways, with co-benefits for biodiversity. It is unclear whether a larger land carbon sink can be reconciled with ourcurrent understanding of terrestrial carbon cycling. Our possible underestimation of the historical residual terrestrial carbonsink adds further uncertainty to our capacity to predict the future of terrestrial carbon uptake and losses

Published
2017
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29. A global view of shifting cultivation: Recent, current, and future extent

Author

Stephen E. Frolking, Matthew C. Hansen, Ritvik Sahajpal, George C. Hurtt, Andreas Egelund Christensen, Ole Mertz, Andrew Heinimann, Kaspar Hurni, Fernando Sedano, and Louise Chini

Subjects
Satellite Imagery, 010504 meteorology & atmospheric sciences, lcsh:Medicine, Datasets as Topic, Social Sciences, Surveys, 010501 environmental sciences, 01 natural sciences, Geographical Locations, Database and Informatics Methods, Shifting cultivation, Land Use, Greenhouse gas accounting, Database Searching, 910 Geography & travel, lcsh:Science, 2. Zero hunger, Multidisciplinary, Geography, Ecology, Environmental resource management, Agriculture, 330 Economics, Research Design, Research Article, Conservation of Natural Resources, Asia, Land cover, Environment, Human Geography, Research and Analysis Methods, Spatio-Temporal Analysis, Deforestation, 0105 earth and related environmental sciences, Survey Research, Land use, business.industry, lcsh:R, Reproducibility of Results, Biology and Life Sciences, South America, 15. Life on land, Earth system science, Physical Geography, 13. Climate action, Greenhouse gas, People and Places, Africa, Earth Sciences, lcsh:Q, business, Earth Systems
Abstract

Mosaic landscapes under shifting cultivation, with their dynamic mix of managed and natural land covers, often fall through the cracks in remote sensing-based land cover and land use classifications, as these are unable to adequately capture such landscapes' dynamic nature and complex spectral and spatial signatures. But information about such landscapes is urgently needed to improve the outcomes of global earth system modelling and large-scale carbon and greenhouse gas accounting. This study combines existing global Landsat-based deforestation data covering the years 2000 to 2014 with very high-resolution satellite imagery to visually detect the specific spatio-temporal pattern of shifting cultivation at a one-degree cell resolution worldwide. The accuracy levels of our classification were high with an overall accuracy above 87%. We estimate the current global extent of shifting cultivation and compare it to other current global mapping endeavors as well as results of literature searches. Based on an expert survey, we make a first attempt at estimating past trends as well as possible future trends in the global distribution of shifting cultivation until the end of the 21st century. With 62% of the investigated one-degree cells in the humid and sub-humid tropics currently showing signs of shifting cultivation-the majority in the Americas (41%) and Africa (37%)-this form of cultivation remains widespread, and it would be wrong to speak of its general global demise in the last decades. We estimate that shifting cultivation landscapes currently cover roughly 280 million hectares worldwide, including both cultivated fields and fallows. While only an approximation, this estimate is clearly smaller than the areas mentioned in the literature which range up to 1,000 million hectares. Based on our expert survey and historical trends we estimate a possible strong decrease in shifting cultivation over the next decades, raising issues of livelihood security and resilience among people currently depending on shifting cultivation.

Published
2017
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30. The PMIP4 contribution to CMIP6 – Part 3: the Last Millennium, Scientific Objective and Experimental Design for the PMIP4 past1000 simulations

Author

Gavin A. Schmidt, Alexander Shapiro, Claudia Timmreck, Malte Meinshausen, Jesús Fidel González-Rouco, Myriam Khodri, Natalie A. Krivova, George C. Hurtt, Qiang Zhang, Edouard Bard, Hugues Goosse, Juerg Luterbacher, Stephan Lorenz, Andrew Schurer, Sami K. Solanki, Louise Chini, Matthew Toohey, Wenmin Man, Michael N. Evans, Johann H. Jungclaus, Kees Klein Goldewijk, Michael Sigl, Hauke Schmidt, Bette I. Otto-Bliesner, T. Egorova, Werner Schmutz, Allegra N. LeGrande, Pascale Braconnot, Ilya Usoskin, Anders Moberg, Jed O. Kaplan, E. Zorita, Mélanie Baroni, Sebastian Wagner, Steven J. Phipps, Fortunat Joos, Julia Pongratz, Davide Zanchettin, C.-Y. Wu, Jason E. Smerdon, Christoph Nehrbass-Ahles, Kok Leng Yeo, Jian Cao, and Eugene Rozanov

Subjects
0301 basic medicine, 03 medical and health sciences, 030104 developmental biology, 010504 meteorology & atmospheric sciences, Environmental science, 01 natural sciences, 0105 earth and related environmental sciences
Abstract

The pre-industrial millennium is among the periods selected by the Paleoclimate Model Intercomparison Project (PMIP) for experiments contributing to the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and the fourth phase of PMIP (PMIP4). The past1000 transient simulations serve to investigate the response to (mainly) natural forcing under background conditions not too different from today, and to discriminate between forced and internally generated variability on interannual to centennial time scales. This manuscript describes the motivation and the experimental set-ups for the PMIP4-CMIP6 past1000 simulations, and discusses the forcing agents: orbital, solar, volcanic, land-use/land-cover changes, and variations in greenhouse gas concentrations. The past1000 simulations covering the pre-industrial millennium from 850 Common Era (CE) to 1849 CE have to be complemented by historical simulations (1850 to 2014 CE) following the CMIP6 protocol. The external forcings for the past1000 experiments have been adapted to provide a seamless transition across these time periods. Protocols for the past1000 simulations have been divided into three tiers. A default forcing data set has been defined for the “tier-1” (the CMIP6 past1000) experiment. However, the PMIP community has maintained the flexibility to conduct coordinated sensitivity experiments to explore uncertainty in forcing reconstructions as well as parameter uncertainty in dedicated “tier-2” simulations. Additional experiments (“tier-3”) are defined to foster collaborative model experiments focusing on the early instrumental period and to extend the temporal range and the scope of the simulations. This manuscript outlines current and future research foci and common analyses for collaborative work between the PMIP and the observational communities (reconstructions, instrumental data).

Published
2016
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31. 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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32. Harmonization of land-use scenarios for the period 1500–2100: 600 years of global gridded annual land-use transitions, wood harvest, and resulting secondary lands

Author

Ying-Ping Wang, Steven J. Smith, Richard Betts, Kees Klein Goldewijk, Johannes J. Feddema, Günther Fischer, Steve Frolking, Peter E. Thornton, J. Fisk, Louise Chini, D.P. van Vuuren, Tsuguki Kinoshita, Georg Kindermann, George C. Hurtt, Allison M. Thomson, Elena Shevliakova, Kathy Hibbard, Richard A. Houghton, Keywan Riahi, Anthony C. Janetos, Chris D. Jones, and Elke Stehfest

Subjects
Atmospheric Science, Global and Planetary Change, Land use, business.industry, Environmental resource management, International community, Climate change, Harmonization, Earth system science, Shifting cultivation, Climatology, Environmental science, business, Implementation
Abstract

In preparation for the fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), the international community is developing new advanced Earth System Models (ESMs) to assess the combined effects of human activities (e. g. land use and fossil fuel emissions) on the carbon-climate system. In addition, four Representative Concentration Pathway (RCP) scenarios of the future (2005-2100) are being provided by four Integrated Assessment Model (IAM) teams to be used as input to the ESMs for future carbon-climate projections (Moss et al. 2010). The diversity of approaches and requirements among IAMs and ESMs for tracking land-use change, along with the dependence of model projections on land-use history, presents a challenge for effectively passing data between these communities and for smoothly transitioning from the historical estimates to future projections. Here, a harmonized set of land-use scenarios are presented that smoothly connects historical reconstructions of land use with future projections, in the format required by ESMs. The land-use harmonization strategy estimates fractional land-use patterns and underlying land-use transitions annually for the time period 1500-2100 at 0.5° × 0.5° resolution. Inputs include new gridded historical maps of crop and pasture data from HYDE 3.1 for 1500-2005, updated estimates of historical national wood harvest and of shifting cultivation, and future information on crop, pasture, and wood harvest from the IAM implementations of the RCPs for the period 2005-2100. The computational method integrates these multiple data sources, while minimizing differences at the transition between the historical reconstruction ending conditions and IAM initial conditions, and working to preserve the future changes depicted by the IAMs at the grid cell level. This study for the first time harmonizes land-use history data together with future scenario information from multiple IAMs into a single consistent, spatially gridded, set of land-use change scenarios for studies of human impacts on the past, present, and future Earth system. © 2011 The Author(s).

Published
2011
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33. Climate mitigation and the future of tropical landscapes

Author

Anthony C. Janetos, Benjamin Bond-Lamberty, Steve Frolking, George C. Hurtt, Marshall Wise, Louise Chini, James A. Edmonds, Allison M. Thomson, and Katherine Calvin

Subjects
Tropical Climate, Multidisciplinary, Agroforestry, Natural resource economics, Climate Change, Global warming, Land management, Conservation of Energy Resources, Climate change, Agriculture, Carbon Dioxide, Models, Theoretical, Zea mays, Deforestation, Biofuels, Climate Mitigation and Food Production in Tropical Landscapes Special Feature, Greenhouse gas, Environmental science, Land use, land-use change and forestry, Agricultural productivity, Productivity
Abstract

Land-use change to meet 21st-century demands for food, fuel, and fiber will depend on many interactive factors, including global policies limiting anthropogenic climate change and realized improvements in agricultural productivity. Climate-change mitigation policies will alter the decision-making environment for land management, and changes in agricultural productivity will influence cultivated land expansion. We explore to what extent future increases in agricultural productivity might offset conversion of tropical forest lands to crop lands under a climate mitigation policy and a contrasting no-policy scenario in a global integrated assessment model. The Global Change Assessment Model is applied here to simulate a mitigation policy that stabilizes radiative forcing at 4.5 W m −2 (approximately 526 ppm CO 2 ) in the year 2100 by introducing a price for all greenhouse gas emissions, including those from land use. These scenarios are simulated with several cases of future agricultural productivity growth rates and the results downscaled to produce gridded maps of potential land-use change. We find that tropical forests are preserved near their present-day extent, and bioenergy crops emerge as an effective mitigation option, only in cases in which a climate mitigation policy that includes an economic price for land-use emissions is in place, and in which agricultural productivity growth continues throughout the century. We find that idealized land-use emissions price assumptions are most effective at limiting deforestation, even when cropland area must increase to meet future food demand. These findings emphasize the importance of accounting for feedbacks from land-use change emissions in global climate change mitigation strategies.

Published
2010
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34. Global carbon budget 2014

Author

Joanna Isobel House, Roland Séférian, Stephen Sitch, Robbie M. Andrew, C. Cosca, Jörg Schwinger, Thomas A. Boden, Truls Johannessen, Michael R. Raupach, Pieter P. Tans, Nicolas Metzl, Jeremy T. Mathis, Ying-Ping Wang, R. Moriarty, G. R. van der Werf, Christian Rödenbeck, Peter Landschützer, Ute Schuster, Benjamin D. Stocker, Benjamin Poulter, Taro Takahashi, Kees Klein Goldewijk, Joachim Segschneider, Philippe Ciais, Almut Arneth, Andrew Lenton, Pierre Friedlingstein, Frédéric Chevallier, Laurent Bopp, C. Le Quéré, Etsushi Kato, Wouter Peters, Atul K. Jain, Camilla S. Landa, T. Ono, Ning Zeng, Charles D. Koven, Ralph F. Keeling, Yann Bozec, Joe Salisbury, Ivan D. Lima, Yukihiro Nojiri, Are Olsen, Steve D Jones, Shushi Peng, Mario Hoppema, Richard A. Houghton, Tobias Steinhoff, Bronte Tilbrook, Glen P. Peters, S. Saito, Benjamin Pfeil, Andy Wiltshire, Adrienne J. Sutton, Louise Chini, Josep G. Canadell, Vassilis Kitidis, Ian Harris, Pierre Regnier, Gregg Marland, Nicolas Viovy, Rik Wanninkhof, 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), 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), Karlsruhe Institute of Technology (KIT), College of Life and Environmental Sciences [Exeter], University of Exeter, NOAA Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA), Oak Ridge National Laboratory [Oak Ridge] (ORNL), UT-Battelle, LLC, CHImie Marine (CHIM), Adaptation et diversité en milieu marin (AD2M), Station biologique de Roscoff [Roscoff] (SBR), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Station biologique de Roscoff [Roscoff] (SBR), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Global Carbon Project, CSIRO Marine and Atmospheric Research, Department of Geographical Sciences, University of Maryland [College Park], University of Maryland System-University of Maryland System, Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), NOAA Pacific Marine Environmental Laboratory [Seattle] (PMEL), Climatic Research Unit, University of East Anglia, Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), Woods Hole Oceanographic Institution (WHOI), University of Bristol [Bristol], Department of Atmospheric Sciences [Urbana], University of Illinois at Urbana-Champaign [Urbana], University of Illinois System-University of Illinois System, Geophysical Institute [Bergen] (GFI / BiU), University of Bergen (UiB), Bjerknes Centre for Climate Research (BCCR), Department of Biological Sciences [Bergen] (BIO / UiB), University of Bergen (UiB)-University of Bergen (UiB), Institute of Applied Energy (IAE), Earth Science Division [LBNL Berkeley] (ESD), Lawrence Berkeley National Laboratory [Berkeley] (LBNL), Plymouth Marine Laboratory (PML), Plymouth Marine Laboratory, PBL Netherlands Environmental Assessment Agency, Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research (UFZ), Institute of Biogeochemistry and Pollutant Dynamics [ETH Zürich] (IBP), Department of Environmental Systems Science [ETH Zürich] (D-USYS), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich)- Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Oceans and Atmosphere Flagship (CSIRO), CSIRO Oceans and Atmosphere Flagship, Appalachian State University, University, Équipe CO2 (E-CO2), 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), Institute of Cancer Epidemiology, Danish Cancer Society, National Institute of Advanced Industrial Science and Technology (AIST), Swedish Defence Research Agency [Stockholm] (FOI), Meteorology and Air Quality Department [Wageningen] (MAQ), Wageningen University and Research [Wageningen] (WUR), Montana State University (MSU), Australian National University (ANU), Université libre de Bruxelles (ULB), Max-Planck-Institut für Biogeochemie (MPI-BGC), Japan Meteorological Agency (JMA), University of New Hampshire (UNH), Météo-France [Paris], Météo France, Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Helmholtz Centre for Ocean Research [Kiel] (GEOMAR), Imperial College London, Oeschger Centre for Climate Change Research (OCCR), University of Bern, Joint Institute for the Study of the Atmosphere and Ocean (JISAO), University of Washington [Seattle], Department of Mechanical Science and Engineering, Nagoya University, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Faculty of Earth and Life Sciences [Amsterdam] (FALW), Vrije Universiteit Amsterdam [Amsterdam] (VU), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), NOAA Atlantic Oceanographic and Meteorological Laboratory (AOML), Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Department of Atmospheric and Oceanic Science [College Park] (AOSC), Earth and Climate, Amsterdam Global Change Institute, 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), 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)), and Météo-France

Subjects
Meteorologie en Luchtkwaliteit, ENVIRONMENT SIMULATOR JULES, 010504 meteorology & atmospheric sciences, earth system model, environment simulator jules, 010501 environmental sciences, 01 natural sciences, land-use change, chemistry.chemical_compound, ComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATION, ddc:550, SDG 13 - Climate Action, Land use, land-use change and forestry, DIOXIDE EMISSIONS, lcsh:Environmental sciences, lcsh:GE1-350, EARTH SYSTEM MODEL, lcsh:QE1-996.5, Biosphere, terrestrial ecosystems, Vegetation, LAND-USE CHANGE, FLUX VARIABILITY, Climatology, Carbon dioxide, INTERANNUAL VARIABILITY, FIRE EMISSIONS, international-trade, Meteorology and Air Quality, 530 Physics, interannual variability, Climate change, co2 flux variability, [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], Carbon cycle, Latitude, ANTHROPOGENIC CO2 UPTAKE, Deforestation, Mathematics and natural scienses: 400::Zoology and botany: 480::Ecology: 488 [VDP], TheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITY, SDG 14 - Life Below Water, ATMOSPHERIC CO2, 0105 earth and related environmental sciences, atmospheric co2, WIMEK, Généralités, 15. Life on land, dioxide emissions, TERRESTRIAL ECOSYSTEMS, lcsh:Geology, Earth sciences, mixed-layer scheme, chemistry, 13. Climate action, General Earth and Planetary Sciences, Environmental science, Matematikk og naturvitenskap: 400::Zoologiske og botaniske fag: 480::Økologi: 488 [VDP], MathematicsofComputing_DISCRETEMATHEMATICS
Abstract

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the 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)., 0, SCOPUS: ar.j, info:eu-repo/semantics/published

Published
2015
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35. Terrestrial and Inland Water Systems

Author

Thomas Hickler, Dieter Gerten, Paulo M. Brando, Rita Adrian, Stephen Sitch, Carlo Rondinini, Piero Visconti, Craig D. Allen, Nicola Golding, Patrick Gonzalez, Scott J. Goetz, Céline Bellard, Robert J. Scholes, Klement Tockner, Paul Leadley, William R. L. Anderegg, Franck Courchamp, Josef Settele, Daniel C. Nepstad, Jonathan T. Overpeck, Georgina M. Mace, Beatriz Rodríguez-Labajos, Richard G. Pearson, Marten Winter, Camille Parmesan, Ed Hawkins, Rebecca Shaw, Wendy Foden, George C. Hurtt, Stuart E. Bunn, Miguel Angel Taboada, Louise Chini, Melodie A. McGeoch, Richard Betts, Heike Lischke, Josh Lawler, and Charles D. Koven

Subjects
Aquatic ecosystem, Greenhouse gas, Climate change, Environmental science, Tropics, Land use, land-use change and forestry, Terrestrial ecosystem, Ecosystem, Physical geography, Civil engineering, Southern Hemisphere
Abstract

The topics assessed in this chapter were last assessed by the IPCC in 2007, principally in WGII AR4 Chapters 3 (Kundzewicz et al., 2007) and 4 (Fischlin et al., 2007), but also in WGII AR4 Sections 1.3.4 and 1.3.5 (Rosenzweig et al., 2007). The WGII AR4 SPM stated “Observational evidence from all continents and most oceans shows that many natural systems are being affected by regional climate changes, particularly temperature increases,” though they noted that documentation of observed changes in tropical regions and the Southern Hemisphere was sparse (Rosenzweig et al., 2007). Fischlin et al. (2007) found that 20 to 30% of the plant and animal species that had been assessed to that time were considered to be at increased risk of extinction if the global average temperature increase exceeds 2°C to 3°C above the preindustrial level with medium confidence, and that substantial changes in structure and functioning of terrestrial, marine, and other aquatic ecosystems are very likely under that degree of warming and associated atmospheric CO2 concentration. No time scale was associated with these findings. The carbon stocks in terrestrial ecosystems were considered to be at high risk from climate change and land use change. The report warned that the capacity of ecosystems to adapt naturally to the combined effect of climate change and other stressors is likely to be exceeded if greenhouse gas (GHG) emission continued at or above the then-current rate.

Published
2015
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36. Global Carbon Budget 2015

Author

Douglas Vandemark, Robert J. Andres, Charles D. Koven, Christian Rödenbeck, Benjamin Poulter, Taro Takahashi, Leticia Barbero, Yukihiro Nojiri, Fiz F. Pérez, Judith Hauck, Jörg Schwinger, S. Nakaoka, Ralph F. Keeling, Etsushi Kato, Gregor Rehder, Pieter P. Tans, Aki Murata, Thanos Gkritzalis, C. Le Quéré, Nathalie Lefèvre, Julia E. M. S. Nabel, R. Moriarty, T. Ono, Laurent Bopp, Tatiana Ilyina, Jinfeng Chang, Thomas A. Boden, Joanna Isobel House, Jan Ivar Korsbakken, Roland Séférian, Atul K. Jain, Marianela Fader, Frank J. Millero, S. van Heuven, Philippe Ciais, Are Olsen, Adrienne J. Sutton, Richard A. Houghton, Louise Chini, Robbie M. Andrew, Denis Pierrot, Tobias Steinhoff, David R. Munro, Nicolas Metzl, Richard A. Feely, Peter Landschützer, Dorothee C. E. Bakker, Pierre Friedlingstein, I. T. van der Laan-Luijkx, Siv K. Lauvset, Kees Klein Goldewijk, Ute Schuster, Benjamin D. Stocker, Andrew Lenton, Ian Harris, Vassilis Kitidis, Stephen Sitch, Ning Zeng, Bronte Tilbrook, Glen P. Peters, S. Saito, Benjamin Pfeil, Andy Wiltshire, Sönke Zaehle, Ivan D. Lima, Karen O'Brien, Almut Arneth, Frédéric Chevallier, G. R. van der Werf, Nicolas Viovy, Josep G. Canadell, Natural Environment Research Council (UK), Norwegian Research Council, European Commission, Department of Energy (US), Helmholtz Association, Leverhulme Trust, Department of Energy and Climate Change (UK), European Research Council, National Aeronautics and Space Administration (US), Department for Environment, Food and Rural Affairs (UK), Department of Commerce (US), National Science Foundation (US), Ministry of Environment (Japan), Institut national des sciences de l'Univers (France), Institut Polaire Français Paul Emile Victor, German Research Foundation, Gobierno de España, Bundesministerium für Bildung und Forschung, European Space Agency, Research Council of Norway, Swiss National Science Foundation, National Energy Research Scientific Computing Center (US), Scripps Institution of Oceanography (US), Leerstoel Ridder, Environmental Sciences, Sub Algemeen Math. Inst, 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), Oceans and Atmosphere Research, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), College of Life and Environmental Sciences [Exeter], University of Exeter, Exeter Climate Systems, College of Engineering, Mathematics and Physical Science, University of Exeter, Exeter, United Kingdom, Carbon Dioxide Information Analysis Center [Oak Ridge] (CDIAC), U.S. Department of Energy [Washington] (DOE), Woods Hole Oceanographic Institution (WHOI), University of Bristol [Bristol], Scripps Institution of Oceanography (SIO), University of California [San Diego] (UC San Diego), University of California-University of California, NOAA Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA), Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT), Rosenstiel School of Marine and Atmospheric Science (RSMAS), 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), Institut méditerranéen de biodiversité et d'écologie marine et continentale (IMBE), Centre National de la Recherche Scientifique (CNRS)-Institut de recherche pour le développement [IRD] : UMR237-Aix Marseille Université (AMU)-Avignon Université (AU), NOAA Pacific Marine Environmental Laboratory [Seattle] (PMEL), Flanders Marine Institute, VLIZ, Climatic Research Unit [Norwich] (CRU), Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, 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), Plymouth Marine Laboratory (PML), Plymouth Marine Laboratory, PBL Netherlands Environmental Assessment Agency, Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research (UFZ), Institute of Applied Energy (IAE), Institute of Biogeochemistry and Pollutant Dynamics [ETH Zürich] (IBP), Department of Environmental Systems Science [ETH Zürich] (D-USYS), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich)- Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), 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), 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, Department of Atmospheric and Oceanic Sciences [Boulder] (ATOC), University of Colorado [Boulder], Institute of Arctic and Alpine Research (INSTAAR), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), National Institute for Environmental Studies (NIES), National Institute of Advanced Industrial Science and Technology (AIST), Instituto de Investigaciones Marinas, Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Cooperative Institute for Marine and Atmospheric Studies (CIMAS), University of Miami [Coral Gables]-University of Miami [Coral Gables], Max-Planck-Institut für Biogeochemie (MPI-BGC), Japan Meteorological Agency (JMA), Météo-France [Paris], Météo France, Helmholtz Centre for Ocean Research [Kiel] (GEOMAR), Imperial College London, Joint Institute for the Study of the Atmosphere and Ocean (JISAO), University of Washington [Seattle], Lamont-Doherty Earth Observatory (LDEO), Columbia University [New York], Wageningen University and Research [Wageningen] (WUR), Faculty of Earth and Life Sciences [Amsterdam] (FALW), Vrije Universiteit Amsterdam [Amsterdam] (VU), Centre for Isotope Research [Groningen] (CIO), University of Groningen [Groningen], Ocean Process Analysis Laboratory, University of New Hampshire (UNH), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Max Planck Institute for Biogeochemistry (MPI-BGC), Department of Atmospheric and Oceanic Science [College Park] (AOSC), European Project: 603542,EC:FP7:ENV,FP7-ENV-2013-two-stage,LUC4C(2013), European Project: 282672,EC:FP7:ENV,FP7-ENV-2011,EMBRACE(2011), European Project: 264879,EC:FP7:ENV,FP7-ENV-2010,CARBOCHANGE(2011), Scripps Institution of Oceanography (SIO - UC San Diego), University of California (UC)-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), Avignon Université (AU)-Aix Marseille Université (AMU)-Institut de recherche pour le développement [IRD] : UMR237-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)), Institute of Arctic Alpine Research [University of Colorado Boulder] (INSTAAR), Météo-France, Earth and Climate, and Geology and Geochemistry

Subjects
Meteorologie en Luchtkwaliteit, ENVIRONMENT SIMULATOR JULES, 010504 meteorology & atmospheric sciences, 010501 environmental sciences, Atmospheric sciences, 7. Clean energy, 01 natural sciences, Physical Geography and Environmental Geoscience, chemistry.chemical_compound, FOSSIL-FUEL COMBUSTION, CO2 FLUX VARIABILITY, SDG 13 - Climate Action, Meteorology & Atmospheric Sciences, Geosciences, Multidisciplinary, DIOXIDE EMISSIONS, lcsh:Environmental sciences, lcsh:GE1-350, EARTH SYSTEM MODEL, lcsh:QE1-996.5, Biosphere, Geology, Vegetation, LAND-USE CHANGE, COVER CHANGE, Carbon dioxide, Physical Sciences, INTERANNUAL VARIABILITY, Meteorology and Air Quality, Life on Land, MIXED-LAYER SCHEME, Climate change, [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], 12. Responsible consumption, Carbon cycle, Latitude, Atmospheric Sciences, Atmosphere, Deforestation, Life Science, SDG 14 - Life Below Water, ATMOSPHERIC CO2, 0105 earth and related environmental sciences, Science & Technology, WIMEK, 15. Life on land, Climate Action, lcsh:Geology, Geochemistry, chemistry, 13. Climate action, General Earth and Planetary Sciences, Environmental science
Abstract

48 pages, 9 figures, 10 tables.-- Proyecto Carbochange, 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 as well as 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, 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 (2005–2014), EFF was 9.0 ± 0.5 GtC yr−1, ELUC was 0.9 ± 0.5 GtC yr−1, GATM was 4.4 ± 0.1 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1, and SLAND was 3.0 ± 0.8 GtC yr−1. For the year 2014 alone, EFF grew to 9.8 ± 0.5 GtC yr−1, 0.6 % above 2013, continuing the growth trend in these emissions, albeit at a slower rate compared to the average growth of 2.2 % yr−1 that took place during 2005–2014. Also, for 2014, ELUC was 1.1 ± 0.5 GtC yr−1, GATM was 3.9 ± 0.2 GtC yr−1, SOCEAN was 2.9 ± 0.5 GtC yr−1, and SLAND was 4.1 ± 0.9 GtC yr−1. GATM was lower in 2014 compared to the past decade (2005–2014), reflecting a larger SLAND for that year. The global atmospheric CO2 concentration reached 397.15 ± 0.10 ppm averaged over 2014. For 2015, preliminary data indicate that the growth in EFF will be near or slightly below zero, with a projection of −0.6 [range of −1.6 to +0.5] %, based on national emissions projections for China and the USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the global economy for the rest of the world. From this projection of EFF and assumed constant ELUC for 2015, cumulative emissions of CO2 will reach about 555 ± 55 GtC (2035 ± 205 GtCO2) for 1870–2015, 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., 2015, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2015)., NERC provided funding to C. Le Quéré, R. Moriarty, and the GCP through their International Opportunities Fund specifically to support this publication (NE/103002X/1). G. P. Peters and R. M. Andrew were supported by the Norwegian Research Council (236296). J. G. Canadell was supported by the Australian Climate Change Science Programme. S. Sitch was supported by EU FP7 for funding through projects LUC4C (GA603542). R. J. Andres was supported by US Department of Energy, Office of Science, Biological and Environmental Research (BER) programmes under US Department of Energy contract DE-AC05- 00OR22725. 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 DE-AC05-00OR22725.J. I. House was supported by the Leverhulme foundation and the EU FP7 through project LUC4C (GA603542). P. Friedlingstein was supported by the EU FP7 for funding through projects LUC4C (GA603542) and EMBRACE (GA282672). A. Arneth was supported by the EU FP7 for funding through LUC4C (603542), and the Helmholtz foundation and its ATMO programme. D. C. E. Bakker was supported by the EU FP7 for funding through project CARBOCHANGE (284879), the UK Ocean Acidification Research Programme (NE/H017046/1; funded by the Natural Environment Research Council, the Department for Energy and Climate Change and the Department for Environment, Food and Rural Affairs). L. Barbero was supported by NOAA’s Ocean Acidification Program and acknowledges support for this work from the National Aeronautics and Space Administration (NASA) ROSES Carbon Cycle Science under NASA grant 13-CARBON13_2-0080. P. Ciais acknowledges support from the European Research Council through Synergy grant ERC-2013-SyG-610028 “IMBALANCE-P”. M. Fader was supported by the EU FP7 for funding through project LUC4C (GA603542). J. Hauck was supported by the Helmholtz Postdoc Programme (Initiative and Networking Fund of the Helmholtz Association). R. A. Feely and A. J. Sutton were supported by the Climate Observation Division, Climate Program Office, NOAA, US Department of Commerce. 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 NASA LCLUC programme (NASA NNX14AD94G). E. Kato was supported by the ERTDF (S-10) from the Ministry of Environment, Japan. K. Klein Goldewijk was supported by the Dutch NWO VENI grant no. 863.14.022. S. K. Lauvset was supported by the project “Monitoring ocean acidification in Norwegian waters” from the Norwegian Ministry of Climate and Environment. V. Kitidis was supported by the EU FP7 for funding through project CARBOCHANGE (264879). 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. P. Landschützer was supported by GEOCarbon. I. T. van der Lann-Luijkx received financial support from OCW/NWO for ICOS-NL and computing time from NWO (SH-060-13). I. D. Lima was supported by the US 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. D. R. Munro was supported by the US National Science Foundation (NSF PLR-1341647 and NSF AOAS-0944761). J. E. M. S. Nabel was supported by the German Research Foundation’s Emmy Noether Programme (PO1751/1-1) and acknowledges Julia Pongratz and Kim Naudts for their contributions. Y. Nojiri and S. Nakaoka were supported by the Global Environment Research Account for National Institutes (1432) by the Ministry of Environment of Japan. A. Olsen appreciates support from the Norwegian Research Council (SNACS, 229752). F. F. Pérez were supported by BOCATS (CTM2013-41048-P) project co-founded by the Spanish government and the Fondo Europeo de Desarrollo Regional (FEDER). B. Pfeil was supported through the European Union’s Horizon 2020 research and innovation programme AtlantOS under grant agreement no. 633211. D. Pierrot was supported by NOAA through the Climate Observation Division of the Climate Program Office. B. Poulter was supported by the EU FP7 for funding through GEOCarbon. G. Rehder was supported by BMBF (Bundesministerium für Bildung und Forschung) through project ICOS, grant no. 01LK1224D. U. Schuster was supported by NERC UKOARP (NE/H017046/1), NERC RAGANRoCC (NE/K002473/1), the European Space Agency (ESA) OceanFlux Evolution project, and EU FP7 CARBOCHANGE (264879). T. Steinhoff was supported by ICOS-D (BMBF FK 01LK1101C) and EU FP7 for funding through project CARBOCHANGE (264879). J. Schwinger was supported by the Research Council of Norway through project EVA (229771). T. Takahashi was supported by grants from NOAA and the Comer Education and Science Foundation. B. Tilbrook was supported by the Australian Department of Environment and the Integrated Marine Observing System. B. D. Stocker was supported by the Swiss National Science Foundation and FP7 funding through project EMBRACE (282672). S. van Heuven was supported by the EU FP7 for funding through project CARBOCHANGE (264879). G. R. van der Werf was supported by the European Research Council (280061). A. Wiltshire was supported by the Joint UK DECC/Defra Met Office Hadley Centre Climate Programme (GA01101) and EU FP7 Funding through project LUC4C (603542). S. Zaehle was supported by the European Research Council (ERC) under the Eu ropean Union’s Horizon 2020 research and innovation programme (QUINCY; grant agreement no. 647204). ISAM (PI: Atul K. Jain) simulations were carried out at the National Energy Research Scientific Computing Center (NERSC), which is supported by the US DOE under contract DE-AC02-05CH11231. Contributions from the Scripps Institution of Oceanography were supported under DoE grant DE-SC0012167 and by Schmidt Philanthropies. This is NOAA-PMEL contribution number 4400

Published
2015
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37. Effect of Anthropogenic Land-Use and Land-Cover Changes on Climate and Land Carbon Storage in CMIP5 Projections for the Twenty-First Century

Author

F. Pacifico, Lena Boysen, M. Weiss, Martin Claussen, Etsushi Kato, Juan Pablo Boisier, Julia Pongratz, Vivek K. Arora, Victor Brovkin, Pierre Friedlingstein, Patricia Cadule, C. D. Jones, Louise Chini, George C. Hurtt, B. J. J. M. van den Hurk, Veronika Gayler, N. de Noblet-Ducoudré, 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), Extrèmes : Statistiques, Impacts et Régionalisation (ESTIMR), 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
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Atmospheric Science, Coupled model intercomparison project, 010504 meteorology & atmospheric sciences, Land use, 0207 environmental engineering, Climate change, 02 engineering and technology, Land cover, Forcing (mathematics), Subtropics, 15. Life on land, 01 natural sciences, 7. Clean energy, Carbon cycle, 13. Climate action, Agricultural land, Climatology, Environmental science, 020701 environmental engineering, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, 0105 earth and related environmental sciences
Abstract

The effects of land-use changes on climate are assessed using specified-concentration simulations complementary to the representative concentration pathway 2.6 (RCP2.6) and RCP8.5 scenarios performed for phase 5 of the Coupled Model Intercomparison Project (CMIP5). This analysis focuses on differences in climate and land–atmosphere fluxes between the ensemble averages of simulations with and without land-use changes by the end of the twenty-first century. Even though common land-use scenarios are used, the areas of crops and pastures are specific for each Earth system model (ESM). This is due to different interpretations of land-use classes. The analysis reveals that fossil fuel forcing dominates land-use forcing. In addition, the effects of land-use changes are globally not significant, whereas they are significant for regions with land-use changes exceeding 10%. For these regions, three out of six participating models—the Second Generation Canadian Earth System Model (CanESM2); Hadley Centre Global Environmental Model, version 2 (Earth System) (HadGEM2-ES); and Model for Interdisciplinary Research on Climate, Earth System Model (MIROC-ESM)—reveal statistically significant changes in mean annual surface air temperature. In addition, changes in land surface albedo, available energy, and latent heat fluxes are small but significant for most ESMs in regions affected by land-use changes. These climatic effects are relatively small, as land-use changes in the RCP2.6 and RCP8.5 scenarios are small in magnitude and mainly limited to tropical and subtropical regions. The relative importance of the climatic effects of land-use changes is higher for the RCP2.6 scenario, which considers an expansion of biofuel croplands as a climate mitigation option. The underlying similarity among all models is the loss in global land carbon storage due to land-use changes.

Published
2013
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38. Scenarios for global biodiversity in the 21st century

Author

Patricia Balvanera, H. David Cooper, Paul Leadley, Louise Chini, Matt Walpole, Eric Gilman, Thierry Oberdorff, Miguel B. Araújo, Rob Alkemade, William W. L. Cheung, Carmen Revenga, Sylvie Guénette, Henrique M. Pereira, Joern P. W. Scharlemann, Robert J. Scholes, Reinette Biggs, Henry P. Huntington, Ussif Rashid Sumaila, Vania Proenca, Georgina M. Mace, Patrícia Rodrigues, Juan F. Fernández-Manjarrés, and George C. Hurtt

Subjects
0106 biological sciences, Aquatic Organisms, 010504 meteorology & atmospheric sciences, Population Dynamics, distributions, vulnerability, Biodiversity, 01 natural sciences, Ecosystem services, extinctions, Natural resource management, marine ecosystems, Multidisciplinary, Environmental resource management, MILIEU CONTINENTAL, Plants, changing climate, Policy, Geography, Milieusysteemanalyse, climate-change, IMPACT SUR L'ENVIRONNEMENT, future, Conservation of Natural Resources, STRUCTURE DU PEUPLEMENT, Climate change, Extinction, Biological, Models, Biological, 010603 evolutionary biology, ABONDANCE, FACTEUR ANTHROPIQUE, range shifts, MODELE, models, ESPECE MENACEE, POPULATION ANIMALE, land-use, Animals, Ecosystem, 14. Life underwater, 0105 earth and related environmental sciences, WIMEK, Land use, business.industry, BIODIVERSITE, 15. Life on land, Environmental Systems Analysis, Habitat destruction, CHANGEMENT CLIMATIQUE, MILIEU MARIN, business, EAU DOUCE, Forecasting, Global biodiversity
Abstract

Assessing Biodiversity Declines Understanding human impact on biodiversity depends on sound quantitative projection. Pereira et al. (p. 1496 , published online 26 October) review quantitative scenarios that have been developed for four main areas of concern: species extinctions, species abundances and community structure, habitat loss and degradation, and shifts in the distribution of species and biomes. Declines in biodiversity are projected for the whole of the 21st century in all scenarios, but with a wide range of variation. Hoffmann et al. (p. 1503 , published online 26 October) draw on the results of five decades' worth of data collection, managed by the International Union for Conservation of Nature Species Survival Commission. A comprehensive synthesis of the conservation status of the world's vertebrates, based on an analysis of 25,780 species (approximately half of total vertebrate diversity), is presented: Approximately 20% of all vertebrate species are at risk of extinction in the wild, and 11% of threatened birds and 17% of threatened mammals have moved closer to extinction over time. Despite these trends, overall declines would have been significantly worse in the absence of conservation actions.

Published
2010

39. 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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