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2. Warming response of peatland CO2 sink is sensitive to seasonality in warming trends

Author

Helbig, M., Živković, T., Alekseychik, P., Aurela, M., El-Madany, T. S., Euskirchen, E. S., Flanagan, L. B., Griffis, T. J., Hanson, P. J., Hattakka, J., Helfter, C., Hirano, T., Humphreys, E. R., Kiely, G., Kolka, R. K., Laurila, T., Leahy, P. G., Lohila, A., Mammarella, I., Nilsson, M. B., Panov, A., Parmentier, F. J. W., Peichl, M., Rinne, J., Roman, D. T., Sonnentag, O., Tuittila, E.-S, Ueyama, M., Vesala, T., Vestin, P., Weldon, S., Weslien, P., and Zaehle, S.

Published
2022
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3. Biodiversity and Climate Extremes: Known Interactions and Research Gaps

Author

Mahecha, M. D., primary, Bastos, A., additional, Bohn, F. J., additional, Eisenhauer, N., additional, Feilhauer, H., additional, Hickler, T., additional, Kalesse‐Los, H., additional, Migliavacca, M., additional, Otto, F. E. L., additional, Peng, J., additional, Sippel, S., additional, Tegen, I., additional, Weigelt, A., additional, Wendisch, M., additional, Wirth, C., additional, Al‐Halbouni, D., additional, Deneke, H., additional, Doktor, D., additional, Dunker, S., additional, Duveiller, G., additional, Ehrlich, A., additional, Foth, A., additional, García‐García, A., additional, Guerra, C. A., additional, Guimarães‐Steinicke, C., additional, Hartmann, H., additional, Henning, S., additional, Herrmann, H., additional, Hu, P., additional, Ji, C., additional, Kattenborn, T., additional, Kolleck, N., additional, Kretschmer, M., additional, Kühn, I., additional, Luttkus, M. L., additional, Maahn, M., additional, Mönks, M., additional, Mora, K., additional, Pöhlker, M., additional, Reichstein, M., additional, Rüger, N., additional, Sánchez‐Parra, B., additional, Schäfer, M., additional, Stratmann, F., additional, Tesche, M., additional, Wehner, B., additional, Wieneke, S., additional, Winkler, A. J., additional, Wolf, S., additional, Zaehle, S., additional, Zscheischler, J., additional, and Quaas, J., additional

Published
2024
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4. Amazon forest response to CO2 fertilization dependent on plant phosphorus acquisition

Author

Fleischer, K, Rammig, A, De Kauwe, MG, Walker, AP, Domingues, TF, Fuchslueger, L, Garcia, S, Goll, DS, Grandis, A, Jiang, M, Haverd, V, Hofhansl, F, Holm, JA, Kruijt, B, Leung, F, Medlyn, BE, Mercado, LM, Norby, RJ, Pak, B, von Randow, C, Quesada, CA, Schaap, KJ, Valverde-Barrantes, OJ, Wang, YP, Yang, X, Zaehle, S, Zhu, Q, and Lapola, DM

Subjects
MD Multidisciplinary, Meteorology & Atmospheric Sciences
Abstract

Global terrestrial models currently predict that the Amazon rainforest will continue to act as a carbon sink in the future, primarily owing to the rising atmospheric carbon dioxide (CO2) concentration. Soil phosphorus impoverishment in parts of the Amazon basin largely controls its functioning, but the role of phosphorus availability has not been considered in global model ensembles—for example, during the Fifth Climate Model Intercomparison Project. Here we simulate the planned free-air CO2 enrichment experiment AmazonFACE with an ensemble of 14 terrestrial ecosystem models. We show that phosphorus availability reduces the projected CO2-induced biomass carbon growth by about 50% to 79 ± 63 g C m−2 yr−1 over 15 years compared to estimates from carbon and carbon–nitrogen models. Our results suggest that the resilience of the region to climate change may be much less than previously assumed. Variation in the biomass carbon response among the phosphorus-enabled models is considerable, ranging from 5 to 140 g C m−2 yr−1, owing to the contrasting plant phosphorus use and acquisition strategies considered among the models. The Amazon forest response thus depends on the interactions and relative contributions of the phosphorus acquisition and use strategies across individuals, and to what extent these processes can be upregulated under elevated CO2.

Published
2019

7. A belowground perspective on the nexus between biodiversity change, climate change, and human well-being

Author

Eisenhauer, N., Frank, Karin, Weigelt, A., Bartkowski, Bartosz, Beugnon, R., Liebal, K., Mahecha, M., Quaas, M., Al-Halbouni, D., Bastos, A., Bohn, Friedrich, de Brito, Mariana Madruga, Denzler, J., Feilhauer, H., Fischer, R., Fritsche, I., Guimaraes-Steinicke, C., Hänsel, M., Haun, D.B.M., Herrmann, H., Huth, Andreas, Kalesse-Los, H., Koetter, M., Kolleck, N., Krause, M., Kretschmer, M., Leitão, P.J., Masson, T., Mora, K., Müller, Birgit, Peng, Jian, Pöhlker, M.L., Ratzke, L., Reichstein, M., Richter, S., Rüger, N., Sánchez-Parra, B., Shadaydeh, M., Sippel, S., Tegen, I., Thrän, Daniela, Umlauft, J., Wendisch, M., Wolf, K., Wirth, C., Zacher, H., Zaehle, S., Quaas, J., Eisenhauer, N., Frank, Karin, Weigelt, A., Bartkowski, Bartosz, Beugnon, R., Liebal, K., Mahecha, M., Quaas, M., Al-Halbouni, D., Bastos, A., Bohn, Friedrich, de Brito, Mariana Madruga, Denzler, J., Feilhauer, H., Fischer, R., Fritsche, I., Guimaraes-Steinicke, C., Hänsel, M., Haun, D.B.M., Herrmann, H., Huth, Andreas, Kalesse-Los, H., Koetter, M., Kolleck, N., Krause, M., Kretschmer, M., Leitão, P.J., Masson, T., Mora, K., Müller, Birgit, Peng, Jian, Pöhlker, M.L., Ratzke, L., Reichstein, M., Richter, S., Rüger, N., Sánchez-Parra, B., Shadaydeh, M., Sippel, S., Tegen, I., Thrän, Daniela, Umlauft, J., Wendisch, M., Wolf, K., Wirth, C., Zacher, H., Zaehle, S., and Quaas, J.

Abstract

Soil is central to the complex interplay among biodiversity, climate, and society. This paper examines the interconnectedness of soil biodiversity, climate change, and societal impacts, emphasizing the urgent need for integrated solutions. Human-induced biodiversity loss and climate change intensify environmental degradation, threatening human well-being. Soils, rich in biodiversity and vital for ecosystem function regulation, are highly vulnerable to these pressures, affecting nutrient cycling, soil fertility, and resilience. Soil also crucially regulates climate, influencing energy, water cycles, and carbon storage. Yet, climate change poses significant challenges to soil health and carbon dynamics, amplifying global warming. Integrated approaches are essential, including sustainable land management, policy interventions, technological innovations, and societal engagement. Practices like agroforestry and organic farming improve soil health and mitigate climate impacts. Effective policies and governance are crucial for promoting sustainable practices and soil conservation. Recent technologies aid in monitoring soil biodiversity and implementing sustainable land management. Societal engagement, through education and collective action, is vital for environmental stewardship. By prioritizing interdisciplinary research and addressing key frontiers, scientists can advance understanding of the soil biodiversity–climate change–society nexus, informing strategies for environmental sustainability and social equity.

Published
2024

8. Biodiversity and climate extremes: known interactions and research gaps

Author

Mahecha, Miguel Dario, Bastos, A., Bohn, Friedrich, Eisenhauer, N., Feilhauer, Hannes, Hickler, T., Kalesse-Los, H., Migliavacca, M., Otto, F.E.L., Peng, Jian, Sippel, S., Tegen, I., Weigelt, A., Wendisch, M., Wirth, C., Al-Halbouni, D., Deneke, H.M., Doktor, Daniel, Dunker, Susanne, Duveiller, G., Ehrlich, A., Foth, A., García-García, Almudena, Guerra, C.A., Guimarães- Steinicke, C., Hartmann, H., Henning, S., Herrmann, H., Hu, P., Ji, C., Kattenborn, T., Kolleck, N., Kretschmer, M., Kühn, Ingolf, Luttkus, M.L., Maahn, M., Mönks, M., Mora, K., Pöhlker, M., Reichstein, M., Rüger, N., Sánchez-Parra, B., Schäfer, M., Stratmann, F., Tesche, M., Wehner, B., Wieneke, S., Winkler, A.J., Wolf, S., Zaehle, S., Zscheischler, Jakob, Quaas, J., Mahecha, Miguel Dario, Bastos, A., Bohn, Friedrich, Eisenhauer, N., Feilhauer, Hannes, Hickler, T., Kalesse-Los, H., Migliavacca, M., Otto, F.E.L., Peng, Jian, Sippel, S., Tegen, I., Weigelt, A., Wendisch, M., Wirth, C., Al-Halbouni, D., Deneke, H.M., Doktor, Daniel, Dunker, Susanne, Duveiller, G., Ehrlich, A., Foth, A., García-García, Almudena, Guerra, C.A., Guimarães- Steinicke, C., Hartmann, H., Henning, S., Herrmann, H., Hu, P., Ji, C., Kattenborn, T., Kolleck, N., Kretschmer, M., Kühn, Ingolf, Luttkus, M.L., Maahn, M., Mönks, M., Mora, K., Pöhlker, M., Reichstein, M., Rüger, N., Sánchez-Parra, B., Schäfer, M., Stratmann, F., Tesche, M., Wehner, B., Wieneke, S., Winkler, A.J., Wolf, S., Zaehle, S., Zscheischler, Jakob, and Quaas, J.

Abstract

Climate extremes are on the rise. Impacts of extreme climate and weather events on ecosystem services and ultimately human well-being can be partially attenuated by the organismic, structural, and functional diversity of the affected land surface. However, the ongoing transformation of terrestrial ecosystems through intensified exploitation and management may put this buffering capacity at risk. Here, we summarise the evidence that reductions in biodiversity can destabilise the functioning of ecosystems facing climate extremes. We then explore if impaired ecosystem functioning could, in turn, exacerbate climate extremes. We argue that only a comprehensive approach, incorporating both ecological and hydrometeorological perspectives, enables to understand and predict the entire feedback system between altered biodiversity and climate extremes. This ambition, however, requires a reformulation of current research priorities to emphasise the bidirectional effects that link ecology and atmospheric processes.

Published
2024

9. Role of CO2, climate and land use in regulating the seasonal amplitude increase of carbon fluxes in terrestrial ecosystems: A multimodel analysis

Author

Zhao, F, Zeng, N, Asrar, G, Friedlingstein, P, Ito, A, Jain, A, Kalnay, E, Kato, E, Koven, C, Poulter, B, Rafique, R, Sitch, S, Shu, S, Stocker, B, Viovy, N, Wiltshire, A, and Zaehle, S

Subjects
Meteorology & Atmospheric Sciences, Earth Sciences, Environmental Sciences, Biological Sciences
Abstract

We examined the net terrestrial carbon flux to the atmosphere (FTA) simulated by nine models from the TRENDY dynamic global vegetation model project for its seasonal cycle and amplitude trend during 1961-2012. While some models exhibit similar phase and amplitude compared to atmospheric inversions, with spring drawdown and autumn rebound, others tend to rebound early in summer. The model ensemble mean underestimates the magnitude of the seasonal cycle by 40g% compared to atmospheric inversions. Global FTA amplitude increase (19g±g8g%) and its decadal variability from the model ensemble are generally consistent with constraints from surface atmosphere observations. However, models disagree on attribution of this long-term amplitude increase, with factorial experiments attributing 83g±g56g%, ĝ'3g±g74 and 20g±g30g% to rising CO2, climate change and land use/cover change, respectively. Seven out of the nine models suggest that CO2 fertilization is the strongest control - with the notable exception of VEGAS, which attributes approximately equally to the three factors. Generally, all models display an enhanced seasonality over the boreal region in response to high-latitude warming, but a negative climate contribution from part of the Northern Hemisphere temperate region, and the net result is a divergence over climate change effect. Six of the nine models show that land use/cover change amplifies the seasonal cycle of global FTA: some are due to forest regrowth, while others are caused by crop expansion or agricultural intensification, as revealed by their divergent spatial patterns. We also discovered a moderate cross-model correlation between FTA amplitude increase and increase in land carbon sink (R2 Combining double low line g0.61). Our results suggest that models can show similar results in some benchmarks with different underlying mechanisms; therefore, the spatial traits of CO2 fertilization, climate change and land use/cover changes are crucial in determining the right mechanisms in seasonal carbon cycle change as well as mean sink change.

Published
2016

10. C4MIP-The Coupled Climate-Carbon Cycle Model Intercomparison Project: Experimental protocol for CMIP6

Author

Jones, CD, Arora, V, Friedlingstein, P, Bopp, L, Brovkin, V, Dunne, J, Graven, H, Hoffman, F, Ilyina, T, John, JG, Jung, M, Kawamiya, M, Koven, C, Pongratz, J, Raddatz, T, Randerson, JT, and Zaehle, S

Subjects
Earth Sciences
Abstract

Coordinated experimental design and implementation has become a cornerstone of global climate modelling. Model Intercomparison Projects (MIPs) enable systematic and robust analysis of results across many models, by reducing the influence of ad hoc differences in model set-up or experimental boundary conditions. As it enters its 6th phase, the Coupled Model Intercomparison Project (CMIP6) has grown significantly in scope with the design and documentation of individual simulations delegated to individual climate science communities. The Coupled Climate-Carbon Cycle Model Intercomparison Project (C4MIP) takes responsibility for design, documentation, and analysis of carbon cycle feedbacks and interactions in climate simulations. These feedbacks are potentially large and play a leading-order contribution in determining the atmospheric composition in response to human emissions of CO2 and in the setting of emissions targets to stabilize climate or avoid dangerous climate change. For over a decade, C4MIP has coordinated coupled climate-carbon cycle simulations, and in this paper we describe the C4MIP simulations that will be formally part of CMIP6. While the climate-carbon cycle community has created this experimental design, the simulations also fit within the wider CMIP activity, conform to some common standards including documentation and diagnostic requests, and are designed to complement the CMIP core experiments known as the Diagnostic, Evaluation and Characterization of Klima (DECK). C4MIP has three key strands of scientific motivation and the requested simulations are designed to satisfy their needs: (1) pre-industrial and historical simulations (formally part of the common set of CMIP6 experiments) to enable model evaluation, (2) idealized coupled and partially coupled simulations with 1% per year increases in CO2 to enable diagnosis of feedback strength and its components, (3) future scenario simulations to project how the Earth system will respond to anthropogenic activity over the 21st century and beyond. This paper documents in detail these simulations, explains their rationale and planned analysis, and describes how to set up and run the simulations. Particular attention is paid to boundary conditions, input data, and requested output diagnostics. It is important that modelling groups participating in C4MIP adhere as closely as possible to this experimental design.

Published
2016

11. Greening of the Earth and its drivers

Author

Zhu, Z, Piao, S, Myneni, RB, Huang, M, Zeng, Z, Canadell, JG, Ciais, P, Sitch, S, Friedlingstein, P, Arneth, A, Cao, C, Cheng, L, Kato, E, Koven, C, Li, Y, Lian, X, Liu, Y, Liu, R, Mao, J, Pan, Y, Peng, S, Peuelas, J, Poulter, B, Pugh, TAM, Stocker, BD, Viovy, N, Wang, X, Wang, Y, Xiao, Z, Yang, H, Zaehle, S, and Zeng, N

Subjects
Atmospheric Sciences, Physical Geography and Environmental Geoscience, Environmental Science and Management
Abstract

Global environmental change is rapidly altering the dynamics of terrestrial vegetation, with consequences for the functioning of the Earth system and provision of ecosystem services. Yet how global vegetation is responding to the changing environment is not well established. Here we use three long-term satellite leaf area index (LAI) records and ten global ecosystem models to investigate four key drivers of LAI trends during 1982-2009. We show a persistent and widespread increase of growing season integrated LAI (greening) over 25% to 50% of the global vegetated area, whereas less than 4% of the globe shows decreasing LAI (browning). Factorial simulations with multiple global ecosystem models suggest that CO2 fertilization effects explain 70% of the observed greening trend, followed by nitrogen deposition (9%), climate change (8%) and land cover change (LCC) (4%). CO2 fertilization effects explain most of the greening trends in the tropics, whereas climate change resulted in greening of the high latitudes and the Tibetan Plateau. LCC contributed most to the regional greening observed in southeast China and the eastern United States. The regional effects of unexplained factors suggest that the next generation of ecosystem models will need to explore the impacts of forest demography, differences in regional management intensities for cropland and pastures, and other emerging productivity constraints such as phosphorus availability.

Published
2016

12. Regional carbon fluxes from land use and land cover change in Asia, 1980-2009

Author

Calle, L, Canadell, JG, Patra, P, Ciais, P, Ichii, K, Tian, H, Kondo, M, Piao, S, Arneth, A, Harper, AB, Ito, A, Kato, E, Koven, C, Sitch, S, Stocker, BD, Vivoy, N, Wiltshire, A, Zaehle, S, and Poulter, B

Subjects
Meteorology & Atmospheric Sciences
Abstract

We present a synthesis of the land-atmosphere carbon flux from land use and land cover change (LULCC) in Asia using multiple data sources and paying particular attention to deforestation and forest regrowth fluxes. The data sources are quasi-independent and include the U.N. Food and Agriculture Organization-Forest Resource Assessment (FAO-FRA 2015; country-level inventory estimates), the Emission Database for Global Atmospheric Research (EDGARv4.3), the 'Houghton' bookkeeping model that incorporates FAO-FRA data, an ensemble of 8 state-of-the-art Dynamic Global Vegetation Models (DGVM), and 2 recently published independent studies using primarily remote sensing techniques. The estimates are aggregated spatially to Southeast, East, and South Asia and temporally for three decades, 1980-1989, 1990-1999 and 2000-2009. Since 1980, net carbon emissions from LULCC in Asia were responsible for 20%-40% of global LULCC emissions, with emissions from Southeast Asia alone accounting for 15%-25% of global LULCC emissions during the same period. In the 2000s and for all Asia, three estimates (FAO-FRA, DGVM, Houghton) were in agreement of a net source of carbon to the atmosphere, with mean estimates ranging between 0.24 to 0.41 Pg C yr-1, whereas EDGARv4.3 suggested a net carbon sink of -0.17 Pg C yr-1. Three of 4 estimates suggest that LULCC carbon emissions declined by at least 34% in the preceding decade (1990-2000). Spread in the estimates is due to the inclusion of different flux components and their treatments, showing the importance to include emissions from carbon rich peatlands and land management, such as shifting cultivation and wood harvesting, which appear to be consistently underreported.

Published
2016

13. Comparative carbon cycle dynamics of the present and last interglacial

Author

Brovkin, V, Brücher, T, Kleinen, T, Zaehle, S, Joos, F, Roth, R, Spahni, R, Schmitt, J, Fischer, H, Leuenberger, M, Stone, EJ, Ridgwell, A, Chappellaz, J, Kehrwald, N, Barbante, C, Blunier, T, and Dahl Jensen, D

Subjects
Carbon cycle, Climate, Models, interglacials, The Holocene, The Eemian, Peatland, Fire, Coral reef, Paleontology, Earth Sciences, History and Archaeology
Abstract

Changes in temperature and carbon dioxide during glacial cycles recorded in Antarctic ice cores are tightly coupled. However, this relationship does not hold for interglacials. While climate cooled towards the end of both the last (Eemian) and present (Holocene) interglacials, CO2 remained stable during the Eemian while rising in the Holocene. We identify and review twelve biogeochemical mechanisms of terrestrial (vegetation dynamics and CO2 fertilization, land use, wildfire, accumulation of peat, changes in permafrost carbon, subaerial volcanic outgassing) and marine origin (changes in sea surface temperature, carbonate compensation to deglaciation and terrestrial biosphere regrowth, shallow-water carbonate sedimentation, changes in the soft tissue pump, and methane hydrates), which potentially may have contributed to the CO2 dynamics during interglacials but which remain not well quantified. We use three Earth System Models (ESMs) of intermediate complexity to compare effects of selected mechanisms on the interglacial CO2 and δ13CO2 changes, focusing on those with substantial potential impacts: namely carbonate sedimentation in shallow waters, peat growth, and (in the case of the Holocene) human land use. A set of specified carbon cycle forcings could qualitatively explain atmospheric CO2 dynamics from 8 ka BP to the pre-industrial. However, when applied to Eemian boundary conditions from 126 to 115 ka BP, the same set of forcings led to disagreement with the observed direction of CO2 changes after 122 ka BP. This failure to simulate late-Eemian CO2 dynamics could be a result of the imposed forcings such as prescribed CaCO3 accumulation and/or an incorrect response of simulated terrestrial carbon to the surface cooling at the end of the interglacial. These experiments also reveal that key natural processes of interglacial CO2 dynamics - shallow water CaCO3 accumulation, peat and permafrost carbon dynamics - are not well represented in the current ESMs. Global-scale modeling of these long-term carbon cycle components started only in the last decade, and uncertainty in parameterization of these mechanisms is a main limitation in the successful modeling of interglacial CO2 dynamics.

Published
2016

14. Global Carbon Budget 2015

Author

Le Quéré, C, Moriarty, R, Andrew, RM, Canadell, JG, Sitch, S, Korsbakken, JI, Friedlingstein, P, Peters, GP, Andres, RJ, Boden, TA, Houghton, RA, House, JI, Keeling, RF, Tans, P, Arneth, A, Bakker, DCE, Barbero, L, Bopp, L, Chang, J, Chevallier, F, Chini, LP, Ciais, P, Fader, M, Feely, RA, Gkritzalis, T, Harris, I, Hauck, J, Ilyina, T, Jain, AK, Kato, E, Kitidis, V, Klein Goldewijk, K, Koven, C, Landschützer, P, Lauvset, SK, Lefèvre, N, Lenton, A, Lima, ID, Metzl, N, Millero, F, Munro, DR, Murata, A, S. Nabel, JEM, Nakaoka, S, Nojiri, Y, O'Brien, K, Olsen, A, Ono, T, Pérez, FF, Pfeil, B, Pierrot, D, Poulter, B, Rehder, G, Rödenbeck, C, Saito, S, Schuster, U, Schwinger, J, Séférian, R, Steinhoff, T, Stocker, BD, Sutton, AJ, Takahashi, T, Tilbrook, B, Van Der Laan-Luijkx, IT, Van Der Werf, GR, Van Heuven, S, Vandemark, D, Viovy, N, Wiltshire, A, Zaehle, S, and Zeng, N

Subjects
Atmospheric Sciences, Geochemistry, Physical Geography and Environmental Geoscience
Abstract

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates as well as consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2, and land-cover change (some including nitrogen-carbon interactions). We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2005-2014), EFF was 9.0 ± 0.5 GtC yrg'1, ELUC was 0.9 ± 0.5 GtC yrg'1, GATM was 4.4 ± 0.1 GtC yrg'1, SOCEAN was 2.6 ± 0.5 GtC yrg'1, and SLAND was 3.0 ± 0.8 GtC yrg'1. For the year 2014 alone, EFF grew to 9.8 ± 0.5 GtC yrg'1, 0.6 % above 2013, continuing the growth trend in these emissions, albeit at a slower rate compared to the average growth of 2.2 % yrg'1 that took place during 2005-2014. Also, for 2014, ELUC was 1.1 ± 0.5 GtC yrg'1, GATM was 3.9 ± 0.2 GtC yrg'1, SOCEAN was 2.9 ± 0.5 GtC yrg'1, and SLAND was 4.1 ± 0.9 GtC yrg'1. GATM was lower in 2014 compared to the past decade (2005-2014), reflecting a larger SLAND for that year. The global atmospheric CO2 concentration reached 397.15 ± 0.10 ppm averaged over 2014. For 2015, preliminary data indicate that the growth in EFF will be near or slightly below zero, with a projection of g'0.6 [range of g'1.6 to +0.5] %, based on national emissions projections for China and the USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the global economy for the rest of the world. From this projection of EFF and assumed constant ELUC for 2015, cumulative emissions of CO2 will reach about 555 ± 55 GtC (2035 ± 205 GtCO2) for 1870-2015, about 75 % from EFF and 25 % from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quéré et al., 2015, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP-2015).

Published
2015

16. Reconciling precipitation with runoff: Observed hydrological change in the midlatitudes

Author

Osborne, JM, Lambert, FH, Groenendijk, M, Harper, AB, Koven, CD, Poulter, B, Pugh, TAM, Sitch, S, Stocker, BD, Wiltshire, A, and Zaehle, S

Subjects
Geographic location, entity, Land surface, Atm, Ocean Structure, Phenomena, Precipitation, Runoff, Mathematical and statistical techniques, Changepoint analysis, Models and modeling, Land surface model, Variability, Climate variability, Atmospheric Sciences, Meteorology & Atmospheric Sciences
Abstract

Century-long observed gridded land precipitation datasets are a cornerstone of hydrometeorological research. But recent work has suggested that observed Northern Hemisphere midlatitude (NHML) land mean precipitation does not show evidence of an expected negative response to mid-twentieth-century aerosol forcing. Utilizing observed river discharges, the observed runoff is calculated and compared with observed land precipitation. The results show a near-zero twentieth-century trend in observed NHML land mean runoff, in contrast to the significant positive trend in observed NHML land mean precipitation. However, precipitation and runoff share common interannual and decadal variability. An obvious split, or breakpoint, is found in the NHML land mean runoff-precipitation relationship in the 1930s. Using runoff simulated by six land surface models (LSMs), which are driven by the observed precipitation dataset, such breakpoints are absent. These findings support previous hypotheses that inhomogeneities exist in the early-twentieth-century NHML land mean precipitation record. Adjusting the observed precipitation record according to the observed runoff record largely accounts for the departure of the observed precipitation response from that predicted given the real-world aerosol forcing estimate, more than halving the discrepancy from about 6 to around 2 W m-2. Consideration of complementary observed runoff adds support to the suggestion that NHML-wide early-twentieth-century precipitation observations are unsuitable for climate change studies. The agreement between precipitation and runoff over Europe, however, is excellent, supporting the use of whole-twentieth-century observed precipitation datasets here.

Published
2015

17. A few extreme events dominate global interannual variability in gross primary production

Author

Zscheischler, J, Mahecha, MD, Von Buttlar, J, Harmeling, S, Jung, M, Rammig, A, Randerson, JT, Schölkopf, B, Seneviratne, SI, Tomelleri, E, Zaehle, S, and Reichstein, M

Subjects
MD Multidisciplinary, Meteorology & Atmospheric Sciences
Abstract

Understanding the impacts of climate extremes on the carbon cycle is important for quantifying the carbon-cycle climate feedback and highly relevant to climate change assessments. Climate extremes and fires can have severe regional effects, but a spatially explicit global impact assessment is still lacking. Here, we directly quantify spatiotemporal contiguous extreme anomalies in four global data sets of gross primary production (GPP) over the last 30 years. We find that positive and negative GPP extremes occurring on 7% of the spatiotemporal domain explain 78% of the global interannual variation in GPP and a significant fraction of variation in the net carbon flux. The largest thousand negative GPP extremes during 1982-2011 (4.3% of the data) account for a decrease in photosynthetic carbon uptake of about 3.5 Pg C yr-1, with most events being attributable to water scarcity. The results imply that it is essential to understand the nature and causes of extremes to understand current and future GPP variability. © 2014 IOP Publishing Ltd.

Published
2014

18. A framework for benchmarking land models

Author

Luo, Y. Q, Randerson, J. T, Abramowitz, G., Bacour, C., Blyth, E., Carvalhais, N., Ciais, P., Dalmonech, D., Fisher, J. B, Fisher, R., Friedlingstein, P., Hibbard, K., Hoffman, F., Huntzinger, D., Jones, C. D, Koven, C., Lawrence, D., Li, D. J, Mahecha, M., Niu, S. L, Norby, R., Piao, S. L, Qi, X., Peylin, P., Prentice, I. C, Riley, W., Reichstein, M., Schwalm, C., Wang, Y. P, Xia, J. Y, Zaehle, S., and Zhou, X. H

Subjects
atmosphere-biosphere interaction, benchmarking, biogeochemistry, biophysics, climate change, climate feedback, ecosystem modeling, ecosystem response, numerical model, prediction, spatiotemporal analysis, trace gas, vegetation dynamics
Abstract

Land models, which have been developed by the modeling community in the past few decades to predict future states of ecosystems and climate, have to be critically evaluated for their performance skills of simulating ecosystem responses and feedback to climate change. Benchmarking is an emerging procedure to measure performance of models against a set of defined standards. This paper proposes a benchmarking framework for evaluation of land model performances and, meanwhile, highlights major challenges at this infant stage of benchmark analysis. The framework includes (1) targeted aspects of model performance to be evaluated, (2) a set of benchmarks as defined references to test model performance, (3) metrics to measure and compare performance skills among models so as to identify model strengths and deficiencies, and (4) model improvement. Land models are required to simulate exchange of water, energy, carbon and sometimes other trace gases between the atmosphere and land surface, and should be evaluated for their simulations of biophysical processes, biogeochemical cycles, and vegetation dynamics in response to climate change across broad temporal and spatial scales. Thus, one major challenge is to select and define a limited number of benchmarks to effectively evaluate land model performance. The second challenge is to develop metrics of measuring mismatches between models and benchmarks. The metrics may include (1) a priori thresholds of acceptable model performance and (2) a scoring system to combine data–model mismatches for various processes at different temporal and spatial scales. The benchmark analyses should identify clues of weak model performance to guide future development, thus enabling improved predictions of future states of ecosystems and climate. The near-future research effort should be on development of a set of widely acceptable benchmarks that can be used to objectively, effectively, and reliably evaluate fundamental properties of land models to improve their prediction performance skills.

Published
2012

20. Global Carbon Budget 2023

Author

Integr. Assessm. Global Environm. Change, Environmental Sciences, Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Bakker, D. C. E., Hauck, J., Landschützer, P., Le Quéré, C., Luijkx, I. T., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Anthoni, P., Barbero, L., Bates, N. R., Becker, M., Bellouin, N., Decharme, B., Bopp, L., Brasika, I. B. M., Cadule, P., Chamberlain, M. A., Chandra, N., Chau, T.-T.-T., Chevallier, F., Chini, L. P., Cronin, M., Dou, X., Enyo, K., Evans, W., Falk, S., Feely, R. A., Feng, L., Ford, D. J., Gasser, T., Ghattas, J., Gkritzalis, T., Grassi, G., Gregor, L., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Heinke, J., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jacobson, A. R., Jain, A., Jarníková, T., Jersild, A., Jiang, F., Jin, Z., Joos, F., Kato, E., Keeling, R. F., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Körtzinger, A., Lan, X., Lefèvre, N., Li, H., Liu, J., Liu, Z., Ma, L., Marland, G., Mayot, N., McGuire, P. C., McKinley, G. A., Meyer, G., Morgan, E. J., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K. M., Olsen, A., Omar, A. M., Ono, T., Paulsen, M., Pierrot, D., Pocock, K., Poulter, B., Powis, C. M., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Rosan, T. M., Schwinger, J., Séférian, R., Smallman, T. L., Smith, S. M., Sospedra-Alfonso, R., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tans, P. P., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., van Ooijen, E., Wanninkhof, R., Watanabe, M., Wimart-Rousseau, C., Yang, D., Yang, X., Yuan, W., Yue, X., Zaehle, S., Zeng, J., Zheng, B., Integr. Assessm. Global Environm. Change, Environmental Sciences, Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Bakker, D. C. E., Hauck, J., Landschützer, P., Le Quéré, C., Luijkx, I. T., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Anthoni, P., Barbero, L., Bates, N. R., Becker, M., Bellouin, N., Decharme, B., Bopp, L., Brasika, I. B. M., Cadule, P., Chamberlain, M. A., Chandra, N., Chau, T.-T.-T., Chevallier, F., Chini, L. P., Cronin, M., Dou, X., Enyo, K., Evans, W., Falk, S., Feely, R. A., Feng, L., Ford, D. J., Gasser, T., Ghattas, J., Gkritzalis, T., Grassi, G., Gregor, L., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Heinke, J., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jacobson, A. R., Jain, A., Jarníková, T., Jersild, A., Jiang, F., Jin, Z., Joos, F., Kato, E., Keeling, R. F., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Körtzinger, A., Lan, X., Lefèvre, N., Li, H., Liu, J., Liu, Z., Ma, L., Marland, G., Mayot, N., McGuire, P. C., McKinley, G. A., Meyer, G., Morgan, E. J., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K. M., Olsen, A., Omar, A. M., Ono, T., Paulsen, M., Pierrot, D., Pocock, K., Poulter, B., Powis, C. M., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Rosan, T. M., Schwinger, J., Séférian, R., Smallman, T. L., Smith, S. M., Sospedra-Alfonso, R., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tans, P. P., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., van Ooijen, E., Wanninkhof, R., Watanabe, M., Wimart-Rousseau, C., Yang, D., Yang, X., Yuan, W., Yue, X., Zaehle, S., Zeng, J., and Zheng, B.

Published
2023

21. The Zero Emissions Commitment and climate stabilization

Author

Palazzo Corner, S., Siegert, M., Ceppi, P., Fox-Kemper, B., Frölicher, T., Gallego-Sala, A., Haigh, J., Hegerl, G., Jones, C., Knutti, R., Koven, C., MacDougall, A., Meinshausen, M., Nicholls, Z., Sallée, J., Sanderson, B., Séférian, R., Turetsky, M., Williams, R., Zaehle, S., Rogelj, J., Palazzo Corner, S., Siegert, M., Ceppi, P., Fox-Kemper, B., Frölicher, T., Gallego-Sala, A., Haigh, J., Hegerl, G., Jones, C., Knutti, R., Koven, C., MacDougall, A., Meinshausen, M., Nicholls, Z., Sallée, J., Sanderson, B., Séférian, R., Turetsky, M., Williams, R., Zaehle, S., and Rogelj, J.

Abstract

How do we halt global warming? Reaching net zero carbon dioxide (CO2) emissions is understood to be a key milestone on the path to a safer planet. But how confident are we that when we stop carbon emissions, we also stop global warming? The Zero Emissions Commitment (ZEC) quantifies how much warming or cooling we can expect following a complete cessation of anthropogenic CO2 emissions. To date, the best estimate by the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report is zero change, though with substantial uncertainty. In this article, we present an overview of the changes expected in major Earth system processes after net zero and their potential impact on global surface temperature, providing an outlook toward building a more confident assessment of ZEC in the decades to come. We propose a structure to guide research into ZEC and associated changes in the climate, separating the impacts expected over decades, centuries, and millennia. As we look ahead at the century billed to mark the end of net anthropogenic CO2 emissions, we ask: what is the prospect of a stable climate in a post-net zero world?

Published
2023
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22. The need for carbon emissions-driven climate projections in CMIP7

Author

Sanderson, B.M., Booth, B.B.B., Dunne, J., Eyring, V., Fisher, R.A., Friedlingstein, P., Gidden, M., Hajima, T., Jones, C.D., Jones, C., King, A., Koven, C.D., Lawrence, D.M., Lowe, J., Mengis, N., Peters, G.P., Rogelj, J., Smith, C., Snyder, A.C., Simpson, I.R., Swann, A.L.S., Tebaldi, C., Ilyina, T., Schleussner, C.-F., Seferian, R., Samset, B.H., van Vuuren, D., Zaehle, S., Sanderson, B.M., Booth, B.B.B., Dunne, J., Eyring, V., Fisher, R.A., Friedlingstein, P., Gidden, M., Hajima, T., Jones, C.D., Jones, C., King, A., Koven, C.D., Lawrence, D.M., Lowe, J., Mengis, N., Peters, G.P., Rogelj, J., Smith, C., Snyder, A.C., Simpson, I.R., Swann, A.L.S., Tebaldi, C., Ilyina, T., Schleussner, C.-F., Seferian, R., Samset, B.H., van Vuuren, D., and Zaehle, S.

Abstract

Previous phases of the Coupled Model Intercomparison Project (CMIP) have primarily focused on simulations driven by atmospheric concentrations of greenhouse gases (GHGs), both for idealized model experiments, and for climate projections of different emissions scenarios. We argue that although this approach was pragmatic to allow parallel development of Earth System Model simulations and detailed socioeconomic futures, carbon cycle uncertainty as represented by diverse, process-resolving Earth System Models (ESMs) is not manifested in the scenario outcomes, thus omitting a dominant source of uncertainty in meeting the Paris Agreement. Mitigation policy is defined in terms of human activity (including emissions), with strategies varying in their timing of net-zero emissions, the balance of mitigation effort between short-lived and long-lived climate forcers, their reliance on land use strategy and the extent and timing of carbon removals. To explore the response to these drivers, ESMs need to explicitly represent complete cycles of major GHGs, including natural processes and anthropogenic influences. Carbon removal and sequestration strategies, which rely on proposed human management of natural systems, are currently represented upstream of ESMs in an idealized fashion during scenario development. However, proper accounting of the coupled system impacts of and feedback on such interventions requires explicit process representation in ESMs to build self-consistent physical representations of their potential effectiveness and risks under climate change. We propose that CMIP7 efforts prioritize simulations driven by CO2 emissions from fossil fuel use, projected deployment of carbon dioxide removal technologies, as well as land use and management, using the process resolution allowed by state-of-the-art ESMs to resolve carbon-climate feedbacks. Post-CMIP7 ambitions should aim to incorporate modeling of non-CO2 GHGs (in particular sources and sinks of methane) and process

Published
2023

23. Net-zero approaches must consider Earth system impacts to achieve climate goals

Author

Zickfeld, K., MacIsaac, A.J., Canadell, J.G., Fuss, S., Jackson, R.B., Jones, C.D., Lohila, A., Matthews, H.D., Peters, G.P., Rogelj, J., Zaehle, S., Zickfeld, K., MacIsaac, A.J., Canadell, J.G., Fuss, S., Jackson, R.B., Jones, C.D., Lohila, A., Matthews, H.D., Peters, G.P., Rogelj, J., and Zaehle, S.

Abstract

Commitments to net-zero carbon dioxide (CO2) or greenhouse gas (GHG) emissions targets now cover 88% of countries’ emissions. Underlying the accounting behind net-zero frameworks is the assumption that emissions can be balanced with removals such that their net climate effect is zero. However, when considering the full climate impacts of CO2 emissions and removals, there are reasons to expect that the two are not equivalent in terms of their climate outcomes. We identify potential contributors to non-equivalence, including impermanence, biogeophysical and non-CO2 GHG effects, and argue that these non-equivalencies need to be accounted for to achieve climate goals. Given key uncertainties about the full climate impact of CO2 removal, it is prudent to prioritize emission reductions over removals.

Published
2023
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24. The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom: 1990–2019

Author

Petrescu, A.M.R., Qiu, C., McGrath, M.J., Peylin, P., Peters, G.P., Ciais, P., Thompson, R.L., Tsuruta, A., Brunner, D., Kuhnert, M., Matthews, B., Palmer, P.I., Tarasova, O., Regnier, P., Lauerwald, R., Bastviken, D., Höglund-Isaksson, L., Winiwarter, W., Etiope, G., Aalto, T., Balsamo, G., Bastrikov, V., Berchet, A., Brockmann, P., Ciotoli, G., Conchedda, G., Crippa, M., Dentener, F., Groot Zwaaftink, C.D., Guizzardi, D., Günther, D., Haussaire, J.-M., Houweling, S., Janssens-Maenhout, G., Kouyate, M., Leip, A., Leppänen, A., Lugato, E., Maisonnier, M., Manning, A.J., Markkanen, T., McNorton, J., Muntean, M., Oreggioni, G.D., Patra, P.K., Perugini, L., Pison, I., Raivonen, M.T., Saunois, M., Segers, A.J., Smith, P., Solazzo, E., Tian, H., Tubiello, F.N., Vesala, T., van der Werf, G.R., Wilson, C., Zaehle, S., Petrescu, A.M.R., Qiu, C., McGrath, M.J., Peylin, P., Peters, G.P., Ciais, P., Thompson, R.L., Tsuruta, A., Brunner, D., Kuhnert, M., Matthews, B., Palmer, P.I., Tarasova, O., Regnier, P., Lauerwald, R., Bastviken, D., Höglund-Isaksson, L., Winiwarter, W., Etiope, G., Aalto, T., Balsamo, G., Bastrikov, V., Berchet, A., Brockmann, P., Ciotoli, G., Conchedda, G., Crippa, M., Dentener, F., Groot Zwaaftink, C.D., Guizzardi, D., Günther, D., Haussaire, J.-M., Houweling, S., Janssens-Maenhout, G., Kouyate, M., Leip, A., Leppänen, A., Lugato, E., Maisonnier, M., Manning, A.J., Markkanen, T., McNorton, J., Muntean, M., Oreggioni, G.D., Patra, P.K., Perugini, L., Pison, I., Raivonen, M.T., Saunois, M., Segers, A.J., Smith, P., Solazzo, E., Tian, H., Tubiello, F.N., Vesala, T., van der Werf, G.R., Wilson, C., and Zaehle, S.

Abstract

Knowledge of the spatial distribution of the fluxes of greenhouse gases (GHGs) and their temporal variability as well as flux attribution to natural and anthropogenic processes is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement and to inform its global stocktake. This study provides a consolidated synthesis of CH4 and N2O emissions using bottom-up (BU) and top-down (TD) approaches for the European Union and UK (EU27 + UK) and updates earlier syntheses (Petrescu et al., 2020, 2021). The work integrates updated emission inventory data, process-based model results, data-driven sector model results and inverse modeling estimates, and it extends the previous period of 1990–2017 to 2019. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported by parties under the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. Uncertainties in NGHGIs, as reported to the UNFCCC by the EU and its member states, are also included in the synthesis. Variations in estimates produced with other methods, such as 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. By comparing NGHGIs with other approaches, the activities included are a key source of bias between estimates, e.g., anthropogenic and natural fluxes, which in atmospheric inversions are sensitive to the prior geospatial distribution of emissions. For CH4 emissions, over the updated 2015–2019 period, which covers a sufficiently robust number of overlapping estimates, and most importantly the NGHGIs, the anthropogenic BU approaches are directly comparable, accounting for mean emissions of 20.5 Tg CH4 yr−1 (EDGARv6.0, last year 2018) and 18.4 Tg CH4 yr−1 (GAINS, last year 2015), close to the NGHGI estimates of 17.5±2.1 Tg CH4 yr−1. TD inversion estim

Published
2023
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25. A joint framework for studying compound ecoclimatic events

Author

Bastos, A., Sippel, S., Frank, D., Mahecha, Miguel Dario, Zaehle, S., Zscheischler, Jakob, Reichstein, M., Bastos, A., Sippel, S., Frank, D., Mahecha, Miguel Dario, Zaehle, S., Zscheischler, Jakob, and Reichstein, M.

Abstract

Extreme weather and climate events have direct impacts on ecosystems and can further trigger ecosystem disturbances, often having impacts that last longer than the event’s duration. The projected increased frequency or intensity of extreme events could thus amplify ecological impacts and reduce the biosphere’s CO2 mitigation potential, but multiple feedbacks between ecosystems and climate extremes are often not considered in risk assessments. In this Perspective, we propose a systemic framework to analyse the causal relationships between climate extremes, disturbance regimes and ecosystems, building on two broadly used perspectives: climate risk assessment and disturbance ecology. Each has strengths and limitations, as each perspective places a different — and partly disjointed — focus on the physical and ecological processes that drive high-impact ecological events. We unify these approaches into a framework (compound ecoclimatic events) that decomposes events into climatic drivers, stressors, environmental factors, impacts and their sources of variability, and further incorporates feedbacks between ecosystem processes and stressors. This framework can be used to develop ecoclimatic storylines to better understand the role of each factor in influencing high-impact events; to incorporate uncertainties associated with internal climate and ecological variability, with scenario definitions, and with epistemic uncertainties; and to quantify the human fingerprint on high-impact ecoclimatic events.

Published
2023

26. Large variability in simulated response of vegetation composition and carbon dynamics to variations in drought-heat occurrence

Author

Tschumi, E., Lienert, S., Bastos, A., Ciais, P., Gregor, K., Joos, F., Knauer, J., Papastefanou, P., Rammig, A., van der Wiel, K., Williams, K., Xu, Y., Zaehle, S., Zscheischler, Jakob, Tschumi, E., Lienert, S., Bastos, A., Ciais, P., Gregor, K., Joos, F., Knauer, J., Papastefanou, P., Rammig, A., van der Wiel, K., Williams, K., Xu, Y., Zaehle, S., and Zscheischler, Jakob

Abstract

The frequency of heatwaves, droughts and their co-occurrence vary greatly in simulations of different climate models. Since these extremes are expected to become more frequent with climate change, it is important to understand how vegetation models respond to different climatologies in heatwave and drought occurrence. In previous work, six climate scenarios featuring different drought-heat signatures have been developed to investigate how single vs. compound extremes affect vegetation and carbon dynamics. Here, we use these scenarios to force six dynamic global vegetation models to investigate model agreement in vegetation and carbon cycle response to these scenarios. We find that global responses to different drought-heat signatures vary considerably across models. Models agree that frequent compound drought-heatwave events lead to a reduction in tree cover and vegetation carbon stocks. However, models show opposite responses in vegetation changes for the scenario with no extremes. We find a strong relationship between the frequency of concurrent hot-dry conditions and the total carbon pool, suggesting a reduction of the natural land carbon sink for increasing occurrence of hot-dry events. The effect of frequent compound hot and dry extremes is larger than the sum of the effects when only one extreme occurs, highlighting the importance of studying compound events. Our results demonstrate that uncertainties in the representation of compound hot-dry event occurrence in climate models propagate to uncertainties in the simulation of vegetation distribution and carbon pools. Therefore, to reduce uncertainties in future carbon cycle projections, the representation of compound events in climate models needs to be improved.

Published
2023

27. Global Carbon Budget 2022

Author

Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Gregor, L., Hauck, J., Le Quéré, C., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Alkama, R., Arneth, A., Arora, V. K., Bates, N. R., Becker, M., Bellouin, N., Bittig, H. C., Bopp, L., Chevallier, F., Chini, L. P., Cronin, M., Evans, W., Falk, S., Feely, R. A., Gasser, T., Gehlen, M., Gkritzalis, T., Gloege, L., Grassi, G., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jain, A. K., Jersild, A., Kadono, K., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Landschützer, P., Lefèvre, N., Lindsay, K., Liu, J., Liu, Z., Marland, G., Mayot, N., McGrath, M. J., Metzl, N., Monacci, N. M., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K., Ono, T., Palmer, P. I., Pan, N., Pierrot, D., Pocock, K., Poulter, B., Resplandy, L., Robertson, E., Rödenbeck, C., Rodriguez, C., Rosan, T. M., Schwinger, J., Séférian, R., Shutler, J. D., Skjelvan, I., Steinhoff, T., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tanhua, T., Tans, P. P., Tian, X., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., Walker, A. P., Wanninkhof, R., Whitehead, C., Willstrand Wranne, A., Wright, R., Yuan, W., Yue, C., Yue, X., Zaehle, S., Zeng, J., Zheng, B., Integr. Assessm. Global Environm. Change, Environmental Sciences, Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), 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), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), 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, College of Life and Environmental Sciences [Exeter], University of Exeter, Rice University [Houston], Center for International Climate and Environmental Research [Oslo] (CICERO), University of Oslo (UiO), Institute of Biogeochemistry and Pollutant Dynamics [ETH Zürich] (IBP), Department of Environmental Systems Science [ETH Zürich] (D-USYS), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich)- Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), Tyndall Centre for Climate Change Research, University of East Anglia [Norwich] (UEA), Meteorology and Air Quality Group, Wageningen University and Research [Wageningen] (WUR), Geophysical Institute [Bergen] (GFI / BiU), University of Bergen (UiB), Bjerknes Centre for Climate Research (BCCR), Department of Biological Sciences [Bergen] (BIO / UiB), University of Bergen (UiB)-University of Bergen (UiB), Meteorology and Air Quality Department [Wageningen] (MAQ), Ludwig-Maximilians-Universität München (LMU), Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, 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), Stanford Woods Institute for the Environment, Stanford University, European Commission - Joint Research Centre [Ispra] (JRC), Karlsruhe Institute of Technology (KIT), Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, Austral, Boréal et Carbone (ABC), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), 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), Cycles biogéochimiques marins : processus et perturbations (CYBIOM), Earth Sciences, Amsterdam Sustainability Institute, and Isotope Research

Subjects
WIMEK, [SDE.MCG]Environmental Sciences/Global Changes, SDG 13 - Climate Action, Life Science, General Earth and Planetary Sciences, Luchtkwaliteit, Air Quality
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 methodologies 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 year 2021, EFOS increased by 5.1 % relative to 2020, with fossil emissions at 10.1 ± 0.5 GtC yr−1 (9.9 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 1.1 ± 0.7 GtC yr−1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 10.9 ± 0.8 GtC yr−1 (40.0 ± 2.9 GtCO2). Also, for 2021, GATM was 5.2 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEAN was 2.9 ± 0.4 GtC yr−1, and SLAND was 3.5 ± 0.9 GtC yr−1, with a BIM of −0.6 GtC yr−1 (i.e. the total estimated sources were too low or sinks were too high). The global atmospheric CO2 concentration averaged over 2021 reached 414.71 ± 0.1 ppm. Preliminary data for 2022 suggest an increase in EFOS relative to 2021 of +1.0 % (0.1 % to 1.9 %) globally and atmospheric CO2 concentration reaching 417.2 ppm, more than 50 % above pre-industrial levels (around 278 ppm). Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2021, 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 change emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extratropics, 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. The data presented in this work are available at https://doi.org/10.18160/GCP-2022 (Friedlingstein et al., 2022b).

Published
2022

28. The three major axes of terrestrial ecosystem function

Author

Migliavacca, M, Musavi, T, Mahecha, M, Nelson, J, Knauer, J, Baldocchi, D, Perez-Priego, O, Christiansen, R, Peters, J, Anderson, K, Bahn, M, Black, T, Blanken, P, Bonal, D, Buchmann, N, Caldararu, S, Carrara, A, Carvalhais, N, Cescatti, A, Chen, J, Cleverly, J, Cremonese, E, Desai, A, El-Madany, T, Farella, M, Fernandez-Martinez, M, Filippa, G, Forkel, M, Galvagno, M, Gomarasca, U, Gough, C, Gockede, M, Ibrom, A, Ikawa, H, Janssens, I, Jung, M, Kattge, J, Keenan, T, Knohl, A, Kobayashi, H, Kraemer, G, Law, B, Liddell, M, Ma, X, Mammarella, I, Martini, D, Macfarlane, C, Matteucci, G, Montagnani, L, Pabon-Moreno, D, Panigada, C, Papale, D, Pendall, E, Penuelas, J, Phillips, R, Reich, P, Rossini, M, Rotenberg, E, Scott, R, Stahl, C, Weber, U, Wohlfahrt, G, Wolf, S, Wright, I, Yakir, D, Zaehle, S, Reichstein, M, Migliavacca M., Musavi T., Mahecha M. D., Nelson J. A., Knauer J., Baldocchi D. D., Perez-Priego O., Christiansen R., Peters J., Anderson K., Bahn M., Black T. A., Blanken P. D., Bonal D., Buchmann N., Caldararu S., Carrara A., Carvalhais N., Cescatti A., Chen J., Cleverly J., Cremonese E., Desai A. R., El-Madany T. S., Farella M. M., Fernandez-Martinez M., Filippa G., Forkel M., Galvagno M., Gomarasca U., Gough C. M., Gockede M., Ibrom A., Ikawa H., Janssens I. A., Jung M., Kattge J., Keenan T. F., Knohl A., Kobayashi H., Kraemer G., Law B. E., Liddell M. J., Ma X., Mammarella I., Martini D., Macfarlane C., Matteucci G., Montagnani L., Pabon-Moreno D. E., Panigada C., Papale D., Pendall E., Penuelas J., Phillips R. P., Reich P. B., Rossini M., Rotenberg E., Scott R. L., Stahl C., Weber U., Wohlfahrt G., Wolf S., Wright I. J., Yakir D., Zaehle S., Reichstein M., Migliavacca, M, Musavi, T, Mahecha, M, Nelson, J, Knauer, J, Baldocchi, D, Perez-Priego, O, Christiansen, R, Peters, J, Anderson, K, Bahn, M, Black, T, Blanken, P, Bonal, D, Buchmann, N, Caldararu, S, Carrara, A, Carvalhais, N, Cescatti, A, Chen, J, Cleverly, J, Cremonese, E, Desai, A, El-Madany, T, Farella, M, Fernandez-Martinez, M, Filippa, G, Forkel, M, Galvagno, M, Gomarasca, U, Gough, C, Gockede, M, Ibrom, A, Ikawa, H, Janssens, I, Jung, M, Kattge, J, Keenan, T, Knohl, A, Kobayashi, H, Kraemer, G, Law, B, Liddell, M, Ma, X, Mammarella, I, Martini, D, Macfarlane, C, Matteucci, G, Montagnani, L, Pabon-Moreno, D, Panigada, C, Papale, D, Pendall, E, Penuelas, J, Phillips, R, Reich, P, Rossini, M, Rotenberg, E, Scott, R, Stahl, C, Weber, U, Wohlfahrt, G, Wolf, S, Wright, I, Yakir, D, Zaehle, S, Reichstein, M, Migliavacca M., Musavi T., Mahecha M. D., Nelson J. A., Knauer J., Baldocchi D. D., Perez-Priego O., Christiansen R., Peters J., Anderson K., Bahn M., Black T. A., Blanken P. D., Bonal D., Buchmann N., Caldararu S., Carrara A., Carvalhais N., Cescatti A., Chen J., Cleverly J., Cremonese E., Desai A. R., El-Madany T. S., Farella M. M., Fernandez-Martinez M., Filippa G., Forkel M., Galvagno M., Gomarasca U., Gough C. M., Gockede M., Ibrom A., Ikawa H., Janssens I. A., Jung M., Kattge J., Keenan T. F., Knohl A., Kobayashi H., Kraemer G., Law B. E., Liddell M. J., Ma X., Mammarella I., Martini D., Macfarlane C., Matteucci G., Montagnani L., Pabon-Moreno D. E., Panigada C., Papale D., Pendall E., Penuelas J., Phillips R. P., Reich P. B., Rossini M., Rotenberg E., Scott R. L., Stahl C., Weber U., Wohlfahrt G., Wolf S., Wright I. J., Yakir D., Zaehle S., and Reichstein M.

Abstract

The leaf economics spectrum and the global spectrum of plant forms and functions3 revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species. Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability. Here we derive a set of ecosystem functions from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems.

Published
2021

30. Are Land-Use Change Emissions in Southeast Asia Decreasing or Increasing?

Author

Kondo, M, Kondo, M, Sitch, S, Ciais, P, Achard, F, Kato, E, Pongratz, J, Houghton, RA, Canadell, JG, Patra, PK, Friedlingstein, P, Li, W, Anthoni, P, Arneth, A, Chevallier, F, Ganzenmüller, R, Harper, A, Jain, AK, Koven, C, Lienert, S, Lombardozzi, D, Maki, T, Nabel, JEMS, Nakamura, T, Niwa, Y, Peylin, P, Poulter, B, Pugh, TAM, Rödenbeck, C, Saeki, T, Stocker, B, Viovy, N, Wiltshire, A, Zaehle, S, Kondo, M, Kondo, M, Sitch, S, Ciais, P, Achard, F, Kato, E, Pongratz, J, Houghton, RA, Canadell, JG, Patra, PK, Friedlingstein, P, Li, W, Anthoni, P, Arneth, A, Chevallier, F, Ganzenmüller, R, Harper, A, Jain, AK, Koven, C, Lienert, S, Lombardozzi, D, Maki, T, Nabel, JEMS, Nakamura, T, Niwa, Y, Peylin, P, Poulter, B, Pugh, TAM, Rödenbeck, C, Saeki, T, Stocker, B, Viovy, N, Wiltshire, A, and Zaehle, S

Abstract

Southeast Asia is a region known for active land-use changes (LUC) over the past 60 years; yet, how trends in net CO2 uptake and release resulting from LUC activities (net LUC flux) have changed through past decades remains uncertain. The level of uncertainty in net LUC flux from process-based models is so high that it cannot be concluded that newer estimates are necessarily more reliable than older ones. Here, we examined net LUC flux estimates of Southeast Asia for the 1980s−2010s from older and newer sets of Dynamic Global Vegetation Model simulations (TRENDY v2 and v7, respectively), and forcing data used for running those simulations, along with two book-keeping estimates (H&N and BLUE). These estimates yielded two contrasting historical LUC transitions, such that TRENDY v2 and H&N showed a transition from increased emissions from the 1980s to 1990s to declining emissions in the 2000s, while TRENDY v7 and BLUE showed the opposite transition. We found that these contrasting transitions originated in the update of LUC forcing data, which reduced the loss of forest area during the 1990s. Further evaluation of remote sensing studies, atmospheric inversions, and the history of forestry and environmental policies in Southeast Asia supported the occurrence of peak emissions in the 1990s and declining thereafter. However, whether LUC emissions continue to decline in Southeast Asia remains uncertain as key processes in recent years, such as conversion of peat forest to oil-palm plantation, are yet to be represented in the forcing data, suggesting a need for further revision.

Published
2022

31. Global Carbon Budget 2022

Author

Integr. Assessm. Global Environm. Change, Environmental Sciences, Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Gregor, L., Hauck, J., Le Quéré, C., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Alkama, R., Arneth, A., Arora, V. K., Bates, N. R., Becker, M., Bellouin, N., Bittig, H. C., Bopp, L., Chevallier, F., Chini, L. P., Cronin, M., Evans, W., Falk, S., Feely, R. A., Gasser, T., Gehlen, M., Gkritzalis, T., Gloege, L., Grassi, G., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jain, A. K., Jersild, A., Kadono, K., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Landschützer, P., Lefèvre, N., Lindsay, K., Liu, J., Liu, Z., Marland, G., Mayot, N., McGrath, M. J., Metzl, N., Monacci, N. M., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K., Ono, T., Palmer, P. I., Pan, N., Pierrot, D., Pocock, K., Poulter, B., Resplandy, L., Robertson, E., Rödenbeck, C., Rodriguez, C., Rosan, T. M., Schwinger, J., Séférian, R., Shutler, J. D., Skjelvan, I., Steinhoff, T., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tanhua, T., Tans, P. P., Tian, X., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., Walker, A. P., Wanninkhof, R., Whitehead, C., Willstrand Wranne, A., Wright, R., Yuan, W., Yue, C., Yue, X., Zaehle, S., Zeng, J., Zheng, B., Integr. Assessm. Global Environm. Change, Environmental Sciences, Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Gregor, L., Hauck, J., Le Quéré, C., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Alkama, R., Arneth, A., Arora, V. K., Bates, N. R., Becker, M., Bellouin, N., Bittig, H. C., Bopp, L., Chevallier, F., Chini, L. P., Cronin, M., Evans, W., Falk, S., Feely, R. A., Gasser, T., Gehlen, M., Gkritzalis, T., Gloege, L., Grassi, G., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jain, A. K., Jersild, A., Kadono, K., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Landschützer, P., Lefèvre, N., Lindsay, K., Liu, J., Liu, Z., Marland, G., Mayot, N., McGrath, M. J., Metzl, N., Monacci, N. M., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K., Ono, T., Palmer, P. I., Pan, N., Pierrot, D., Pocock, K., Poulter, B., Resplandy, L., Robertson, E., Rödenbeck, C., Rodriguez, C., Rosan, T. M., Schwinger, J., Séférian, R., Shutler, J. D., Skjelvan, I., Steinhoff, T., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tanhua, T., Tans, P. P., Tian, X., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., Walker, A. P., Wanninkhof, R., Whitehead, C., Willstrand Wranne, A., Wright, R., Yuan, W., Yue, C., Yue, X., Zaehle, S., Zeng, J., and Zheng, B.

Published
2022

32. Historical Carbon Dioxide Emissions Caused by Land-Use Changes are Possibly Larger than Assumed

Author

Arneth, A, Sitch, S, Pongratz, J, Stocker, B. D, Ciais, P, Poulter, B, Bayer, A. D, Bondeau, A, Calle, L, Chini, L. P, Gasser, T, Fader, M, Friedlingstein, P, Kato, E, Li, W, Lindeskog, M, Nabel, J. E. M. S, Pugh, T. A. M, Robertson, E, Viovy, N, Yue, C, and Zaehle, S

Subjects
Environment Pollution
Abstract

The terrestrial biosphere absorbs about 20% of fossil-fuel CO2 emissions. The overall magnitude of this sink is constrained by the difference between emissions, the rate of increase in atmospheric CO2 concentrations, and the ocean sink. However, the land 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-use change have been substantially underestimated because processes such as tree harvesting and land clearing from shifting cultivation have not been considered. As the overall terrestrial sink is constrained, a larger net flux as a result of land-use change implies that terrestrial uptake of CO2 is also larger, and that terrestrial ecosystems might have greater potential to sequester carbon in the future. Consequently, reforestation projects and efforts to avoid further deforestation could represent important mitigation pathways, with co-benefits for biodiversity. It is unclear whether a larger land carbon sink can be reconciled with our current understanding of terrestrial carbon cycling. Our possible underestimation of the historical residual terrestrial carbon sink adds further uncertainty to our capacity to predict the future of terrestrial carbon uptake and losses.

Published
2017
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33. Magnitude and Uncertainty of Nitrous Oxide Emissions From North America Based on Bottom‐Up and Top‐Down Approaches: Informing Future Research and National Inventories

Author

Xu, R., primary, Tian, H., additional, Pan, N., additional, Thompson, R. L., additional, Canadell, J. G., additional, Davidson, E. A., additional, Nevison, C., additional, Winiwarter, W., additional, Shi, H., additional, Pan, S., additional, Chang, J., additional, Ciais, P., additional, Dangal, S. R. S., additional, Ito, A., additional, Jackson, R. B., additional, Joos, F., additional, Lauerwald, R., additional, Lienert, S., additional, Maavara, T., additional, Millet, D. B., additional, Raymond, P. A., additional, Regnier, P., additional, Tubiello, F. N., additional, Vuichard, N., additional, Wells, K. C., additional, Wilson, C., additional, Yang, J., additional, Yao, Y., additional, Zaehle, S., additional, and Zhou, F., additional

Published
2021
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34. Plant phenology evaluation of CRESCENDO land surface models. Part I: onset and offset timings

Author

Peano, D., Hemming, D., Materia, S., Delire, C., Fan, Y., Joetzjer, E., Lee, H., Nabel, J., Park, T., Peylin, P., Wårlind, D., Wiltshire, A., and Zaehle, S.

Abstract

Plant phenology plays a fundamental role in land–atmosphere interactions, and its variability and variations are an indicator of climate and environmental changes. For this reason, current land surface models include phenology parameterizations and related biophysical and biogeochemical processes. In this work, the climatology of the beginning and end of the growing season, simulated by the land component of seven state-of-the-art European Earth system models participating in the CMIP6, is evaluated globally against satellite observations. The assessment is performed using the vegetation metric leaf area index and a recently developed approach, named four growing season types. On average, the land surface models show a 0.6-month delay in the growing season start, while they are about 0.5 months earlier in the growing season end. The difference with observation tends to be higher in the Southern Hemisphere compared to the Northern Hemisphere. High agreement between land surface models and observations is exhibited in areas dominated by broadleaf deciduous trees, while high variability is noted in regions dominated by broadleaf deciduous shrubs. Generally, the timing of the growing season end is accurately simulated in about 25 % of global land grid points versus 16 % in the timing of growing season start. The refinement of phenology parameterization can lead to better representation of vegetation-related energy, water, and carbon cycles in land surface models, but plant phenology is also affected by plant physiology and soil hydrology processes. Consequently, phenology representation and, in general, vegetation modelling is a complex task, which still needs further improvement, evaluation, and multi-model comparison.

Published
2021

36. The three major axes of terrestrial ecosystem function

Author

Migliavacca, M., Musavi, T., Mahecha, Miguel Dario, Nelson, J.A., Knauer, J., Baldocchi, D.D., Perez-Priego, O., Christiansen, R., Peters, J., Anderson, K., Bahn, M., Black, T.A., Blanken, P.D., Bonal, D., Buchmann, N., Caldararu, S., Carrara, A., Carvalhais, N., Cescatti, A., Chen, J., Cleverly, J., Cremonese, E., Desai, A.R., El-Madany, T.S., Farella, M.M., Fernández-Martínez, M., Filippa, G., Forkel, M., Galvagno, M., Gomarasca, U., Gough, C.M., Göckede, M., Ibrom, A., Ikawa, H., Janssens, I.A., Jung, M., Kattge, J., Keenan, T.F., Knohl, A., Kobayashi, H., Kraemer, G., Law, B.E., Liddell, M.J., Ma, X., Mammarella, I., Martini, D., Macfarlane, C., Matteucci, G., Montagnani, L., Pabon-Moreno, D.E., Panigada, C., Papale, D., Pendall, E., Penuelas, J., Phillips, R.P., Reich, P.B., Rossini, M., Rotenberg, E., Scott, R.L., Stahl, C., Weber, U., Wohlfahrt, G., Wolf, S., Wright, I.J., Yakir, D., Zaehle, S., Reichstein, M., Migliavacca, M., Musavi, T., Mahecha, Miguel Dario, Nelson, J.A., Knauer, J., Baldocchi, D.D., Perez-Priego, O., Christiansen, R., Peters, J., Anderson, K., Bahn, M., Black, T.A., Blanken, P.D., Bonal, D., Buchmann, N., Caldararu, S., Carrara, A., Carvalhais, N., Cescatti, A., Chen, J., Cleverly, J., Cremonese, E., Desai, A.R., El-Madany, T.S., Farella, M.M., Fernández-Martínez, M., Filippa, G., Forkel, M., Galvagno, M., Gomarasca, U., Gough, C.M., Göckede, M., Ibrom, A., Ikawa, H., Janssens, I.A., Jung, M., Kattge, J., Keenan, T.F., Knohl, A., Kobayashi, H., Kraemer, G., Law, B.E., Liddell, M.J., Ma, X., Mammarella, I., Martini, D., Macfarlane, C., Matteucci, G., Montagnani, L., Pabon-Moreno, D.E., Panigada, C., Papale, D., Pendall, E., Penuelas, J., Phillips, R.P., Reich, P.B., Rossini, M., Rotenberg, E., Scott, R.L., Stahl, C., Weber, U., Wohlfahrt, G., Wolf, S., Wright, I.J., Yakir, D., Zaehle, S., and Reichstein, M.

Abstract

The leaf economics spectrum(1,2) and the global spectrum of plant forms and functions(3) revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species(2). Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities(4). However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability(4,5). Here we derive a set of ecosystem functions(6) from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems(7,8).

Published
2021

37. Magnitude and Uncertainty of Nitrous Oxide Emissions From North America Based on Bottom‐Up and Top‐Down Approaches: Informing Future Research and National Inventories

Author

Xu, R., Tian, H., Pan, N., Thompson, R.L., Canadell, J.G., Davidson, E.A., Nevison, C., Winiwarter, W., Shi, H., Pan, S., Chang, J., Ciais, P., Dangal, S.R.S., Ito, A., Jackson, R.B., Joos, F., Lauerwald, R., Lienert, S., Maavara, T., Millet, D.B., Raymond, P.A., Regnier, P., Tubiello, F.N., Vuichard, N., Wells, K.C., Wilson, C., Yang, J., Yao, Y., Zaehle, S., Zhou, F., Xu, R., Tian, H., Pan, N., Thompson, R.L., Canadell, J.G., Davidson, E.A., Nevison, C., Winiwarter, W., Shi, H., Pan, S., Chang, J., Ciais, P., Dangal, S.R.S., Ito, A., Jackson, R.B., Joos, F., Lauerwald, R., Lienert, S., Maavara, T., Millet, D.B., Raymond, P.A., Regnier, P., Tubiello, F.N., Vuichard, N., Wells, K.C., Wilson, C., Yang, J., Yao, Y., Zaehle, S., and Zhou, F.

Abstract

We synthesized N2O emissions over North America using 17 bottom-up (BU) estimates from 1980–2016 and five top-down (TD) estimates from 1998 to 2016. The BU-based total emission shows a slight increase owing to U.S. agriculture, while no consistent trend is shown in TD estimates. During 2007–2016, North American N2O emissions are estimated at 1.7 (1.0–3.0) Tg N yr−1 (BU) and 1.3 (0.9–1.5) Tg N yr−1 (TD). Anthropogenic emissions were twice as large as natural fluxes from soil and water. Direct agricultural and industrial activities accounted for 68% of total anthropogenic emissions, 71% of which was contributed by the U.S. Our estimates of U.S. agricultural emissions are comparable to the EPA greenhouse gas (GHG) inventory, which includes estimates from IPCC tier 1 (emission factor) and tier 3 (process-based modeling) approaches. Conversely, our estimated agricultural emissions for Canada and Mexico are twice as large as the respective national GHG inventories.

Published
2021

38. Global Carbon Budget 2020

Author

Friedlingstein, P, O'Sullivan, M, Jones, MW, Andrew, RM, Hauck, J, Olsen, A, Peters, GP, Peters, W, Pongratz, J, Sitch, S, Le Quéré, C, Canadell, JG, Ciais, P, Jackson, RB, Alin, S, Aragão, LEOC, Arneth, A, Arora, V, Bates, NR, Becker, M, Benoit-Cattin, A, Bittig, HC, Bopp, L, Bultan, S, Chandra, N, Chevallier, F, Chini, LP, Evans, W, Florentie, L, Forster, PM, Gasser, T, Gehlen, M, Gilfillan, D, Gkritzalis, T, Gregor, L, Gruber, N, Harris, I, Hartung, K, Haverd, V, Houghton, RA, Ilyina, T, Jain, AK, Joetzjer, E, Kadono, K, Kato, E, Kitidis, V, Korsbakken, JI, Landschützer, P, Lefèvre, N, Lenton, A, Lienert, S, Liu, Z, Lombardozzi, D, Marland, G, Metzl, N, Munro, DR, Nabel, JEMS, Nakaoka, S-I, Niwa, Y, O'Brien, K, Ono, T, Palmer, PI, Pierrot, D, Poulter, B, Resplandy, L, Robertson, E, Rödenbeck, C, Schwinger, J, Séférian, R, Skjelvan, I, Smith, AJP, Sutton, AJ, Tanhua, T, Tans, PP, Tian, H, Tilbrook, B, van der Werf, G, Vuichard, N, Walker, AP, Wanninkhof, R, Watson, AJ, Willis, D, Wiltshire, AJ, Yuan, W, Yue, X, and Zaehle, S

Abstract

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate – 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 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) 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 (2010–2019), EFOS was 9.6 ± 0.5 GtC yr−1 excluding the cement carbonation sink (9.4 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 1.6 ± 0.7 GtC yr−1. For the same decade, GATM was 5.1 ± 0.02 GtC yr−1 (2.4 ± 0.01 ppm yr−1), SOCEAN 2.5 ± 0.6 GtC yr−1, and SLAND 3.4 ± 0.9 GtC yr−1, with a budget imbalance BIM of −0.1 GtC yr−1 indicating a near balance between estimated sources and sinks over the last decade. For the year 2019 alone, the growth in EFOS was only about 0.1 % with fossil emissions increasing to 9.9 ± 0.5 GtC yr−1 excluding the cement carbonation sink (9.7 ± 0.5 GtC yr−1 when cement carbonation sink is included), and ELUC was 1.8 ± 0.7 GtC yr−1, for total anthropogenic CO2 emissions of 11.5 ± 0.9 GtC yr−1 (42.2 ± 3.3 GtCO2). Also for 2019, GATM was 5.4 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEAN was 2.6 ± 0.6 GtC yr−1, and SLAND was 3.1 ± 1.2 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 409.85 ± 0.1 ppm averaged over 2019. Preliminary data for 2020, accounting for the COVID-19-induced changes in emissions, suggest a decrease in EFOS relative to 2019 of about −7 % (median estimate) based on individual estimates from four studies of −6 %, −7 %, −7 % (−3 % to −11 %), and −13 %. Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2019, but discrepancies of up to 1 GtC yr−1 persist for the representation of semi-decadal variability in CO2 fluxes. Comparison of estimates from diverse approaches and observations shows (1) no consensus in the mean and trend in land-use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent discrepancy between the different methods for the ocean sink outside the tropics, particularly in the Southern Ocean. 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., 2019; Le Quéré et al., 2018b, a, 2016, 2015b, a, 2014, 2013). The data presented in this work are available at https://doi.org/10.18160/gcp-2020 (Friedlingstein et al., 2020).

Published
2020

39. Sources of Uncertainty in Regional and Global Terrestrial CO₂ Exchange Estimates

Author

Bastos, A., O'Sullivan, M., Ciais, P., Makowski, D., Sitch, S., Friedlingstein, P., Chevallier, F., Rödenbeck, C., Pongratz, J., Luijkx, I. T., Patra, P. K., Peylin, P., Canadell, J. G., Lauerwald, R., Li, W., Smith, N. E., Peters, W., Goll, D. S., Jain, A.K., Kato, E., Lienert, S., Lombardozzi, D. L., Haverd, V., Nabel, J. E. M. S., Poulter, B., Tian, H., Walker, A. P., and Zaehle, S.

Subjects
530 Physics
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 GCB 2018: (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 GCB 2018 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

40. Evaluating two soil carbon models within the global land surface model JSBACH using surface and spaceborne observations of atmospheric CO2

Author

Thum, T., Nabel, J., Tsuruta, A., Aalto, T., Dlugokencky, E., Liski, J., Luijkx, I., Markkanen, T., Pongratz, J., Yoshida, Y., and Zaehle, S.

Subjects
WIMEK, Life Science, Luchtkwaliteit, Air Quality
Abstract

The trajectories of soil carbon in our changing climate are of the utmost importance as soil is a substantial carbon reservoir with a large potential to impact the atmospheric carbon dioxide (CO2) burden. Atmospheric CO2 observations integrate all processes affecting carbon exchange between the surface and the atmosphere and therefore are suitable for carbon cycle model evaluation. In this study, we present a framework for how to use atmospheric CO2 observations to evaluate two distinct soil carbon models (CBALANCE, CBA, and Yasso, YAS) that are implemented in a global land surface model (JSBACH). We transported the biospheric carbon fluxes obtained by JSBACH using the atmospheric transport model TM5 to obtain atmospheric CO2. We then compared these results with surface observations from Global Atmosphere Watch stations, as well as with column XCO2 retrievals from GOSAT (Greenhouse Gases Observing Satellite). The seasonal cycles of atmospheric CO2 estimated by the two different soil models differed. The estimates from the CBALANCE soil model were more in line with the surface observations at low latitudes (0–45∘ N) with only a 1 % bias in the seasonal cycle amplitude, whereas Yasso underestimated the seasonal cycle amplitude in this region by 32 %. Yasso, on the other hand, gave more realistic seasonal cycle amplitudes of CO2 at northern boreal sites (north of 45∘ N) with an underestimation of 15 % compared to a 30 % overestimation by CBALANCE. Generally, the estimates from CBALANCE were more successful in capturing the seasonal patterns and seasonal cycle amplitudes of atmospheric CO2 even though it overestimated soil carbon stocks by 225 % (compared to an underestimation of 36 % by Yasso), and its estimations of the global distribution of soil carbon stocks were unrealistic. The reasons for these differences in the results are related to the different environmental drivers and their functional dependencies on the two soil carbon models. In the tropics, heterotrophic respiration in the Yasso model increased earlier in the season since it is driven by precipitation instead of soil moisture, as in CBALANCE. In temperate and boreal regions, the role of temperature is more dominant. There, heterotrophic respiration from the Yasso model had a larger seasonal amplitude, which is driven by air temperature, compared to CBALANCE, which is driven by soil temperature. The results underline the importance of using sub-annual data in the development of soil carbon models when they are used at shorter than annual timescales.

Published
2020

41. The fate of carbon in a mature forest under carbon dioxide enrichment

Author

Jiang, M., Medlyn, B.E., Drake, J.E., Duursma, R.A., Anderson, I.C., Barton, C.V.M., Boer, M.M., Carrillo, Y., Castañeda-Gómez, L., Collins, L., Crous, K.Y., De Kauwe, M.G., Dos Santos, B.M., Emmerson, K.M., Facey, S.L., Gherlenda, A.N., Gimeno, T.E., Hasegawa, S., Johnson, S.N., Kännaste, A., Macdonald, C.A., Mahmud, K., Moore, B.D., Nazaries, L., Neilson, E.H.J., Nielsen, U.N., Niinemets, Ü., Noh, N.J., Ochoa-Hueso, R., Pathare, V.S., Pendall, E., Pihlblad, J., Piñeiro, J., Powell, J.R., Power, S.A., Reich, P.B., Renchon, A.A., Riegler, M., Rinnan, R., Rymer, P.D., Salomón, R.L., Singh, B.K., Smith, B., Tjoelker, M.G., Walker, J.K.M., Wujeska-Klause, A., Yang, J., Zaehle, S., Ellsworth, D.S., Jiang, M., Medlyn, B.E., Drake, J.E., Duursma, R.A., Anderson, I.C., Barton, C.V.M., Boer, M.M., Carrillo, Y., Castañeda-Gómez, L., Collins, L., Crous, K.Y., De Kauwe, M.G., Dos Santos, B.M., Emmerson, K.M., Facey, S.L., Gherlenda, A.N., Gimeno, T.E., Hasegawa, S., Johnson, S.N., Kännaste, A., Macdonald, C.A., Mahmud, K., Moore, B.D., Nazaries, L., Neilson, E.H.J., Nielsen, U.N., Niinemets, Ü., Noh, N.J., Ochoa-Hueso, R., Pathare, V.S., Pendall, E., Pihlblad, J., Piñeiro, J., Powell, J.R., Power, S.A., Reich, P.B., Renchon, A.A., Riegler, M., Rinnan, R., Rymer, P.D., Salomón, R.L., Singh, B.K., Smith, B., Tjoelker, M.G., Walker, J.K.M., Wujeska-Klause, A., Yang, J., Zaehle, S., and Ellsworth, D.S.

Abstract

Atmospheric carbon dioxide enrichment (eCO2) can enhance plant carbon uptake and growth1 5, thereby providing an important negative feedback to climate change by slowing the rate of increase of the atmospheric CO2 concentration6. Although evidence gathered from young aggrading forests has generally indicated a strong CO2 fertilization effect on biomass growth3 5, it is unclear whether mature forests respond to eCO2 in a similar way. In mature trees and forest stands7 10, photosynthetic uptake has been found to increase under eCO2 without any apparent accompanying growth response, leaving the fate of additional carbon fixed under eCO2 unclear4,5,7 11. Here using data from the first ecosystem-scale Free-Air CO2 Enrichment (FACE) experiment in a mature forest, we constructed a comprehensive ecosystem carbon budget to track the fate of carbon as the forest responded to four years of eCO2 exposure. We show that, although the eCO2 treatment of +150 parts per million (+38 per cent) above ambient levels induced a 12 per cent (+247 grams of carbon per square metre per year) increase in carbon uptake through gross primary production, this additional carbon uptake did not lead to increased carbon sequestration at the ecosystem level. Instead, the majority of the extra carbon was emitted back into the atmosphere via several respiratory fluxes, with increased soil respiration alone accounting for half of the total uptake surplus. Our results call into question the predominant thinking that the capacity of forests to act as carbon sinks will be generally enhanced under eCO2, and challenge the efficacy of climate mitigation strategies that rely on ubiquitous CO2 fertilization as a driver of increased carbon sinks in global forests. © 2020, The Author(s), under exclusive licence to Springer Nature Limited.

Published
2020

42. A comprehensive quantification of global nitrous oxide sources and sinks

Author

Tian, H., Xu, R., Canadell, J.G., Winiwarter, W., Suntharalingam, P., Davidson, E.A., Ciais, P., Jackson, R.B., Janssens-Maenhout, G., Prather, M.J., Regnier, P., Pan, N., Peters, G.P., Shi, H., Tubiello, F.N., Zaehle, S., Zhou, F., Ameth, A., Battaglia, G., Berthet, S., Bopp, L., Bouwman, A.F., Buitenhuis, E.T., Chang, J., Chipperfield, M.P., Dangal, S.R.S., Dlugokencky, E., Elkins, J.W., Eyre, B.D., Fu, B., Hall, B., Ito, A., Joos, F., Krummel, P.B., Landolfi, A., Laruelle, G.G., Lauerwald, R., Li, W., Lienert, S., Maavara, T., MacLeod, M., Millet, D.B., Olin, S., Patra, P.K., Prinn, R.G., Raymond, R.A., Ruiz, D.J., van der Werf, G.R., Vuichard, N., Wang, J., Weiss, R.F., Wells, K.C., Wilson, C., Yang, J., Yao, Y., Tian, H., Xu, R., Canadell, J.G., Winiwarter, W., Suntharalingam, P., Davidson, E.A., Ciais, P., Jackson, R.B., Janssens-Maenhout, G., Prather, M.J., Regnier, P., Pan, N., Peters, G.P., Shi, H., Tubiello, F.N., Zaehle, S., Zhou, F., Ameth, A., Battaglia, G., Berthet, S., Bopp, L., Bouwman, A.F., Buitenhuis, E.T., Chang, J., Chipperfield, M.P., Dangal, S.R.S., Dlugokencky, E., Elkins, J.W., Eyre, B.D., Fu, B., Hall, B., Ito, A., Joos, F., Krummel, P.B., Landolfi, A., Laruelle, G.G., Lauerwald, R., Li, W., Lienert, S., Maavara, T., MacLeod, M., Millet, D.B., Olin, S., Patra, P.K., Prinn, R.G., Raymond, R.A., Ruiz, D.J., van der Werf, G.R., Vuichard, N., Wang, J., Weiss, R.F., Wells, K.C., Wilson, C., Yang, J., and Yao, Y.

Abstract

Nitrous oxide (N2O), like carbon dioxide, is a long-lived greenhouse gas that accumulates in the atmosphere. Over the past 150 years, increasing atmospheric N2O concentrations have contributed to stratospheric ozone depletion1 and climate change2, with the current rate of increase estimated at 2 per cent per decade. Existing national inventories do not provide a full picture of N2O emissions, owing to their omission of natural sources and limitations in methodology for attributing anthropogenic sources. Here we present a global N2O inventory that incorporates both natural and anthropogenic sources and accounts for the interaction between nitrogen additions and the biochemical processes that control N2O emissions. We use bottom-up (inventory, statistical extrapolation of flux measurements, process-based land and ocean modelling) and top-down (atmospheric inversion) approaches to provide a comprehensive quantification of global N2O sources and sinks resulting from 21 natural and human sectors between 1980 and 2016. Global N2O emissions were 17.0 (minimum-maximum estimates: 12.2-23.5) teragrams of nitrogen per year (bottom-up) and 16.9 (15.9-17.7) teragrams of nitrogen per year (top-down) between 2007 and 2016. Global human-induced emissions, which are dominated by nitrogen additions to croplands, increased by 30% over the past four decades to 7.3 (4.2-11.4) teragrams of nitrogen per year. This increase was mainly responsible for the growth in the atmospheric burden. Our findings point to growing N2O emissions in emerging economies-particularly Brazil, China and India. Analysis of process-based model estimates reveals an emerging N2O-climate feedback resulting from interactions between nitrogen additions and climate change. The recent growth in N2O emissions exceeds some of the highest projected emission scenarios3,4, underscoring the urgency to mitigate N2O emissions.

Published
2020

43. Organizing principles for vegetation dynamics

Author

Franklin, O., Harrison, S.P., Dewar, R., Farrior, C.E., Brännström, Å., Dieckmann, U., Pietsch, S., Falster, S., Cramer, W., Loreau, M., Wang, H., Mäkelä, A., Rebel, K.T., Meron, E., Schymanski, S.J., Rovenskaya, E., Stocker, B.D., Zaehle, S., Manzoni, S., van Oijen, My, Wright, I.J., Ciais, P., van Bodegom, P.M., Peñuelas, J., Hofhansl, F., Terrer, C., Soudzilovskaia, N.A., Midgley, G., Prentice, I.C., Franklin, O., Harrison, S.P., Dewar, R., Farrior, C.E., Brännström, Å., Dieckmann, U., Pietsch, S., Falster, S., Cramer, W., Loreau, M., Wang, H., Mäkelä, A., Rebel, K.T., Meron, E., Schymanski, S.J., Rovenskaya, E., Stocker, B.D., Zaehle, S., Manzoni, S., van Oijen, My, Wright, I.J., Ciais, P., van Bodegom, P.M., Peñuelas, J., Hofhansl, F., Terrer, C., Soudzilovskaia, N.A., Midgley, G., and Prentice, I.C.

Published
2020

45. Global carbon budget 2019

Author

Friedlingstein, P., Jones, M. W., O'Sullivan, M., Andrew, R. M., Hauck, J., Peters, G. P., Peters, W., Pongratz, J., Sitch, S., Le Quéré, C., Bakker, D. C. E., Canadell, J. G., Ciais, P., Jackson, R. B., Anthoni, P., Barbero, L., Bastos, A., Bastrikov, V., Becker, M., Bopp, L., Buitenhuis, E., Chandra, N., Chevalier, F., Chini, L. P., Currie, K. I., Feely, R. A., Gehlen, M., Gilfillan, D., Gkritzalis, T., Goll, D. S., Gruber, N., Gutekunst, S., Harris, I., Kato, E., Klein Goldewijk, K., Korsbakken, J. I., Landschützer, P., Lauvset, S. K., Lefèvre, N., Lenton, A., Lienert, S., Lombardozzi, D., Marland, G., McGuire, Patrick C., Melton, J. R., Metzl, N., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S.-I., Neill, C., Omar, A. M., Ono, T., Peregon, A., Pierrot, D., Poulter, B., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Séférian, R., Schwinger, J., Smith, N., Tans, P. P., Tian, H., Tilbrook, B., Tubiello, F. N., ven der Werf, G. R., Wiltshire, A. J., and Zaehle, S.

Abstract

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFF) are based on energy statistics and cement production data, while emissions from land use change (ELUC), mainly deforestation, are based on land use and land use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2009–2018), EFF was 9.5±0.5 GtC yr−1, ELUC 1.5±0.7 GtC yr−1, GATM 4.9±0.02 GtC yr−1 (2.3±0.01 ppm yr−1), SOCEAN 2.5±0.6 GtC yr−1, and SLAND 3.2±0.6 GtC yr−1, with a budget imbalance BIM of 0.4 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For the year 2018 alone, the growth in EFF was about 2.1 % and fossil emissions increased to 10.0±0.5 GtC yr−1, reaching 10 GtC yr−1 for the first time in history, ELUC was 1.5±0.7 GtC yr−1, for total anthropogenic CO2 emissions of 11.5±0.9 GtC yr−1 (42.5±3.3 GtCO2). Also for 2018, GATM was 5.1±0.2 GtC yr−1 (2.4±0.1 ppm yr−1), SOCEAN was 2.6±0.6 GtC yr−1, and SLAND was 3.5±0.7 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 407.38±0.1 ppm averaged over 2018. For 2019, preliminary data for the first 6–10 months indicate a reduced growth in EFF of +0.6 % (range of −0.2 % to 1.5 %) based on national emissions projections for China, the USA, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. Overall, the mean and trend in the five components of the global carbon budget are consistently estimated over the period 1959–2018, but discrepancies of up to 1 GtC yr−1 persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations shows (1) no consensus in the mean and trend in land use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Le Quéré et al., 2018a, b, 2016, 2015a, b, 2014, 2013). The data generated by this work are available at https://doi.org/10.18160/gcp-2019 (Friedlingstein et al., 2019).

Published
2019

46. Warming response of peatland CO2sink is sensitive to seasonality in warming trends

Author

Helbig, M., Živković, T., Alekseychik, P., Aurela, M., El-Madany, T. S., Euskirchen, E. S., Flanagan, L. B., Griffis, T. J., Hanson, P. J., Hattakka, J., Helfter, C., Hirano, T., Humphreys, E. R., Kiely, G., Kolka, R. K., Laurila, T., Leahy, P. G., Lohila, A., Mammarella, I., Nilsson, M. B., Panov, A., Parmentier, F. J. W., Peichl, M., Rinne, J., Roman, D. T., Sonnentag, O., Tuittila, E.-S, Ueyama, M., Vesala, T., Vestin, P., Weldon, S., Weslien, P., and Zaehle, S.

Abstract

Peatlands have acted as net CO2sinks over millennia, exerting a global climate cooling effect. Rapid warming at northern latitudes, where peatlands are abundant, can disturb their CO2sink function. Here we show that sensitivity of peatland net CO2exchange to warming changes in sign and magnitude across seasons, resulting in complex net CO2sink responses. We use multiannual net CO2exchange observations from 20 northern peatlands to show that warmer early summers are linked to increased net CO2uptake, while warmer late summers lead to decreased net CO2uptake. Thus, net CO2sinks of peatlands in regions experiencing early summer warming, such as central Siberia, are more likely to persist under warmer climate conditions than are those in other regions. Our results will be useful to improve the design of future warming experiments and to better interpret large-scale trends in peatland net CO2uptake over the coming few decades.

Published
2022
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48. Direct and seasonal legacy effects of the 2018 heat wave and drought on European ecosystem productivity

Author

Bastos, A., primary, Ciais, P., additional, Friedlingstein, P., additional, Sitch, S., additional, Pongratz, J., additional, Fan, L., additional, Wigneron, J. P., additional, Weber, U., additional, Reichstein, M., additional, Fu, Z., additional, Anthoni, P., additional, Arneth, A., additional, Haverd, V., additional, Jain, A. K., additional, Joetzjer, E., additional, Knauer, J., additional, Lienert, S., additional, Loughran, T., additional, McGuire, P. C., additional, Tian, H., additional, Viovy, N., additional, and Zaehle, S., additional

Published
2020
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49. Sources of Uncertainty in Regional and Global Terrestrial CO2 Exchange Estimates

Author

Bastos, A., primary, O'Sullivan, M., additional, Ciais, P., additional, Makowski, D., additional, Sitch, S., additional, Friedlingstein, P., additional, Chevallier, F., additional, Rödenbeck, C., additional, Pongratz, J., additional, Luijkx, I. T., additional, Patra, P. K., additional, Peylin, P., additional, Canadell, J. G., additional, Lauerwald, R., additional, Li, W., additional, Smith, N. E., additional, Peters, W., additional, Goll, D. S., additional, Jain, A.K., additional, Kato, E., additional, Lienert, S., additional, Lombardozzi, D. L., additional, Haverd, V., additional, Nabel, J. E. M. S., additional, Poulter, B., additional, Tian, H., additional, Walker, A. P., additional, and Zaehle, S., additional

Published
2020
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