Author: "Julia Pongratz" / Topic: 15. life on land - Searchworks@Jio Institute Digital Library Search Results

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1. Slowdown of the greening trend in natural vegetation with further rise in atmospheric CO2

Author: Ranga B. Myneni, Stephen Sitch, Almut Arneth, Atul K. Jain, Victor Brovkin, Etsushi Kato, Sönke Zaehle, Pierre Friedlingstein, Alexander J. Winkler, Julia E. M. S. Nabel, Hanqin Tian, Danica Lombardozzi, Vivek K. Arora, Alexis Hannart, Daniel S. Goll, Vanessa Haverd, Julia Pongratz, Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Boston University [Boston] (BU), Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET), University of Exeter, CSIRO Oceans and Atmosphere, CISRO Oceans and Atmosphere, National Center for Atmospheric Research [Boulder] (NCAR), Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, Ludwig-Maximilians-Universität München (LMU), 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), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), 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)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), 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 Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)
Subjects: 0303 health sciences, 010504 meteorology & atmospheric sciences, Biome, Climate change, Carbon sink, Vegetation, 15. Life on land, 01 natural sciences, 03 medical and health sciences, Greening, [SDU]Sciences of the Universe [physics], 13. Climate action, Effects of global warming, Greenhouse gas, Environmental science, Ecosystem, Physical geography, Ecology, Evolution, Behavior and Systematics, 030304 developmental biology, 0105 earth and related environmental sciences, Earth-Surface Processes
Abstract: Satellite data reveal widespread changes in Earth's vegetation cover. Regions intensively attended to by humans are mostly greening due to land management. Natural vegetation, on the other hand, is exhibiting patterns of both greening and browning in all continents. Factors linked to anthropogenic carbon emissions, such as CO2 fertilization, climate change, and consequent disturbances such as fires and droughts, are hypothesized to be key drivers of changes in natural vegetation. A rigorous regional attribution at the biome level that can be scaled to a global picture of what is behind the observed changes is currently lacking. Here we analyze different datasets of decades-long satellite observations of global leaf area index (LAI, 1981–2017) as well as other proxies for vegetation changes and identify several clusters of significant long-term changes. Using process-based model simulations (Earth system and land surface models), we disentangle the effects of anthropogenic carbon emissions on LAI in a probabilistic setting applying causal counterfactual theory. The analysis prominently indicates the effects of climate change on many biomes – warming in northern ecosystems (greening) and rainfall anomalies in tropical biomes (browning). The probabilistic attribution method clearly identifies the CO2 fertilization effect as the dominant driver in only two biomes, the temperate forests and cool grasslands, challenging the view of a dominant global-scale effect. Altogether, our analysis reveals a slowing down of greening and strengthening of browning trends, particularly in the last 2 decades. Most models substantially underestimate the emerging vegetation browning, especially in the tropical rainforests. Leaf area loss in these productive ecosystems could be an early indicator of a slowdown in the terrestrial carbon sink. Models need to account for this effect to realize plausible climate projections of the 21st century.
Published: 2021

2. Modelled land use and land cover change emissions – a spatio-temporal comparison of different approaches

Author: Michael O. Sullivan, Almut Arneth, Peter Anthoni, Felix Havermann, Sebastian Lienert, A. Wiltshire, Sebastiaan Luyssaert, Daniel S. Goll, Soenke Zaehle, Stephen Sitch, Ana Bastos, Danica Lombardozzi, Julia Pongratz, Joe R. Melton, Anthony P. Walker, Wolfgang A. Obermeier, Tammas Loughran, Kerstin Hartung, Hanqin Tian, Patrick C. McGuire, Benjamin Poulter, Julia E. M. S. Nabel, Ludwig-Maximilians-Universität München (LMU), Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Max Planck Institute for Biogeochemistry (MPI-BGC), 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), Systems Ecology, 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: 010504 meteorology & atmospheric sciences, 530 Physics, Science, QE500-639.5, Land cover, Forcing (mathematics), 010501 environmental sciences, Atmospheric sciences, 01 natural sciences, Carbon cycle, Agricultural land, Deforestation, Modellvergleichsstudie, 550 Earth sciences & geology, ddc:550, Landnutzungsemissionen, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, SDG 15 - Life on Land, 0105 earth and related environmental sciences, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, QE1-996.5, Land use, Geology, Vegetation, 15. Life on land, Dynamic and structural geology, dynamische Vegetationsmodelle, Earth sciences, Climate change mitigation, 13. Climate action, General Earth and Planetary Sciences, Environmental science
Abstract: Quantifying the net carbon flux from land use and land cover changes (fLULCC) is critical for understanding the global carbon cycle and, hence, to support climate change mitigation. However, large-scale fLULCC is not directly measurable and has to be inferred from models instead, such as semi-empirical bookkeeping models and process-based dynamic global vegetation models (DGVMs). By definition, fLULCC estimates are not directly comparable between these two different model types. As an important example, DGVM-based fLULCC in the annual global carbon budgets is estimated under transient environmental forcing and includes the so-called loss of additional sink capacity (LASC). The LASC results from the impact of environmental changes on land carbon storage potential of managed land compared to potential vegetation and accumulates over time, which is not captured in bookkeeping models. The fLULCC from transient DGVM simulations, thus, strongly depends on the timing of land use and land cover changes mainly because LASC accumulation is cut off at the end of the simulated period. To estimate the LASC, the fLULCC from pre-industrial DGVM simulations, which is independent of changing environmental conditions, can be used. Additionally, DGVMs using constant present-day environmental forcing enable an approximation of bookkeeping estimates. Here, we analyse these three DGVM-derived fLULCC estimations (under transient, pre-industrial, and present-day forcing) for 12 models within 18 regions and quantify their differences as well as climate- and CO2-induced components and compare them to bookkeeping estimates. Averaged across the models, we find a global fLULCC (under transient conditions) of 2.0±0.6 PgC yr−1 for 2009–2018, of which ∼40 % are attributable to the LASC (0.8±0.3 PgC yr−1). From 1850 onward, the fLULCC accumulated to 189±56 PgC with 40±15 PgC from the LASC. Around 1960, the accumulating nature of the LASC causes global transient fLULCC estimates to exceed estimates under present-day conditions, despite generally increased carbon stocks in the latter. Regional hotspots of high cumulative and annual LASC values are found in the USA, China, Brazil, equatorial Africa, and Southeast Asia, mainly due to deforestation for cropland. Distinct negative LASC estimates in Europe (early reforestation) and from 2000 onward in the Ukraine (recultivation of post-Soviet abandoned agricultural land), indicate that fLULCC estimates in these regions are lower in transient DGVM compared to bookkeeping approaches. Our study unravels the strong dependence of fLULCC estimates on the time a certain land use and land cover change event happened to occur and on the chosen time period for the forcing of environmental conditions in the underlying simulations. We argue for an approach that provides an accounting of the fLULCC that is more robust against these choices, for example by estimating a mean DGVM ensemble fLULCC and LASC for a defined reference period and homogeneous environmental changes (CO2 only).
Published: 2021

3. 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

4. Dynamic global vegetation models underestimate net CO2 flux mean and interannual variability in dryland ecosystems

Author: Marcy E. Litvak, Tilden P. Meyers, Anthony P. Walker, Praveena Krishnan, Julia E. M. S. Nabel, Vivek K. Arora, Julia Pongratz, Stephen Sitch, Danica Lombardozzi, Natasha MacBean, Vladislav Bastrikov, Thomas Kolb, Sönke Zaehle, Philippe Peylin, David J. P. Moore, Joel A. Biederman, Russell L. Scott, Daniel S. Goll, 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), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
Subjects: 0106 biological sciences, 010504 meteorology & atmospheric sciences, global carbon cycle, [SDE.MCG]Environmental Sciences/Global Changes, Atmospheric sciences, 010603 evolutionary biology, 01 natural sciences, Carbon cycle, inter-annual variability, medicine, Ecosystem, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, General Environmental Science, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Renewable Energy, Sustainability and the Environment, Public Health, Environmental and Occupational Health, Co2 flux, Drylands, 15. Life on land, 13. Climate action, dynamic global vegetation models, Environmental science, medicine.symptom, Vegetation (pathology)
Abstract: Despite their sparse vegetation, dryland regions exert a huge influence over global biogeochemical cycles because they cover more than 40% of the world surface (Schimel 2010 Science 327 418–9). It is thought that drylands dominate the inter-annual variability (IAV) and long-term trend in the global carbon (C) cycle (Poulter et al 2014 Nature 509 600–3, Ahlstrom et al 2015 Science 348 895–9, Zhang et al 2018 Glob. Change Biol. 24 3954–68). Projections of the global land C sink therefore rely on accurate representation of dryland C cycle processes; however, the dynamic global vegetation models (DGVMs) used in future projections have rarely been evaluated against dryland C flux data. Here, we carried out an evaluation of 14 DGVMs (TRENDY v7) against net ecosystem exchange (NEE) data from 12 dryland flux sites in the southwestern US encompassing a range of ecosystem types (forests, shrub- and grasslands). We find that all the models underestimate both mean annual C uptake/release as well as the magnitude of NEE IAV, suggesting that improvements in representing dryland regions may improve global C cycle projections. Across all models, the sensitivity and timing of ecosystem C uptake to plant available moisture was at fault. Spring biases in gross primary production (GPP) dominate the underestimate of mean annual NEE, whereas models’ lack of GPP response to water availability in both spring and summer monsoon are responsible for inability to capture NEE IAV. Errors in GPP moisture sensitivity at high elevation forested sites were more prominent during the spring, while errors at the low elevation shrub and grass-dominated sites were more important during the monsoon. We propose a range of hypotheses for why model GPP does not respond sufficiently to changing water availability that can serve as a guide for future dryland DGVM developments. Our analysis suggests that improvements in modeling C cycle processes across more than a quarter of the Earth’s land surface could be achieved by addressing the moisture sensitivity of dryland C uptake.
Published: 2021

5. A multi-data assessment of land use and land cover emissions from Brazil during 2000-2019

Author: Celso von Randow, Lina M. Mercado, Kees Klein Goldewijk, Ana Bastos, Viola Heinrich, Raphael Ganzenmüller, Michael O'Sullivan, Luiz E. O. C. Aragão, Julia Pongratz, Thais M. Rosan, Stephen Sitch, Pierre Friedlingstein, A. Wiltshire, and Francesco N. Tubiello
Subjects: 010504 meteorology & atmospheric sciences, 0207 environmental engineering, 02 engineering and technology, Land cover, 7. Clean energy, 01 natural sciences, Ecology and Environment, land-use and land cover change, Environmental Science(all), global carbon budget, 11. Sustainability, deforestation, Renewable Energy, 020701 environmental engineering, 0105 earth and related environmental sciences, General Environmental Science, Land use, Sustainability and the Environment, Renewable Energy, Sustainability and the Environment, business.industry, Data assessment, Environmental resource management, Environmental and Occupational Health, Public Health, Environmental and Occupational Health, 15. Life on land, 13. Climate action, land-use emissions, Environmental science, Public Health, business
Abstract: Brazil is currently the largest contributor of land use and land cover change (LULCC) carbon dioxide net emissions worldwide, representing 17%–29% of the global total. There is, however, a lack of agreement among different methodologies on the magnitude and trends in LULCC emissions and their geographic distribution. Here we perform an evaluation of LULCC datasets for Brazil, including those used in the annual global carbon budget (GCB), and national Brazilian assessments over the period 2000–2018. Results show that the latest global HYDE 3.3 LULCC dataset, based on new FAO inventory estimates and multi-annual ESA CCI satellite-based land cover maps, can represent the observed spatial variation in LULCC over the last decades, representing an improvement on the HYDE 3.2 data previously used in GCB. However, the magnitude of LULCC assessed with HYDE 3.3 is lower than estimates based on MapBiomas. We use HYDE 3.3 and MapBiomas as input to a global bookkeeping model (bookkeeping of land use emission, BLUE) and a process-based Dynamic Global Vegetation Model (JULES-ES) to determine Brazil’s LULCC emissions over the period 2000–2019. Results show mean annual LULCC emissions of 0.1–0.4 PgC yr−1, compared with 0.1–0.24 PgC yr−1 reported by the Greenhouse Gas Emissions Estimation System of land use changes and forest sector (SEEG/LULUCF) and by FAO in its latest assessment of deforestation emissions in Brazil. Both JULES-ES and BLUE now simulate a slowdown in emissions after 2004 (−0.006 and −0.004 PgC yr−2 with HYDE 3.3, −0.014 and −0.016 PgC yr−2 with MapBiomas, respectively), in agreement with the Brazilian INPE-EM, global Houghton and Nassikas book-keeping models, FAO and as reported in the 4th national greenhouse gas inventories. The inclusion of Earth observation data has improved spatial representation of LULCC in HYDE and thus model capability to simulate Brazil’s LULCC emissions. This will likely contribute to reduce uncertainty in global LULCC emissions, and thus better constrains GCB assessments.
Published: 2021

6. Five years of variability in the global carbon cycle: comparing an estimate from the Orbiting Carbon Observatory-2 and process-based models

Author: Daniel S. Goll, Xuhui Wang, Vanessa Haverd, Stephen Sitch, Scot M. Miller, Julia E. M. S. Nabel, Sönke Zaehle, Emilie Joetzjer, Benjamin Poulter, Sebastian Lienert, Andy Wiltshire, Vladislav Bastrikov, Danica Lombardozzi, Julia Pongratz, Atul K. Jain, Shilong Piao, Joe R. Melton, Hanqin Tian, Etsushi Kato, Deborah N. Huntzinger, Zichong Chen, Junjie Liu, Peter Anthoni, Pierre Friedlingstein, Patrick C. McGuire, A. Arneth, 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)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and 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)
Subjects: Biosphere model, 010504 meteorology & atmospheric sciences, 530 Physics, Biome, OCO-2 satellite, Magnitude (mathematics), Tropical and subtropical grasslands, savannas, and shrublands, 010501 environmental sciences, Atmospheric sciences, 01 natural sciences, Carbon cycle, inter-annual variability, 550 Earth sciences & geology, carbon cycle, ddc:550, climate-carbon relationships, Precipitation, 0105 earth and related environmental sciences, General Environmental Science, Renewable Energy, Sustainability and the Environment, Public Health, Environmental and Occupational Health, Tropics, 15. Life on land, Earth sciences, 13. Climate action, [SDU]Sciences of the Universe [physics], Environmental science, environmental drivers, Satellite, ddc:500
Abstract: Year-to-year variability in CO2 fluxes can yield insight into climate-carbon cycle relationships, a fundamental yet uncertain aspect of the terrestrial carbon cycle. In this study, we use global observations from NASA’s Orbiting Carbon Observatory-2 (OCO-2) satellite for years 2015–2019 and a geostatistical inverse model to evaluate 5 years of interannual variability (IAV) in CO2 fluxes and its relationships with environmental drivers. OCO-2 launched in late 2014, and we specifically evaluate IAV during the time period when OCO-2 observations are available. We then compare inferences from OCO-2 with state-of-the-art process-based models (terrestrial biosphere model, TBMs). Results from OCO-2 suggest that the tropical grasslands biome (including grasslands, savanna, and agricultural lands within the tropics) makes contributions to global IAV during the 5 year study period that are comparable to tropical forests, a result that differs from a majority of TBMs. Furthermore, existing studies disagree on the environmental variables that drive IAV during this time period, and the analysis using OCO-2 suggests that both temperature and precipitation make comparable contributions. TBMs, by contrast, tend to estimate larger IAV during this time and usually estimate larger relative contributions from the extra-tropics. With that said, TBMs show little consensus on both the magnitude and the contributions of different regions to IAV. We further find that TBMs show a wide range of responses on the relationships of CO2 fluxes with annual anomalies in temperature and precipitation, and these relationships across most of the TBMs have a larger magnitude than inferred from OCO-2. Overall, the findings of this study highlight large uncertainties in process-based estimates of IAV during recent years and provide an avenue for evaluating these processes against inferences from OCO-2.
Published: 2021

7. Slow-down of the greening trend in natural vegetation with further rise in atmospheric CO2

Author: Alexander J. Winkler, Ranga B. Myneni, Alexis Hannart, Stephen Sitch, Vanessa Haverd, Danica Lombardozzi, Vivek K. Arora, Julia Pongratz, Julia E. M. S. Nabel, Daniel S. Goll, Etsushi Kato, Hanqin Tian, Almut Arneth, Pierre Friedlingstein, Atul K. Jain, Sönke Zaehle, and Victor Brovkin
Subjects: 010504 meteorology & atmospheric sciences, 13. Climate action, 0211 other engineering and technologies, 02 engineering and technology, 15. Life on land, 01 natural sciences, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences
Abstract: Satellite data reveal widespread changes of Earth's vegetation cover. Regions intensively attended to by humans are mostly greening due to land management. Natural vegetation, on the other hand, is exhibiting patterns of both greening and browning in all continents. Factors linked to anthropogenic carbon emissions, such as CO2 fertilization, climate change and consequent disturbances, such as fires and droughts, are hypothesized to be key drivers of changes in natural vegetation. A rigorous regional attribution at biome-level that can be scaled into a global picture of what is behind the observed changes is currently lacking. Here we analyze different datasets of decades-long satellite observations of global leaf area index (LAI, 1981–2017) as well as other proxies of vegetation changes, and identify several clusters of significant long-term changes. Using process-based model simulations (Earth system and land surface models), we disentangle the effects of anthropogenic carbon emissions on LAI in a probabilistic setting applying Causal Counterfactual Theory. The analysis prominently indicates the effects of climate change on many biomes – warming in northern ecosystems (greening) and rainfall anomalies in tropical biomes (browning). Our results do not support previously published accounts of dominant global-scale effects of CO2 fertilization. Altogether, our analysis reveals a slowing down of greening and strengthening of browning trends, particularly in the last two decades. Most models substantially underestimate the emerging vegetation browning, especially in the tropical rainforests. Leaf area loss in these productive ecosystems could be an early indicator of a slow-down in the terrestrial carbon sink. Models need to account for this effect to realize plausible climate projections of the 21st century.
Published: 2021

8. Empirical estimates of regional carbon budgets imply reduced global soil heterotrophic respiration

Author: Anna Peregon, Chao Yue, Grégoire Broquet, Chunjing Qiu, Jinfeng Chang, Thomas Gasser, Julia Pongratz, Bertrand Guenet, Ashley-P Ballantyne, Alessandro Baccini, Yilong Wang, Glen P. Peters, Josep G. Canadell, Anatoly Shvidenko, Fabienne Maignan, Riccardo Valentini, Ronny Lauerwald, Philippe Ciais, Yitong Yao, Alexandra G. Konings, Daniel S. Goll, Yi Yin, Shushi Peng, Rob J Andres, Hui Yang, Prabir K. Patra, Benjamin Poulter, Jens Hartmann, Anthony W. King, Goulven Gildas Laruelle, A. Johannes Dolman, Wei Li, Vanessa Haverd, Ana Bastos, Dan Zhu, Sebastiaan Luyssaert, Pierre Regnier, Jakob Zscheischler, Yi Liu, Peter A. Raymond, Rong Wang, 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)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ICOS-ATC (ICOS-ATC), 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), Ludwig-Maximilians-Universität München (LMU), 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), Vrije Universiteit Amsterdam [Amsterdam] (VU), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), NASA Goddard Space Flight Center (GSFC), Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), Laboratoire de géologie de l'ENS (LGENS), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, 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 Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), 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)-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), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Earth Sciences, Systems Ecology, and Earth and Climate
Subjects: 010504 meteorology & atmospheric sciences, AcademicSubjects/SCI00010, 530 Physics, Atmospheric carbon cycle, Inventory data, chemistry.chemical_element, 010502 geochemistry & geophysics, Atmospheric sciences, 01 natural sciences, carbon budget, SDG 17 - Partnerships for the Goals, SDG 13 - Climate Action, soil carbon, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, Carbon flux, Biomass (ecology), Multidisciplinary, Heterotrophic respiration, Géochimie, Primary production, human appropriation of ecosystems, Soil carbon, 15. Life on land, chemistry, 13. Climate action, [SDE]Environmental Sciences, Earth Sciences, Environmental science, AcademicSubjects/MED00010, Carbon, Research Article
Abstract: Resolving regional carbon budgets is critical for informing land-based mitigation policy. For nine regions covering nearly the whole globe, we collected inventory estimates of carbon-stock changes complemented by satellite estimates of biomass changes where inventory data are missing. The net land–atmospheric carbon exchange (NEE) was calculated by taking the sum of the carbon-stock change and lateral carbon fluxes from crop and wood trade, and riverine-carbon export to the ocean. Summing up NEE from all regions, we obtained a global ‘bottom-up’ NEE for net land anthropogenic CO2 uptake of –2.2 ± 0.6 PgC yr−1 consistent with the independent top-down NEE from the global atmospheric carbon budget during 2000–09. This estimate is so far the most comprehensive global bottom-up carbon budget accounting, which set up an important milestone for global carbon-cycle studies. By decomposing NEE into component fluxes, we found that global soil heterotrophic respiration amounts to a source of CO2 of 39 PgC yr−1 with an interquartile of 33–46 PgC yr−1—a much smaller portion of net primary productivity than previously reported., info:eu-repo/semantics/published
Published: 2021

9. The consolidated European synthesis of CO2 emissions and removals for the European Union and United Kingdom: 1990–2018

Author: Ronny Lauerwald, A.M.R. Petrescu, Matthew J. McGrath, Pete Smith, Hugo Denier van der Gon, Giacomo Grassi, Juraj Balkovic, Guillaume Monteil, Saqr Munassar, Ute Karstens, Patrick Brockmann, Philippe Peylin, Glen P. Peters, Lucia Perugini, Richard A. Houghton, Raphael Ganzenmüller, Efisio Solazzo, Matthias Kuhnert, A. J. Dolman, Mart-Jan Schelhaas, Dirk Günther, Gert-Jan Nabuurs, Christoph Gerbig, Robbie M. Andrew, Ingrid T. Luijkx, Philippe Ciais, Julia Pongratz, Greet Janssens-Maenhout, Pierre Regnier, Giulia Conchedda, Marko Scholze, Igor B. Konovalov, Chunjing Qiu, Grégoire Broquet, Roberto Pilli, Rona Thompson, Monica Crippa, Francesco N. Tubiello, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), and 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)
Subjects: 010504 meteorology & atmospheric sciences, Land use, [SDE.MCG]Environmental Sciences/Global Changes, Inversion (meteorology), 04 agricultural and veterinary sciences, 15. Life on land, Atmospheric sciences, 01 natural sciences, 7. Clean energy, 12. Responsible consumption, 13. Climate action, Greenhouse gas, 11. Sustainability, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, General Earth and Planetary Sciences, Sector model, Environmental science, media_common.cataloged_instance, Land use, land-use change and forestry, Kyoto Protocol, Emission inventory, European union, 0105 earth and related environmental sciences, media_common
Abstract: Reliable quantification of the sources and sinks of atmospheric carbon dioxide (CO 2 ), including that of their trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Kyoto Protocol and the Paris Agreement. This study provides a consolidated synthesis of estimates for all anthropogenic and natural sources and sinks of CO 2 for the European Union and UK (EU27 + UK), derived from a combination of state-of-the-art bottom-up (BU) and top-down (TD) data sources and models. Given the wide scope of the work and the variety of datasets involved, this study focuses on identifying essential questions which need to be answered to properly understand the differences between various datasets, in particular with regards to the less-well-characterized fluxes from managed ecosystems. The work integrates recent emission inventory data, process-based ecosystem model results, data-driven sector model results and inverse modeling estimates over the period 1990–2018. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported under the UNFCCC in 2019, aiming to assess and understand the differences between approaches. For the uncertainties in NGHGIs, we used the standard deviation obtained by varying parameters of inventory calculations, reported by the member states following the IPCC Guidelines. Variation in estimates produced with other methods, like atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arises from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. In comparing NGHGIs with other approaches, a key source of uncertainty is that related to different system boundaries and emission categories (CO 2 fossil) and the use of different land use definitions for reporting emissions from land use, land use change and forestry (LULUCF) activities (CO 2 land). At the EU27 + UK level, the NGHGI (2019) fossil CO 2 emissions (including cement production) account for 2624 Tg CO 2 in 2014 while all the other seven bottom-up sources are consistent with the NGHGIs and report a mean of 2588 ( ± 463 Tg CO 2 ). The inversion reports 2700 Tg CO 2 ( ± 480 Tg CO 2 ), which is well in line with the national inventories. Over 2011–2015, the CO 2 land sources and sinks from NGHGI estimates report −90 Tg C yr −1 ± 30 Tg C yr −1 while all other BU approaches report a mean sink of −98 Tg C yr −1 ( ± 362 Tg of C from dynamic global vegetation models only). For the TD model ensemble results, we observe a much larger spread for regional inversions (i.e., mean of 253 Tg C yr −1 ± 400 Tg C yr −1 ). This concludes that (a) current independent approaches are consistent with NGHGIs and (b) their uncertainty is too large to allow a verification because of model differences and probably also because of the definition of “CO 2 flux” obtained from different approaches. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.4626578 (Petrescu et al., 2020a).
Published: 2021

10. Integrating the evidence for a terrestrial carbon sink caused by increasing atmospheric CO2

Author: Philippe Ciais, Terhi Riutta, Margaret S. Torn, Kathleen K. Treseder, Phillip J. van Mantgem, Fortunat Joos, William K. Smith, Heather Graven, Trevor F. Keenan, Simone Fatichi, Stephen Sitch, Susan E. Trumbore, Belinda E. Medlyn, Lianhong Gu, Yao Liu, Anna T. Trugman, Juergen Schleucher, Elliott Campbell, Steve L. Voelker, Ana Bastos, Kristina J. Anderson-Teixeira, Pieter A. Zuidema, Mary E. Whelan, Mingkai Jiang, Martin G. De Kauwe, Ralph F. Keeling, Vanessa Haverd, David S. Ellsworth, Anthony P. Walker, Colleen M. Iversen, David J. P. Moore, Martin Heimann, Benton N. Taylor, César Terrer, Yadvinder Malhi, Tim R. McVicar, Julia Pongratz, Josep Peñuelas, David Frank, Katerina Georgiou, Josep G. Canadell, A. Shafer Powell, Matthew E. Craig, Manon Sabot, Roel J. W. Brienen, Victor O. Leshyk, Christian Körner, Sönke Zaehle, Sebastian Leuzinger, Richard J. Norby, Maxime Cailleret, Graham D. Farquhar, Benjamin N. Sulman, Giovanna Battipaglia, Natasha MacBean, Joshua B. Fisher, Kristine Grace Cabugao, Soumaya Belmecheri, Bruce A. Hungate, Sean M. McMahon, Kelly A. Heilman, Jürgen Knauer, Oak Ridge National Laboratory [Oak Ridge] (ORNL), UT-Battelle, LLC, Ludwig-Maximilians-Universität München (LMU), Scripps Institution of Oceanography (SIO - UC San Diego), University of California [San Diego] (UC San Diego), University of California (UC)-University of California (UC), Hawkesbury Institute for the Environment, Western Sydney University, Oak Ridge National Laboratory, Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft, University of the Study of Campania Luigi Vanvitelli, School of Geography and the Environment [Oxford] (SoGE), University of Oxford, Risques, Ecosystèmes, Vulnérabilité, Environnement, Résilience (RECOVER), Aix Marseille Université (AMU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), University of California (UC), Data61 [Canberra] (CSIRO), Australian National University (ANU)-Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), 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)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ICOS-ATC (ICOS-ATC), 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), U.S. Department of Energy Office of Science, Biological and Environmental Research. Grant Number: DE-AC05-00OR22725, Australian Research Council (ARC) Discovery Grant. Grant Number: DP190101823, US National Science Foundation Paleo Perspectives on Clima te Change Program, US Geological Survey Ecosystems Mission Area, NASA: NASA Terrestrial Ecosystems Grant 80NSSC19M 0103 and NASA Terrestrial Ecology Program IDS Award NNH 17AE86I, German Research Foundation’s Emmy Noether Program, Australian Research Council Centre of Excellence for Climate Extremes (CE170100023), VR, KAW and Kempe foundations, Lawrence Fellow award through Lawrence Livermore National Labor atory (LLNL) under contract DE-AC52-07NA27344 with the US Department of Energy and the LLNL-LDRD Program under Project no. 20-ERD-055, US Department of Energy, Ofﬁce of Science under contract number DE-AC02-05CH11231, USDA National Institute of Food and Agriculture, Agricultural and Food Research Initiative Competitive Programme grant no.2018-67012-31496, University of California Laboratory Fees Research Program Award no. LFR-20-652467, European Project: 647204,H2020,ERC-2014-CoG,QUINCY(2015), European Project: 610028,EC:FP7:ERC,ERC-2013-SyG,IMBALANCE-P(2014), Walker, Anthony P., De Kauwe, Martin G., Bastos, Ana, Belmecheri, Soumaya, Georgiou, Katerina, Keeling, Ralph F., Mcmahon, Sean M., Medlyn, Belinda E., Moore, David J. P., Norby, Richard J., Zaehle, Sönke, Anderson‐teixeira, Kristina J., Battipaglia, Giovanna, Brienen, Roel J. W., Cabugao, Kristine G., Cailleret, Maxime, Campbell, Elliott, Canadell, Josep G., Ciais, Philippe, Craig, Matthew E., Ellsworth, David S., Farquhar, Graham D., Fatichi, Simone, Fisher, Joshua B., Frank, David C., Graven, Heather, Gu, Lianhong, Haverd, Vanessa, Heilman, Kelly, Heimann, Martin, Hungate, Bruce A., Iversen, Colleen M., Joos, Fortunat, Jiang, Mingkai, Keenan, Trevor F., Knauer, Jürgen, Körner, Christian, Leshyk, Victor O., Leuzinger, Sebastian, Liu, Yao, Macbean, Natasha, Malhi, Yadvinder, Mcvicar, Tim R., Penuelas, Josep, Pongratz, Julia, Powell, A. Shafer, Riutta, Terhi, Sabot, Manon E. B., Schleucher, Juergen, Sitch, Stephen, Smith, William K., Sulman, Benjamin, Taylor, Benton, Terrer, César, Torn, Margaret S., Treseder, Kathleen K., Trugman, Anna T., Trumbore, Susan E., Mantgem, Phillip J., Voelker, Steve L., Whelan, Mary E., and Zuidema, Pieter A.
Subjects: 0106 biological sciences, CO fertilization, 010504 meteorology & atmospheric sciences, global carbon cycle, Physiology, chemistry.chemical_element, Plant Science, Atmospheric sciences, 01 natural sciences, Carbon cycle, chemistry.chemical_compound, land–atmosphere feedback, free-air CO enrichment (FACE), CO-fertilization hypothesis, CO2-fertilization hypothesis, Bosecologie en Bosbeheer, CO2 fertilization, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, Carbon dioxide in Earth's atmosphere, Carbon sink, food and beverages, carbon dioxide, terrestrial ecosystems, Global change, Soil carbon, 15. Life on land, PE&RC, Forest Ecology and Forest Management, chemistry, 13. Climate action, Carbon dioxide, [SDE]Environmental Sciences, Environmental science, Terrestrial ecosystem, beta factor, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Carbon, 010606 plant biology & botany, free-air CO2 enrichment (FACE)
Abstract: International audience; Atmospheric carbon dioxide concentration ([CO 2 ]) is increasing, which increases leaf-scale photosynthesis and intrinsic water-use efficiency. These direct responses have the potential to increase plant growth, vegetation biomass, and soil organic matter; transferring carbon from the atmosphere into terrestrial ecosystems (a carbon sink). A substantial global terrestrial carbon sink would slow the rate of [CO 2] increase and thus climate change. However, ecosystem CO2 responses are complex or confounded by concurrent changes in multiple agents of global change and evidence for a [CO 2]-driven terrestrial carbon sink can appear contradictory. Here we synthesize theory and broad, multidisciplinary evidence for the effects of increasing [CO 2] (iCO 2) on the global terrestrial carbon sink. Evidence suggests a substantial increase in global photosynthesis since pre-industrial times. Established theory, supported by experiments, indicates that iCO 2 is likely responsible for about half of the increase. Global carbon budgeting, atmospheric data, and forest inventories indicate a historical carbon sink, and these apparent iCO 2 responses are high in comparison to experiments and predictions from theory. Plantmortality and soil carbon iCO 2 responses are highly uncertain. In conclusion, a range of evidence supports a positive terrestrial carbon sink in response to iCO2 , albeit with uncertain magnitude and strong suggestion of a role for additional agents of global change.
Published: 2021

11. 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

12. The consolidated European synthesis of CO2 emissions and removals for EU27 and UK: 1990–2018

Author: Ana Maria Roxana Petrescu, Matthew J. McGrath, Robbie M. Andrew, Philippe Peylin, Glen P. Peters, Philippe Ciais, Gregoire Broquet, Francesco N. Tubiello, Christoph Gerbig, Julia Pongratz, Greet Janssens-Maenhout, Giacomo Grassi, Gert-Jan Nabuurs, Pierre Regnier, Ronny Lauerwald, Matthias Kuhnert, Juraj Balcovič, Mart-Jan Schelhaas, Hugo A. C. Denier van der Gon, Efisio Solazzo, Chunjing Qiu, Roberto Pilli, Igor B. Konovalov, Richard Houghton, Dirk Günther, Lucia Perugini, Monica Crippa, Raphael Ganzenmüller, Ingrid T. Luijkx, Pete Smith, Saqr Munassar, Rona L. Thompson, Giulia Conchedda, Guillaume Monteil, Marko Scholze, Ute Karstens, Patrick Brokmann, and Han Dolman
Subjects: 010504 meteorology & atmospheric sciences, 13. Climate action, 15. Life on land, 7. Clean energy, 01 natural sciences, 12. Responsible consumption, 0105 earth and related environmental sciences
Abstract: Reliable quantification of the sources and sinks of atmospheric carbon dioxide (CO2), including that of their trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Kyoto Protocol and the Paris Agreement. This study provides a consolidated synthesis of estimates for all anthropogenic and natural sources and sinks of CO2 for the European Union and UK (EU27 + UK), derived from a combination of state-of-the-art bottom-up (BU) and top-down (TD) data sources and models. Given the wide scope of the work and the variety of datasets involved, this study focuses on identifying essential questions which need to be answered to properly understand the differences between various datasets, in particular with regards to the less-well characterized fluxes from managed ecosystems. The work integrates recent emission inventory data, process-based ecosystem model results, data-driven sector model results, and inverse modelling estimates, over the period 1990–2018. BU and TD products are compared with European national GHG inventories (NGHGI) reported under the UNFCCC in 2019, aiming to assess and understand the differences between approaches. For the uncertainties in NGHGI, we used the standard deviation obtained by varying parameters of inventory calculations, reported by the Member States following the IPCC guidelines. Variation in estimates produced with other methods, like atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. In comparing NGHGI with other approaches, a key source of uncertainty is that related to different system boundaries and emission categories (CO2 fossil) and the use of different land use definitions for reporting emissions from Land Use, Land Use Change and Forestry (LULUCF) activities (CO2 land). At the EU27 + UK level, the NGHGI (2019) fossil CO2 emissions (including cement production) account for 2624 Tg CO2 in 2014 while all the other seven bottom-up sources are consistent with the NGHGI and report a mean of 2588 (± 463 Tg CO2). The inversion reports 2700 Tg CO2 (± 480 Tg CO2), well in line with the national inventories. Over 2011–2015, the CO2 land sources/sinks from NGHGI estimates report −90 Tg C yr−1 ± 30 Tg C while all other BU approaches report a mean sink of −98 Tg yr−1 (± 362 Tg C from DGVMs only). For the TD model ensemble results, we observe a much larger spread for regional inversions (i.e., mean of 253 Tg C yr−1 ± 400 T g C yr−1). This concludes that a) current independent approaches are consistent with NGHGI b) their uncertainty is too large to allow a verification because of model differences and probably also because of the definition of CO2 flux obtained from different approaches. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.4288883 (Petrescu et al., 2020).
Published: 2020

13. Decadal variability in land carbon sink efficiency

Author: Lei Zhu, Philippe Ciais, Ana Bastos, Frédéric Chevallier, Julia Pongratz, Ashley P. Ballantyne, Christian Rödenbeck, Wei Li, Thomas Gasser, Masayuki Kondo, Tsinghua University [Beijing] (THU), 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)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ICOS-ATC (ICOS-ATC), 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), 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)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Ludwig-Maximilians-Universität München (LMU), Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), International Institute for Applied Systems Analysis [Laxenburg] (IIASA), Nagoya University, Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Max Planck Institute for Biogeochemistry (MPI-BGC), This study is supported by the National Key R&D Program of China (Grant Number 2019YFA0606604, This work is also partly supported by the European Space Agency Climate Change Initiative ESA‐CCI RECCAP2 project (ESRIN/ 4000123002/18/I‐NB), ANR-16-CONV-0003,CLAND,CLAND : Changement climatique et usage des terres(2016), European Project: 610028,EC:FP7:ERC,ERC-2013-SyG,IMBALANCE-P(2014), 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), and 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)
Subjects: 010504 meteorology & atmospheric sciences, Pinatubo eruption, Management, Monitoring, Policy and Law, Atmospheric sciences, 01 natural sciences, Sink (geography), Carbon neutrality, 03 medical and health sciences, Earth and Planetary Sciences (miscellaneous), GE1-350, Ecosystem, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Trend reversal, 030304 developmental biology, 0105 earth and related environmental sciences, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, 0303 health sciences, Global and Planetary Change, geography, geography.geographical_feature_category, business.industry, Research, Fossil fuel, Carbon sink, Tropics, 15. Life on land, Land carbon sink efficiency, Environmental sciences, Climate change mitigation, 13. Climate action, General Earth and Planetary Sciences, Environmental science, business
Abstract: Background The climate mitigation target of limiting the temperature increase below 2 °C above the pre-industrial levels requires the efforts from all countries. Tracking the trajectory of the land carbon sink efficiency is thus crucial to evaluate the nationally determined contributions (NDCs). Here, we define the instantaneous land sink efficiency as the ratio of natural land carbon sinks to emissions from fossil fuel and land-use and land-cover change with a value of 1 indicating carbon neutrality to track its temporal dynamics in the past decades. Results Land sink efficiency has been decreasing during 1957–1990 because of the increased emissions from fossil fuel. After the effect of the Mt. Pinatubo eruption diminished (after 1994), the land sink efficiency firstly increased before 2009 and then began to decrease again after 2009. This reversal around 2009 is mostly attributed to changes in land sinks in tropical regions in response to climate variations. Conclusions The decreasing trend of land sink efficiency in recent years reveals greater challenges in climate change mitigation, and that climate impacts on land carbon sinks must be accurately quantified to assess the effectiveness of regional scale climate mitigation policies.
Published: 2020

14. European anthropogenic AFOLU greenhouse gas emissions:a review and benchmark data

Author: Ana Bastos, Glen P. Peters, Philippe Ciais, Greet Janssens-Maenhout, Lena Höglund-Isaksson, Gema Carmona-Garcia, Adrian Leip, Efisio Solazzo, Mart-Jan Schelhaas, Gert-Jan Nabuurs, Roberto Pilli, Dirk Günther, Julia E. M. S. Nabel, Anja Kiesow, Giacomo Grassi, Robbie M. Andrew, Francesco N. Tubiello, Julia Pongratz, Giulia Conchedda, A. J. Dolman, Wilfried Winiwarter, A.M.R. Petrescu, Center for International Climate and Environmental Research [Oslo] (CICERO), University of Oslo (UiO), JRC Institute for Environment and Sustainability (IES), European Commission - Joint Research Centre [Ispra] (JRC), 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), Food and Agriculture Organization of the United Nations, Regional Office for the Near East and North Africa (FAO), Food and Agriculture Organization of the United Nations [Rome, Italie] (FAO), Team Vegetation Forest & Landscape Ecology, Wageningen University and Research [Wageningen] (WUR), Climate Change Unit [Ispra], European Commission - Joint Research Centre [Ispra] (JRC)-European Commission - Joint Research Centre [Ispra] (JRC), International Institute for Applied Systems Analysis [Laxenburg] (IIASA), JRC Institute for Health and Consumer Protection (IHCP), Ludwig Maximilian University [Munich] (LMU), Department of Global Ecology [Carnegie] (DGE), Carnegie Institution for Science [Washington], Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, New Zealand Centre for Ecological Economics (NZCEE), Centre for Ecosystem Studies, ALTERRA, 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 Carnegie Institution for Science
Subjects: 010504 meteorology & atmospheric sciences, Natural resource economics, Bos- en Landschapsecologie, 010501 environmental sciences, 01 natural sciences, 7. Clean energy, 11. Sustainability, SDG 13 - Climate Action, media_common.cataloged_instance, Life Science, Forest and Landscape Ecology, Ecosystem, European union, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Vegetatie, lcsh:Environmental sciences, 0105 earth and related environmental sciences, media_common, lcsh:GE1-350, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Vegetation, Land use, lcsh:QE1-996.5, 15. Life on land, PE&RC, lcsh:Geology, 13. Climate action, Greenhouse gas, General Earth and Planetary Sciences, Environmental science, Vegetatie, Bos- en Landschapsecologie, Vegetation, Forest and Landscape Ecology, Benchmark data
Abstract: Emission of greenhouse gases (GHGs) and removals from land, including both anthropogenic and natural fluxes, require reliable quantification, including estimates of uncertainties, to support credible mitigation action under the Paris Agreement. This study provides a state-of-the-art scientific overview of bottom-up anthropogenic emissions data from agriculture, forestry and other land use (AFOLU) in the European Union (EU281). The data integrate recent AFOLU emission inventories with ecosystem data and land carbon models and summarize GHG emissions and removals over the period 1990-2016. This compilation of bottom-up estimates of the AFOLU GHG emissions of European national greenhouse gas inventories (NGHGIs), with those of land carbon models and observation-based estimates of large-scale GHG fluxes, aims at improving the overall estimates of the GHG balance in Europe with respect to land GHG emissions and removals. Whenever available, we present uncertainties, its propagation and role in the comparison of different estimates. While NGHGI data for the EU28 provide consistent quantification of uncertainty following the established IPCC Guidelines, uncertainty in the estimates produced with other methods needs to account for both within model uncertainty and the spread from different model results. The largest inconsistencies between EU28 estimates are mainly due to different sources of data related to human activity, referred to here as activity data (AD) and methodologies (tiers) used for calculating emissions and removals from AFOLU sectors. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.3662371 (Petrescu et al., 2020).
Published: 2020

15. Increased control of vegetation on global terrestrial energy fluxes

Author: Andy Wiltshire, Vivek K. Arora, Alessandro Cescatti, Eddy Robertson, Goran Georgievski, Almut Arneth, Danica Lombardozzi, Giovanni Forzieri, Youngryel Ryu, Philippe Ciais, Peter Lawrence, Brecht Martens, Gregory Duveiller, Ke Zhang, Guido Ceccherini, Chongya Jiang, Etsushi Kato, Julia Pongratz, Peter Anthoni, Ramdane Alkama, Julia E. M. S. Nabel, Pierre Friedlingstein, Daniel S. Goll, Stephen Sitch, Markus Kautz, Diego G. Miralles, Sebastian Lienert, Shilong Piao, Wei Li, Hanqin Tian, European Commission - Joint Research Centre [Ispra] (JRC), 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)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ICOS-ATC (ICOS-ATC), 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), ANR-16-CONV-0003,CLAND,CLAND : Changement climatique et usage des terres(2016), 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), and 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)
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, 0303 health sciences, 010504 meteorology & atmospheric sciences, Moisture, Land cover, Vegetation, 15. Life on land, Environmental Science (miscellaneous), Plant functional type, Atmospheric sciences, 01 natural sciences, 03 medical and health sciences, 13. Climate action, Evapotranspiration, Environmental science, Bowen ratio, Leaf area index, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Social Sciences (miscellaneous), ComputingMilieux_MISCELLANEOUS, 030304 developmental biology, 0105 earth and related environmental sciences, Transpiration
Abstract: Changes in vegetation structure are expected to influence the redistribution of heat and moisture; however, how variations in the leaf area index (LAI) affect this global energy partitioning is not yet quantified. Here, we estimate that a unit change in LAI leads to 3.66 ± 0.45 and −3.26 ± 0.41 W m−2 in latent (LE) and sensible (H) fluxes, respectively, over the 1982–2016 period. Analysis of an ensemble of data-driven products shows that these sensitivities increase by about 20% over the observational period, prominently in regions with a limited water supply, probably because of an increased transpiration/evaporation ratio. Global greening has caused a decrease in the Bowen ratio (B = H/LE) of −0.010 ± 0.002 per decade, which is attributable to the increased evaporative surface. Such a direct LAI effect on energy fluxes is largely modulated by plant functional types (PFTs) and background climate conditions. Land surface models (LSMs) misrepresent this vegetation control, possibly due to underestimation of the biophysical responses to changes in the water availability and poor representation of LAI dynamics. Changes in the leaf area index alter the distribution of heat and moisture. The change in energy partitioning related to leaf area, increasing latent and decreasing sensible fluxes over the observational period 1982–2016, is moderated by plant functional type and background climate.
Published: 2020

16. Sources of Uncertainty in Regional and Global Terrestrial CO 2 Exchange Estimates

Author: Julia E. M. S. Nabel, Anthony P. Walker, Danica Lombardozzi, Naomi E. Smith, B. Poulter, Stephen Sitch, Christian Rödenbeck, Ingrid T. Luijkx, Sönke Zaehle, Frédéric Chevallier, Wei Li, J. G. Canadell, Atul K. Jain, Etsushi Kato, P. Ciais, Wouter Peters, P. Peylin, Sebastian Lienert, Daniel S. Goll, V. Haverd, Pierre Friedlingstein, Prabir K. Patra, Ronny Lauerwald, Hanqin Tian, Julia Pongratz, Michael O'Sullivan, David Makowski, Ana Bastos, College of Engineering, Mathematics and Physical Sciences [Exeter] (EMPS), University of Exeter, LUDWIG MAXIMILIANS UNIVERSITAT MUNCHEN DEPARTMENT OF GEOGRAPHY MUNICH DEU, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), 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), Agronomie, AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), College of Life and Environmental Sciences [Exeter], Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), Max-Planck-Institut für Biogeochemie (MPI-BGC), Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, WUR - Wageningen University and Research Centre [Wageningen], Research Institute for Global Change (RIGC), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), CSIRO Oceans and Atmosphere, CISRO Oceans and Atmosphere, Department of Geosciences, Environment and Society, Université libre de Bruxelles (ULB), Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Wageningen University and Research [Wageningen] (WUR), Centre for Isotope Research [Groningen] (CIO), University of Groningen [Groningen], Department of Geography, University of Augsburg, Department of Atmospheric Sciences [Urbana], University of Illinois at Urbana-Champaign [Urbana], University of Illinois System-University of Illinois System, Institute of Applied Energy (IAE), Climate and Environmental Physics [Bern] (CEP), Physikalisches Institut [Bern], Universität Bern [Bern]-Universität Bern [Bern], CLIMATE AND GLOBAL DYNAMICS LABORATORY NATIONAL CENTER FOR ATMOSPHERIC RESEARCH BOULDER USA, Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Biospheric Sciences Laboratory, NASA Goddard Space Flight Center (GSFC), INTERNATIONAL CENTER FOR CLIMATE AND GLOBAL CHANGE RESEARCH AUBURN UNIVERSITY AUBURN USA, Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Max Planck Institute for Biogeochemistry (MPI-BGC), European Comission. Grant Numbers: ASICA (649087), IMBALANCE-P European Space Agency (ESA). Grant Number: ESRIN/ 4000123002/18/I-NB National Science Foundation (NSF). Grant Number: AGS 12-43071 U.S. Department of Energy (DOE). Grant Number: DESC0016323, 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), Universität Bern [Bern] (UNIBE)-Universität Bern [Bern] (UNIBE), 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), ANR-16-CONV-0003,CLAND,CLAND : Changement climatique et usage des terres(2016), and Isotope Research
Subjects: 0106 biological sciences, Meteorologie en Luchtkwaliteit, FLUXES, Atmospheric Science, 010504 meteorology & atmospheric sciences, Meteorology and Air Quality, Biome, BURNED AREA PRODUCT, atmospheric inversions, 01 natural sciences, Carbon cycle, DATA ASSIMILATION, Data assimilation, PLANT FUNCTIONAL TYPES, global carbon budget, carbon cycle, Environmental Chemistry, Land use, land-use change and forestry, ATMOSPHERIC CO2, 0105 earth and related environmental sciences, General Environmental Science, ddc:910, LAND-COVER CHANGE, Global and Planetary Change, WIMEK, FOSSIL-FUEL, Land use, business.industry, 010604 marine biology & hydrobiology, VEGETATION MODEL ORCHIDEE, Fossil fuel, Vegetation, 15. Life on land, CARBON-DIOXIDE EMISSIONS, 13. Climate action, Climatology, [SDE]Environmental Sciences, dynamic global vegetation models, Environmental science, business, Scale (map), INCORPORATING SPITFIRE
Abstract: The Global Carbon Budget 2018 (GCB2018) estimated by the atmospheric CO2 growth rate, fossil fuel emissions, and modeled (bottom-up) land and ocean fluxes cannot be fully closed, leading to a “budget imbalance,” highlighting uncertainties in GCB components. However, no systematic analysis has been performed on which regions or processes contribute to this term. To obtain deeper insight on the sources of uncertainty in global and regional carbon budgets, we analyzed differences in Net Biome Productivity (NBP) for all possible combinations of bottom-up and top-down data sets in GCB2018: (i) 16 dynamic global vegetation models (DGVMs), and (ii) 5 atmospheric inversions that match the atmospheric CO2 growth rate. We find that the global mismatch between the two ensembles matches well the GCB2018 budget imbalance, with Brazil, Southeast Asia, and Oceania as the largest contributors. Differences between DGVMs dominate global mismatches, while at regional scale differences between inversions contribute the most to uncertainty. At both global and regional scales, disagreement on NBP interannual variability between the two approaches explains a large fraction of differences. We attribute this mismatch to distinct responses to El Niño–Southern Oscillation variability between DGVMs and inversions and to uncertainties in land use change emissions, especially in South America and Southeast Asia. We identify key needs to reduce uncertainty in carbon budgets: reducing uncertainty in atmospheric inversions (e.g., through more observations in the tropics) and in land use change fluxes, including more land use processes and evaluating land use transitions (e.g., using high-resolution remote-sensing), and, finally, improving tropical hydroecological processes and fire representation within DGVMs.
Published: 2020

17. Rainfall manipulation experiments as simulated by terrestrial biosphere models : where do we stand?

Author: Inger Kappel Schmidt, Romà Ogaya, Ying-Ping Wang, Martin G. De Kauwe, Qiuan Zhu, Julia E. M. S. Nabel, Anthony J. Parolari, Alan K. Knapp, Athanasios Paschalis, Enqing Hou, Daniel S. Goll, Nicolas Viovy, Donghai Wu, Jakob Zscheischler, Philippe Ciais, Changhui Peng, Jinfeng Chang, Hao Shi, Paul J. Hanson, Simone Fatichi, Hanqin Tian, Anna M. Ukkola, Sara Vicca, Jaime Kigel, Yiqi Luo, Lena Boysen, Marcelo Sternberg, Klaus Steenberg Larsen, Julia Pongratz, Patrick Meir, Marc Estiarte, Sebastian Lienert, Elisabeth Tschumi, Michael Bahn, Anna B. Harper, Wei Li, Serge Rambal, Zhuonan Wang, Karina Williams, Josep Peñuelas, 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)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ICOS-ATC (ICOS-ATC), 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), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Natural Environment Research Council (NERC), 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), and 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)
Subjects: 0106 biological sciences, 010504 meteorology & atmospheric sciences, COMMUNITY LAND MODEL, Biodiversity & Conservation, 05 Environmental Sciences, drought, Atmospheric sciences, 01 natural sciences, irrigation, Terrestrial biosphere models, Evapotranspiration, CLIMATE EXTREMES, ComputingMilieux_MISCELLANEOUS, General Environmental Science, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Global and Planetary Change, Ecology, Biosphere, Vegetation, Chemistry, Productivity (ecology), Biodiversity Conservation, Seasons, INTERANNUAL VARIABILITY, Life Sciences & Biomedicine, WATER-USE EFFICIENCY, VEGETATION DYNAMICS, 530 Physics, STOMATAL CONDUCTANCE, Growing season, Environmental Sciences & Ecology, SOIL-MOISTURE, 010603 evolutionary biology, Carbon Cycle, Carbon cycle, terrestrial biosphere models, Environmental Chemistry, Ecosystem, Leaf area index, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Biology, Irrigation, 0105 earth and related environmental sciences, CARBON FLUXES, Science & Technology, Drought, Rainfall manipulation experiment, LEAF-AREA INDEX, Water, 15. Life on land, 06 Biological Sciences, Plant Leaves, 13. Climate action, Environmental science, PRECIPITATION PULSES, Environmental Sciences, rainfall manipulation experiment
Abstract: Changes in rainfall amounts and patterns have been observed and are expected to continue in the near future with potentially significant ecological and societal consequences. Modelling vegetation responses to changes in rainfall is thus crucial to project water and carbon cycles in the future. In this study, we present the results of a new model‐data intercomparison project, where we tested the ability of ten terrestrial biosphere models to reproduce observed sensitivity of ecosystem productivity to rainfall changes at ten sites across the globe, in nine of which, rainfall exclusion and/or irrigation experiments had been performed.The key results are:(a) Inter‐model variation is generally large and model agreement varies with time scales. In severely water limited sites, models only agree on the interannual variability of evapotranspiration and to a smaller extent gross primary productivity. In more mesic sites model agreement for both water and carbon fluxes is typically higher on fine (daily‐monthly) time scales and reduces on longer (seasonal‐annual) scales.(b) Models on average overestimate the relationship between ecosystem productivity and mean rainfall amounts across sites (in space) and have a low capacity in reproducing the temporal (interannual) sensitivity of vegetation productivity to annual rainfall at a given site, even though observation uncertainty is comparable to inter‐model variability.(c) Most models reproduced the sign of the observed patterns in productivity changes in rainfall manipulation experiments but had a low capacity in reproducing the observed magnitude of productivity changes. Models better reproduced the observed productivity responses due to rainfall exclusion than addition.(d) All models attribute ecosystem productivity changes to the intensity of vegetation stress and peak leaf area, whereas the impact of the change in growing season length is negligible. The relative contribution of the peak leaf area and vegetation stress intensity was highly variable among models.
Published: 2020

18. Direct and seasonal legacy effects of the 2018 heat wave and drought on European ecosystem productivity

Author: Julia Pongratz, Atul K. Jain, P. Ciais, Markus Reichstein, Tammas Loughran, Pierre Friedlingstein, Peter Anthoni, Jean-Pierre Wigneron, Zheng Fu, Almut Arneth, Sebastian Lienert, Patrick C. McGuire, Lei Fan, Ana Bastos, Jürgen Knauer, Hanqin Tian, Sönke Zaehle, Emilie Joetzjer, Nicolas Viovy, Stephen Sitch, Ulrich Weber, Vanessa Haverd, Ludwig Maximilian University [Munich] (LMU), 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)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ICOS-ATC (ICOS-ATC), 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), College of Engineering, Mathematics and Physical Sciences [Exeter] (EMPS), University of Exeter, 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)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Potsdam Institute for Climate Impact Research (PIK), Department of Global Ecology [Carnegie] (DGE), Carnegie Institution for Science, Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Ludwig-Maximilians-Universität München (LMU), Interactions Sol Plante Atmosphère (UMR ISPA), Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), University of Illinois at Urbana-Champaign [Urbana], University of Illinois System, 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), Climate and Environmental Physics [Bern] (CEP), Physikalisches Institut [Bern], Universität Bern [Bern] (UNIBE)-Universität Bern [Bern] (UNIBE), Department of Meteorology [Reading], University of Reading (UOR), Auburn University (AU), 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)-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), 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), Carnegie Institution for Science [Washington], Météo France-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), and Universität Bern [Bern]-Universität Bern [Bern]
Subjects: 010504 meteorology & atmospheric sciences, Summer heat, 530 Physics, 010501 environmental sciences, Atmospheric sciences, 01 natural sciences, Sink (geography), Ecosystem carbon, ddc:550, Ecosystem, [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology, Water content, Research Articles, 0105 earth and related environmental sciences, 2. Zero hunger, Climatology, geography, Multidisciplinary, geography.geographical_feature_category, Ecology, fungi, SciAdv r-articles, food and beverages, Vegetation composition, 15. Life on land, Heat wave, Earth sciences, 13. Climate action, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Environmental science, Research Article
Abstract: Ecosystems responded asymmetrically to the 2018 European drought., In summer 2018, central and northern Europe were stricken by extreme drought and heat (DH2018). The DH2018 differed from previous events in being preceded by extreme spring warming and brightening, but moderate rainfall deficits, yet registering the fastest transition between wet winter conditions and extreme summer drought. Using 11 vegetation models, we show that spring conditions promoted increased vegetation growth, which, in turn, contributed to fast soil moisture depletion, amplifying the summer drought. We find regional asymmetries in summer ecosystem carbon fluxes: increased (reduced) sink in the northern (southern) areas affected by drought. These asymmetries can be explained by distinct legacy effects of spring growth and of water-use efficiency dynamics mediated by vegetation composition, rather than by distinct ecosystem responses to summer heat/drought. The asymmetries in carbon and water exchanges during spring and summer 2018 suggest that future land-management strategies could influence patterns of summer heat waves and droughts under long-term warming.
Published: 2020

19. Forest production efficiency increases with growth temperature

Author: Alessandro Cescatti, Alessio Collalti, Andreas Ibrom, Giorgio Matteucci, Marcos Fernández-Martínez, Ramdane Alkama, Daniel S. Goll, Julia Pongratz, Philippe Ciais, Anders Stockmarr, Vanessa Haverd, Stephen Sitch, Julia E. M. S. Nabel, Iain Colin Prentice, Pierre Friedlingstein, Almut Arneth, 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)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), FOE-2019 College of Natural Resources, University of California Berkeley, CNR: DTA.AD003.474, We thank R.H. Waring, S. Vicca, M. Campioli, F. Pagani and E. Grieco for early constructive comments and thoughtful suggestions, S. Noce for the map of data points. We thank efforts from all site investigators and their funding agencies. This paper contributes to the AXA Chair Programme in Biosphere and Climate Impacts and the Imperial College initiative Grand Challenges in Ecosystems and the Environment. A.C. and G.M. are partially supported by resources available from the Ministry of University and Research (FOE-2019), under the project 'Climate Change' (CNR DTA.AD003.474), M.F.-M. is a postdoctoral fellow of the Research Foundation—Flanders (FWO), AXA Research Fund, and 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)
Subjects: 0106 biological sciences, 010504 meteorology & atmospheric sciences, General Physics and Astronomy, adaptation, Atmospheric sciences, 01 natural sciences, Nutrient, Forest production efficiency, ddc:550, SDG 13 - Climate Action, gpp, lcsh:Science, Plant ecology, chemistry.chemical_classification, forest productivity, Carbon dioxide in Earth's atmosphere, Biomass (ecology), Multidisciplinary, Climate-change ecology, Biogeography, [SDE]Environmental Sciences, Engineering sciences. Technology, primary production, biomass production efficienty, Science, carbon use efficiency, chemistry.chemical_element, General Biochemistry, Genetics and Molecular Biology, Article, Latitude, Organic matter, Ecosystem, Precipitation, Biology, 0105 earth and related environmental sciences, Computer. Automation, npp, Primary production, General Chemistry, 15. Life on land, Earth sciences, chemistry, 13. Climate action, Environmental science, lcsh:Q, Forest ecology, Carbon, 010606 plant biology & botany
Abstract: Forest production efficiency (FPE) metric describes how efficiently the assimilated carbon is partitioned into plants organs (biomass production, BP) or—more generally—for the production of organic matter (net primary production, NPP). We present a global analysis of the relationship of FPE to stand-age and climate, based on a large compilation of data on gross primary production and either BP or NPP. FPE is important for both forest production and atmospheric carbon dioxide uptake. We find that FPE increases with absolute latitude, precipitation and (all else equal) with temperature. Earlier findings—FPE declining with age—are also supported by this analysis. However, the temperature effect is opposite to what would be expected based on the short-term physiological response of respiration rates to temperature, implying a top-down regulation of carbon loss, perhaps reflecting the higher carbon costs of nutrient acquisition in colder climates. Current ecosystem models do not reproduce this phenomenon. They consistently predict lower FPE in warmer climates, and are therefore likely to overestimate carbon losses in a warming climate., Many models assume a universal carbon use efficiency across forest biomes, in contrast to assumptions of other process-based models. Here the authors analyse forest production efficiency across a wide range of climates to show a positive relationship with annual temperature and precipitation, indicating that ecosystem models are overestimating forest carbon losses under warming.
Published: 2020

20. Soil carbon sequestration simulated in CMIP6-LUMIP models: implications for climatic mitigation

Author: Tomohiro Hajima, Sergey Malyshev, Daniele Peano, Akihiko Ito, Victor Brovkin, Bertrand Guenet, David Wårlind, Stefano Materia, Nicolas Vuichard, Elena Shevliakova, Andy Wiltshire, Eddy Robertson, Tilo Ziehn, Julia Pongratz, Chris D. Jones, David M. Lawrence, Sonali McDermid, Christine Delire, National Institute for Environmental Studies (NIES), 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), Horizon 2020 Framework Programme, H2020, Original content from this work may be used under the terms of the . Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Joint UK BEIS/Defra Met Office Hadley Centre Climate Programme GA01101 Integrated Research Program for Advancing Climate Models JPMXD0717935715 European Union’s Horizon 2020 research and innovation programme CRESCENDO 641816 German Research Foundation’s EmmyNoether Program PO1751/1-1 Regional and Global Climate Modeling Program 810 ANR 'Investissements d’avenir' program CLAND ANR-16-CONV-0003 yes � 2020 The Author(s). Published by IOP Publishing Ltd Creative Commons Attribution 4.0 license, 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 ANR-16-CONV-0003,CLAND,CLAND : Changement climatique et usage des terres(2016)
Subjects: 010504 meteorology & atmospheric sciences, Land management, Climate change, 010501 environmental sciences, Carbon sequestration, Atmospheric sciences, 01 natural sciences, land-use change, Ecosystem, Land use, land-use change and forestry, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, General Environmental Science, Renewable Energy, Sustainability and the Environment, Public Health, Environmental and Occupational Health, Earth system models, Soil carbon, 15. Life on land, carbon sequestration, soil organic carbon, climate change, Climate change mitigation, [SDU]Sciences of the Universe [physics], 13. Climate action, [SDE]Environmental Sciences, Soil water, Environmental science
Abstract: Land-use change affects both the quality and quantity of soil organic carbon (SOC) and leads to changes in ecosystem functions such as productivity and environmental regulation. Future changes in SOC are, however, highly uncertain owing to its heterogeneity and complexity. In this study, we analyzed the outputs of simulations of SOC stock by Earth system models (ESMs), most of which are participants in the Land-Use Model Intercomparison Project. Using a common protocol and the same forcing data, the ESMs simulated SOC distribution patterns and their changes during historical (1850–2014) and future (2015–2100) periods. Total SOC stock increased in many simulations over the historical period (30 ± 67 Pg C) and under future climate and land-use conditions (48 ± 32 Pg C for ssp126 and 49 ± 58 Pg C for ssp370). Land-use experiments indicated that changes in SOC attributable to land-use scenarios were modest at the global scale, in comparison with climatic and rising CO2 impacts, but they were notable in several regions. Future net soil carbon sequestration rates estimated by the ESMs were roughly 0.4‰ yr−1 (0.6 Pg C yr−1). Although there were considerable inter-model differences, the rates are still remarkable in terms of their potential for mitigation of global warming. The disparate results among ESMs imply that key parameters that control processes such as SOC residence time need to be better constrained and that more comprehensive representation of land management impacts on soils remain critical for understanding the long-term potential of soils to sequester carbon.
Published: 2020

21. Re-evaluating the 1940s CO2 plateau

Author: Philippe Ciais, Shushi Peng, Victor Brovkin, Nicolas Viovy, Julia Pongratz, Thomas Gasser, Jonathan Barichivich, Ana Bastos, Cathy M. Trudinger, and Laurent Bopp
Subjects: 0106 biological sciences, geography, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, 010604 marine biology & hydrobiology, Carbon sink, Climate change, 15. Life on land, 01 natural sciences, Sink (geography), Ice core, 13. Climate action, Climatology, Co2 concentration, Environmental science, 14. Life underwater, Natural variability, Growth rate, Independent data, Ecology, Evolution, Behavior and Systematics, 0105 earth and related environmental sciences, Earth-Surface Processes
Abstract: The high-resolution CO2 record from Law Dome ice core reveals that atmospheric CO2 concentration stalled during the 1940s (so-called CO2 plateau). Since the fossil-fuel emissions did not decrease during the period, this stalling implies the persistence of a strong sink, perhaps sustained for as long as a decade or more. Double-deconvolution analyses have attributed this sink to the ocean, conceivably as a response to the very strong El Niño event in 1940–1942. However, this explanation is questionable, as recent ocean CO2 data indicate that the range of variability in the ocean sink has been rather modest in recent decades, and El Niño events have generally led to higher growth rates of atmospheric CO2 due to the offsetting terrestrial response. Here, we use the most up-to-date information on the different terms of the carbon budget: fossil-fuel emissions, four estimates of land-use change (LUC) emissions, ocean uptake from two different reconstructions, and the terrestrial sink modelled by the TRENDY project to identify the most likely causes of the 1940s plateau. We find that they greatly overestimate atmospheric CO2 growth rate during the plateau period, as well as in the 1960s, in spite of giving a plausible explanation for most of the 20th century carbon budget, especially from 1970 onwards. The mismatch between reconstructions and observations during the CO2 plateau epoch of 1940–1950 ranges between 0.9 and 2.0 Pg C yr−1, depending on the LUC dataset considered. This mismatch may be explained by (i) decadal variability in the ocean carbon sink not accounted for in the reconstructions we used, (ii) a further terrestrial sink currently missing in the estimates by land-surface models, or (iii) LUC processes not included in the current datasets. Ocean carbon models from CMIP5 indicate that natural variability in the ocean carbon sink could explain an additional 0.5 Pg C yr−1 uptake, but it is unlikely to be higher. The impact of the 1940–1942 El Niño on the observed stabilization of atmospheric CO2 cannot be confirmed nor discarded, as TRENDY models do not reproduce the expected concurrent strong decrease in terrestrial uptake. Nevertheless, this would further increase the mismatch between observed and modelled CO2 growth rate during the CO2 plateau epoch. Tests performed using the OSCAR (v2.2) model indicate that changes in land use not correctly accounted for during the period (coinciding with drastic socioeconomic changes during the Second World War) could contribute to the additional sink required. Thus, the previously proposed ocean hypothesis for the 1940s plateau cannot be confirmed by independent data. Further efforts are required to reduce uncertainty in the different terms of the carbon budget during the first half of the 20th century and to better understand the long-term variability of the ocean and terrestrial CO2 sinks.
Published: 2016

22. Unexpectedly large impact of forest management and grazing on global vegetation biomass

Author: Maria Niedertscheider, Christian Lauk, Nuno Carvalhais, Thomas Kastner, Sebastiaan Luyssaert, Karl-Heinz Erb, Helmut Haberl, Martin Thurner, Tamara Fetzel, Anna Liza S. Bais, Simone Gingrich, Julia Pongratz, Christoph Plutzar, and Systems Ecology
Subjects: Carbon Sequestration, Conservation of Natural Resources, Internationality, 010504 meteorology & atmospheric sciences, Forest management, Land management, Climate change, Land cover, Forests, 010501 environmental sciences, Carbon sequestration, Global Warming, 01 natural sciences, Trees, Tropical climate, Journal Article, Animals, Human Activities, Biomass, Animal Husbandry, Stock (geology), 0105 earth and related environmental sciences, SDG 15 - Life on Land, Tropical Climate, Multidisciplinary, Land use, Agroforestry, Uncertainty, Forestry, Plants, 15. Life on land, Carbon, 13. Climate action, Environmental science
Abstract: Carbon stocks in vegetation have a key role in the climate system. However, the magnitude, patterns and uncertainties of carbon stocks and the effect of land use on the stocks remain poorly quantified. Here we show, using state-of-the-art datasets, that vegetation currently stores around 450 petagrams of carbon. In the hypothetical absence of land use, potential vegetation would store around 916 petagrams of carbon, under current climate conditions. This difference highlights the massive effect of land use on biomass stocks. Deforestation and other land-cover changes are responsible for 53-58% of the difference between current and potential biomass stocks. Land management effects (the biomass stock changes induced by land use within the same land cover) contribute 42-47%, but have been underestimated in the literature. Therefore, avoiding deforestation is necessary but not sufficient for mitigation of climate change. Our results imply that trade-offs exist between conserving carbon stocks on managed land and raising the contribution of biomass to raw material and energy supply for the mitigation of climate change. Efforts to raise biomass stocks are currently verifiable only in temperate forests, where their potential is limited. By contrast, large uncertainties hinder verification in the tropical forest, where the largest potential is located, pointing to challenges for the upcoming stocktaking exercises under the Paris agreement.
Published: 2018

23. Evaluating the Interplay Between Biophysical Processes and Leaf Area Changes in Land Surface Models

Author: Gregory Duveiller, Giovanni Forzieri, Peter Anthoni, Alessandro Cescatti, Philippe Ciais, Wei Li, Eddy Robertson, Lorea Garcia-San Martin, Peter Lawrence, Julia Pongratz, Goran Georgievski, Andy Wiltshire, Almut Arneth, Markus Kautz, Stephen Sitch, European Commission - Joint Research Centre [Ispra] (JRC), Earth and Life Institute [Louvain-La-Neuve] (ELI), Université Catholique de Louvain = Catholic University of Louvain (UCL), Brandenburg University of Technology [Cottbus – Senftenberg] (BTU), PHysicochimie des Electrolytes et Nanosystèmes InterfaciauX (PHENIX), Institut de Chimie du CNRS (INC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Karlsruhe Institute of Technology (KIT), Groupe Immunité des Muqueuses et Agents Pathogènes (GIMAP), Université Jean Monnet - Saint-Étienne (UJM), 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)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ICOS-ATC (ICOS-ATC), 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), Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, University of Exeter, Fitzroy Road, Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT), Institute for the Environment and Sustainability, Université Jean Monnet [Saint-Étienne] (UJM), 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), and 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)
Subjects: 010504 meteorology & atmospheric sciences, LUC4C, 0208 environmental biotechnology, Biome, Process representation, 02 engineering and technology, Sensible heat, Biogeosciences, Atmospheric sciences, 01 natural sciences, Ecosystems, Structure, Dynamics, and Modeling, Surface energy balance, Remote Sensing, Surface energy flux, Oceanography: Biological and Chemical, Land/Atmosphere Interactions, biophysics, Temperate climate, ddc:550, Environmental Chemistry, Biogeophysics, Global Change, Geodesy and Gravity, Leaf area index, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Research Articles, satellite data, 0105 earth and related environmental sciences, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Global and Planetary Change, leaf area index, surface energy balance, land‐atmosphere interactions, 15. Life on land, 020801 environmental engineering, Earth sciences, Mass Balance, Ecosystems, Structure and Dynamics, 13. Climate action, Atmospheric Processes, land surface models, Biophysical Process, General Earth and Planetary Sciences, Environmental science, Hydrology, Research Article
Abstract: Land Surface Models (LSMs) are essential to reproduce biophysical processes modulated by vegetation and to predict the future evolution of the land‐climate system. To assess the performance of an ensemble of LSMs (JSBACH, JULES, ORCHIDEE, CLM, and LPJ‐GUESS) a consistent set of land surface energy fluxes and leaf area index (LAI) has been generated. Relationships of interannual variations of modeled surface fluxes and LAI changes have been analyzed at global scale across climatological gradients and compared with those obtained from satellite‐based products. Model‐specific strengths and deficiencies were diagnosed for tree and grass biomes. Results show that the responses of grasses are generally well represented in models with respect to the observed interplay between turbulent fluxes and LAI, increasing the confidence on how the LAI‐dependent partition of net radiation into latent and sensible heat are simulated. On the contrary, modeled forest responses are characterized by systematic bias in the relation between the year‐to‐year variability in LAI and net radiation in cold and temperate climates, ultimately affecting the amount of absorbed radiation due to LAI‐related effects on surface albedo. In addition, for tree biomes, the relationships between LAI and turbulent fluxes appear to contradict the experimental evidences. The dominance of the transpiration‐driven over the observed albedo‐driven effects might suggest that LSMs have the incorrect balance of these two processes. Such mismatches shed light on the limitations of our current understanding and process representation of the vegetation control on the surface energy balance and help to identify critical areas for model improvement., Key Points The covariability of land biophysics and changes in vegetation density predicted by Land Surface Models is compared with satellite dataBiophysical properties of vegetation are explored across climatological gradients of temperature and precipitationModel‐specific and systematic strengths and deficiencies are diagnosed separately for tree and grass biomes
Published: 2018

24. Modeling past human-induced vegetation change is a challenge – the case of Europe

Author: Marie-José Gaillard, Anne Dallmeyer, Anneli Poska, Laurent Marquer, Benjamin Smith, and Julia Pongratz
Subjects: 010506 paleontology, Land use, Ecological succession, 15. Life on land, 010502 geochemistry & geophysics, 01 natural sciences, Vegetation types, 13. Climate action, medicine, Environmental science, Physical geography, medicine.symptom, Vegetation (pathology), 0105 earth and related environmental sciences
Abstract: Differences between pollen-based reconstructions and dynamic vegetation simulations of past vegetation change in Europe over the last seven millennia are interpreted as being due primarily to land-use change. Incorporating land use in climate and dynamic vegetation models requires new approaches.
Published: 2018

25. Biophysics and vegetation cover change: a process-based evaluation framework for confronting land surface models with satellite observations

Author: Stephen Sitch, Peter Lawrence, Andy Wiltshire, Eddy Robertson, Almut Arneth, Alessandro Cescatti, Julia Pongratz, Goran Georgievski, Giovanni Forzieri, Philippe Ciais, Gregory Duveiller, Wei Li, European Commission - Joint Research Centre [Ispra] (JRC), Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Max-Planck-Institut für Meteorologie (MPI-M), Max-Planck-Gesellschaft, National Center for Atmospheric Research [Boulder] (NCAR), 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), Max Planck Institute for Meteorology (MPI-M), University of Exeter, Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT), 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: 010504 meteorology & atmospheric sciences, 0208 environmental biotechnology, Magnitude (mathematics), 02 engineering and technology, Land cover, 010502 geochemistry & geophysics, 01 natural sciences, Radiative transfer, medicine, Robustness (economics), [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, lcsh:Environmental sciences, 0105 earth and related environmental sciences, lcsh:GE1-350, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Land use, lcsh:QE1-996.5, Vegetation, Seasonality, 15. Life on land, medicine.disease, 020801 environmental engineering, lcsh:Geology, 13. Climate action, Climatology, General Earth and Planetary Sciences, Environmental science, Satellite
Abstract: Land use and land cover change (LULCC) alter the biophysical properties of the Earth's surface. The associated changes in vegetation cover can perturb the local surface energy balance, which in turn can affect the local climate. The sign and magnitude of this change in climate depends on the specific vegetation transition, its timing and its location, as well as on the background climate. Land surface models (LSMs) can be used to simulate such land–climate interactions and study their impact in past and future climates, but their capacity to model biophysical effects accurately across the globe remain unclear due to the complexity of the phenomena. Here we present a framework to evaluate the performance of such models with respect to a dedicated dataset derived from satellite remote sensing observations. Idealized simulations from four LSMs (JULES, ORCHIDEE, JSBACH and CLM) are combined with satellite observations to analyse the changes in radiative and turbulent fluxes caused by 15 specific vegetation cover transitions across geographic, seasonal and climatic gradients. The seasonal variation in net radiation associated with land cover change is the process that models capture best, whereas LSMs perform poorly when simulating spatial and climatic gradients of variation in latent, sensible and ground heat fluxes induced by land cover transitions. We expect that this analysis will help identify model limitations and prioritize efforts in model development as well as inform where consensus between model and observations is already met, ultimately helping to improve the robustness and consistency of model simulations to better inform land-based mitigation and adaptation policies. The dataset consisting of both harmonized model simulation and remote sensing estimations is available at https://doi.org/10.5281/zenodo.1182145.
Published: 2018

26. Models meet data: Challenges and opportunities in implementing land management in Earth system models

Author: Patrick Meyfroidt, Martin Herold, Julia Pongratz, Karl-Heinz Erb, Tobias Kuemmerle, Axel Don, Han Dolman, Kim Naudts, Sebastiaan Luyssaert, Chris D. Jones, and Richard Fuchs
Subjects: Conservation of Natural Resources, Earth observation, 010504 meteorology & atmospheric sciences, Earth, Planet, Process (engineering), Computer science, Climate Change, Land management, 01 natural sciences, Laboratory of Geo-information Science and Remote Sensing, Earth observations, Agricultural land, Environmental Chemistry, Land use, land-use change and forestry, grazing, Laboratorium voor Geo-informatiekunde en Remote Sensing, SDG 2 - Zero Hunger, Implementation, climate, Ecosystem, 0105 earth and related environmental sciences, General Environmental Science, SDG 15 - Life on Land, Global and Planetary Change, Research Reviews, Ecology, Land use, business.industry, Environmental resource management, Research Review, forestry, land management, land use, 04 agricultural and veterinary sciences, Earth system models, Models, Theoretical, 15. Life on land, PE&RC, croplands, Earth system science, 13. Climate action, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, business
Abstract: As the applications of Earth system models (ESMs) move from general climate projections toward questions of mitigation and adaptation, the inclusion of land management practices in these models becomes crucial. We carried out a survey among modeling groups to show an evolution from models able only to deal with land‐cover change to more sophisticated approaches that allow also for the partial integration of land management changes. For the longer term a comprehensive land management representation can be anticipated for all major models. To guide the prioritization of implementation, we evaluate ten land management practices—forestry harvest, tree species selection, grazing and mowing harvest, crop harvest, crop species selection, irrigation, wetland drainage, fertilization, tillage, and fire—for (1) their importance on the Earth system, (2) the possibility of implementing them in state‐of‐the‐art ESMs, and (3) availability of required input data. Matching these criteria, we identify “low‐hanging fruits” for the inclusion in ESMs, such as basic implementations of crop and forestry harvest and fertilization. We also identify research requirements for specific communities to address the remaining land management practices. Data availability severely hampers modeling the most extensive land management practice, grazing and mowing harvest, and is a limiting factor for a comprehensive implementation of most other practices. Inadequate process understanding hampers even a basic assessment of crop species selection and tillage effects. The need for multiple advanced model structures will be the challenge for a comprehensive implementation of most practices but considerable synergy can be gained using the same structures for different practices. A continuous and closer collaboration of the modeling, Earth observation, and land system science communities is thus required to achieve the inclusion of land management in ESMs.
Published: 2018

27. Asymmetric responses of primary productivity to altered precipitation simulated by ecosystem models across three long-term grassland sites

Author: Simone Fatichi, Nicolas Viovy, Yiqi Luo, Yongwen Liu, Ying-Ping Wang, Yue He, Almut Arneth, Julia Pongratz, Donghai Wu, Julia Nabel, Daniel M. Ricciuto, Stephen Sitch, Sebastian Sippel, Qiuan Zhu, Akihiko Ito, Philippe Ciais, Johannes Ingrisch, Hélène Genet, Michael Schmitt, Alan K. Knapp, Athanasios Paschalis, Changhui Peng, Anna B. Harper, David Reinthaler, Shilong Piao, Kevin R. Wilcox, Xiaoying Shi, Lena Boysen, Anna M. Ukkola, Hanqin Tian, Sara Vicca, Michael Bahn, Jiafu Mao, Markus Kautz, Guangsheng Chen, Benjamin Poulter, Jakob Zscheischler, Melinda D. Smith, Roland Hasibeder, Patrick Meir, Xiangyi Li, Shree R. S. Dangal, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University [Beijing], 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), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Colorado State University [Fort Collins] (CSU), University of Oklahoma (OU), Institute of Ecology, Technische Universität Berlin (TU), Department of Biology, Centre of Excellence PLECO (Plant and Vegetation Ecology), University of Antwerp (UA), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft, University of California [San Francisco] (UCSF), University of California, National Institute for Environmental Studies (NIES), Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT), Université du Québec à Trois-Rivières (UQTR), Environmental Sciences Division [Oak Ridge], Oak Ridge National Laboratory [Oak Ridge] (ORNL), UT-Battelle, LLC-UT-Battelle, LLC, Northeast Forestry University, Shandong Agricultural University (SDAU), Institute of Arctic Biology, University of Alaska [Anchorage], Centre Hospitalier de l'Université de Montréal (CHUM), Université de Montréal (UdeM), Max Planck Institute for Meteorology (MPI-M), Department of Global Ecology [Carnegie] (DGE), Carnegie Institution for Science [Washington], Karlsruhe Institute of Technology (KIT), University of Innsbruck, Research School of Biology [Canberra, Australia], Australian National University (ANU), Northwest A and F University, Institute for Atmospheric and Climate Science [Zürich] (IAC), Auburn University (AU), Exeter Climate Systems, University of Exeter, Exeter, United Kingdom, Climate Change Science Institute [Oak Ridge] (CCSI), CSIRO Marine and Atmospheric Research [Aspendale], Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Department of Microbiology and Plant Biology, Environnement de Réseaux Autonomes (ERA), Institut Charles Delaunay (ICD), Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS)-Université de Technologie de Troyes (UTT)-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), Technical University of Berlin / Technische Universität Berlin (TU), University of California [San Francisco] (UC San Francisco), University of California (UC), Northeast Forestry University (NEFU), University of Alaska [Fairbanks] (UAF), Carnegie Institution for Science, Leopold Franzens Universität Innsbruck - University of Innsbruck, and University of Exeter
Subjects: 0106 biological sciences, 010504 meteorology & atmospheric sciences, Steppe, Geography & travel, 04 Earth Sciences, 05 Environmental Sciences, lcsh:Life, Atmospheric sciences, 010502 geochemistry & geophysics, 010603 evolutionary biology, 01 natural sciences, Grassland, lcsh:QH540-549.5, Meteorology & Atmospheric Sciences, Ecosystem, Precipitation, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Biology, Ecology, Evolution, Behavior and Systematics, Primary productivity, Earth-Surface Processes, 0105 earth and related environmental sciences, ddc:910, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, geography, geography.geographical_feature_category, Physics, Simulation modeling, lcsh:QE1-996.5, Primary production, 06 Biological Sciences, 15. Life on land, lcsh:Geology, lcsh:QH501-531, Chemistry, Productivity (ecology), 13. Climate action, Environmental science, lcsh:Ecology
Abstract: Field measurements of aboveground net primary productivity (ANPP) in temperate grasslands suggest that both positive and negative asymmetric responses to changes in precipitation (P) may occur. Under normal range of precipitation variability, wet years typically result in ANPP gains being larger than ANPP declines in dry years (positive asymmetry), whereas increases in ANPP are lower in magnitude in extreme wet years compared to reductions during extreme drought (negative asymmetry). Whether the current generation of ecosystem models with a coupled carbon–water system in grasslands are capable of simulating these asymmetric ANPP responses is an unresolved question. In this study, we evaluated the simulated responses of temperate grassland primary productivity to scenarios of altered precipitation with 14 ecosystem models at three sites: Shortgrass steppe (SGS), Konza Prairie (KNZ) and Stubai Valley meadow (STU), spanning a rainfall gradient from dry to moist. We found that (1) the spatial slopes derived from modeled primary productivity and precipitation across sites were steeper than the temporal slopes obtained from inter-annual variations, which was consistent with empirical data; (2) the asymmetry of the responses of modeled primary productivity under normal inter-annual precipitation variability differed among models, and the mean of the model ensemble suggested a negative asymmetry across the three sites, which was contrary to empirical evidence based on filed observations; (3) the mean sensitivity of modeled productivity to rainfall suggested greater negative response with reduced precipitation than positive response to an increased precipitation under extreme conditions at the three sites; and (4) gross primary productivity (GPP), net primary productivity (NPP), aboveground NPP (ANPP) and belowground NPP (BNPP) all showed concave-down nonlinear responses to altered precipitation in all the models, but with different curvatures and mean values. Our results indicated that most models overestimate the negative drought effects and/or underestimate the positive effects of increased precipitation on primary productivity under normal climate conditions, highlighting the need for improving eco-hydrological processes in those models in the future.
Published: 2018

28. Land-use and land-cover change carbon emissions between 1901 and 2012 constrained by biomass observations

Author: Nuno Carvalhais, Philippe Ciais, Nicolas Viovy, Thomas A. M. Pugh, Benjamin Poulter, Julia Pongratz, Martin Thurner, Maurizio Santoro, Benjamin D. Stocker, Rasoul Yousefpour, Julia E. M. S. Nabel, Andy Wiltshire, Yude Pan, Soenke Zaehle, Etsushi Kato, Stephen Sitch, Valerio Avitabile, Yi Y. Liu, Almut Arneth, Wei Li, Charles D. Koven, Yilong Wang, Sassan Saatchi, Anna B. Harper, Chao Yue, Shushi Peng, 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), Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), Institute on Ecosystems and Department of Ecology [Bozeman], Montana State University (MSU), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
Subjects: 0106 biological sciences, Meteorology, 010504 meteorology & atmospheric sciences, lcsh:Life, Land cover, Atmospheric sciences, 010603 evolutionary biology, 01 natural sciences, 7. Clean energy, Laboratory of Geo-information Science and Remote Sensing, lcsh:QH540-549.5, ddc:550, Range (statistics), Life Science, Laboratorium voor Geo-informatiekunde en Remote Sensing, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Ecology, Evolution, Behavior and Systematics, ComputingMilieux_MISCELLANEOUS, Earth-Surface Processes, 0105 earth and related environmental sciences, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Biomass (ecology), Land use, lcsh:QE1-996.5, Vegetation, 04 agricultural and veterinary sciences, 15. Life on land, PE&RC, Constraint (information theory), lcsh:Geology, Earth sciences, lcsh:QH501-531, 13. Climate action, Greenhouse gas, 040103 agronomy & agriculture, Environmental science, 0401 agriculture, forestry, and fisheries, lcsh:Ecology, Scale (map)
Abstract: The use of dynamic global vegetation models (DGVMs) to estimate CO2 emissions from land-use and land-cover change (LULCC) offers a new window to account for spatial and temporal details of emissions and for ecosystem processes affected by LULCC. One drawback of LULCC emissions from DGVMs, however, is lack of observation constraint. Here, we propose a new method of using satellite- and inventory-based biomass observations to constrain historical cumulative LULCC emissions (ELUCc) from an ensemble of nine DGVMs based on emerging relationships between simulated vegetation biomass and ELUCc. This method is applicable on the global and regional scale. The original DGVM estimates of ELUCc range from 94 to 273 PgC during 1901–2012. After constraining by current biomass observations, we derive a best estimate of 155 ± 50 PgC (1σ Gaussian error). The constrained LULCC emissions are higher than prior DGVM values in tropical regions but significantly lower in North America. Our emergent constraint approach independently verifies the median model estimate by biomass observations, giving support to the use of this estimate in carbon budget assessments. The uncertainty in the constrained ELUCc is still relatively large because of the uncertainty in the biomass observations, and thus reduced uncertainty in addition to increased accuracy in biomass observations in the future will help improve the constraint. This constraint method can also be applied to evaluate the impact of land-based mitigation activities.
Published: 2017

29. 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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30. Land management: data availability and process understanding for global change studies

Author: Aude Valade, Ian McCallum, Erika Marin-Spiotta, Eddy Robertson, Chris D. Jones, Verena Seufert, Martin Herold, Axel Don, Richard Fuchs, Patrick Meyfroidt, Tobias Kuemmerle, Karl-Heinz Erb, Steffen Fritz, Andy Wiltshire, Silvia Kloster, Sebastiaan Luyssaert, Tamara Fetzel, Helmut Haberl, Julia Pongratz, A. J. Dolman, 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)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), 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), Systems Ecology, and Earth and Climate
Subjects: Conservation of Natural Resources, 010504 meteorology & atmospheric sciences, Climate Change, Land management, land-cover modification, 01 natural sciences, Trees, global land-use data sets, Laboratory of Geo-information Science and Remote Sensing, SDG 13 - Climate Action, Environmental Chemistry, Laboratorium voor Geo-informatiekunde en Remote Sensing, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, data availability, Ecosystem, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, General Environmental Science, 2. Zero hunger, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Global and Planetary Change, Food security, Ecology, business.industry, Environmental resource management, land management, Global change, 04 agricultural and veterinary sciences, Biodiversity, 15. Life on land, PE&RC, Earth system science, Knowledge base, 13. Climate action, Human resource management, process understanding, Sustainability, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science, business, Common land, earth system models
Abstract: In the light of daunting global sustainability challenges such as climate change, biodiversity loss and food security, improving our understanding of the complex dynamics of the Earth system is crucial. However, large knowledge gaps related to the effects of land management persist, in particular those human-induced changes in terrestrial ecosystems that do not result in land-cover conversions. Here, we review the current state of knowledge of ten common land management activities for their biogeochemical and biophysical impacts, the level of process understanding and data availability. Our review shows that ca. one-tenth of the ice-free land surface is under intense human management, half under medium and one-fifth under extensive management. Based on our review, we cluster these ten management activities into three groups: (i) management activities for which data sets are available, and for which a good knowledge base exists (cropland harvest and irrigation); (ii) management activities for which sufficient knowledge on biogeochemical and biophysical effects exists but robust global data sets are lacking (forest harvest, tree species selection, grazing and mowing harvest, N fertilization); and (iii) land management practices with severe data gaps concomitant with an unsatisfactory level of process understanding (crop species selection, artificial wetland drainage, tillage and fire management and crop residue management, an element of crop harvest). Although we identify multiple impediments to progress, we conclude that the current status of process understanding and data availability is sufficient to advance with incorporating management in, for example, Earth system or dynamic vegetation models in order to provide a systematic assessment of their role in the Earth system. This review contributes to a strategic prioritization of research efforts across multiple disciplines, including land system research, ecological research and Earth system modelling.
Published: 2017

31. The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: Rationale and experimental design

Author: Almut Arneth, Sonia I. Seneviratne, Julia Pongratz, Victor Brovkin, Nathalie de Noblet-Ducoudré, Peter Lawrence, George C. Hurtt, Andrew D. Jones, Elena Shevliakova, Katherine Calvin, David M. Lawrence, Chris D. Jones, 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: 010504 meteorology & atmospheric sciences, Meteorology, Life on Land, media_common.quotation_subject, 0208 environmental biotechnology, Land management, Climate change, Context (language use), 02 engineering and technology, Land use model, 01 natural sciences, 7. Clean energy, C4MIP, ddc:550, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Sophistication, 0105 earth and related environmental sciences, media_common, Protocol (science), [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Land use, business.industry, Environmental resource management, lcsh:QE1-996.5, General Medicine, 15. Life on land, 020801 environmental engineering, lcsh:Geology, Climate Action, 13. Climate action, Earth Sciences, Environmental science, business
Abstract: International audience; Abstract. Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the following questions. (1) What are the effects of LULCC on climate and biogeochemical cycling (past–future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy, and are there regional land-management strategies with the promise to help mitigate climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land use, the unique impacts of land-cover change vs. land-management change, modulation of land-use impact on climate by land–atmosphere coupling strength, and the extent to which impacts of enhanced CO2 concentrations on plant photosynthesis are modulated by past and future land use.LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use data set, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to LULCC. In this paper, we describe LUMIP activity (2), i.e., the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes a two-phase experimental design. Phase one features idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential land-cover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible and clearly report how the model experiments were executed.
Published: 2016

32. 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

33. 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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33 results on '"Julia Pongratz"'

1. Slowdown of the greening trend in natural vegetation with further rise in atmospheric CO2

2. Modelled land use and land cover change emissions – a spatio-temporal comparison of different approaches

3. Global Carbon Budget 2021

4. Dynamic global vegetation models underestimate net CO2 flux mean and interannual variability in dryland ecosystems

5. A multi-data assessment of land use and land cover emissions from Brazil during 2000-2019

6. Five years of variability in the global carbon cycle: comparing an estimate from the Orbiting Carbon Observatory-2 and process-based models

7. Slow-down of the greening trend in natural vegetation with further rise in atmospheric CO2

8. Empirical estimates of regional carbon budgets imply reduced global soil heterotrophic respiration

9. The consolidated European synthesis of CO2 emissions and removals for the European Union and United Kingdom: 1990–2018

10. Integrating the evidence for a terrestrial carbon sink caused by increasing atmospheric CO2

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

12. The consolidated European synthesis of CO2 emissions and removals for EU27 and UK: 1990–2018

13. Decadal variability in land carbon sink efficiency

14. European anthropogenic AFOLU greenhouse gas emissions:a review and benchmark data

15. Increased control of vegetation on global terrestrial energy fluxes

16. Sources of Uncertainty in Regional and Global Terrestrial CO 2 Exchange Estimates

17. Rainfall manipulation experiments as simulated by terrestrial biosphere models : where do we stand?

18. Direct and seasonal legacy effects of the 2018 heat wave and drought on European ecosystem productivity

19. Forest production efficiency increases with growth temperature

20. Soil carbon sequestration simulated in CMIP6-LUMIP models: implications for climatic mitigation

21. Re-evaluating the 1940s CO2 plateau

22. Unexpectedly large impact of forest management and grazing on global vegetation biomass

23. Evaluating the Interplay Between Biophysical Processes and Leaf Area Changes in Land Surface Models

24. Modeling past human-induced vegetation change is a challenge – the case of Europe

25. Biophysics and vegetation cover change: a process-based evaluation framework for confronting land surface models with satellite observations

26. Models meet data: Challenges and opportunities in implementing land management in Earth system models

27. Asymmetric responses of primary productivity to altered precipitation simulated by ecosystem models across three long-term grassland sites

28. Land-use and land-cover change carbon emissions between 1901 and 2012 constrained by biomass observations

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

30. Land management: data availability and process understanding for global change studies

31. The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: Rationale and experimental design

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

33. Etsushi Kato 29 , Markus Kautz 30 , Ralph F. Keeling 31

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