449 results on '"Viovy, N."'
Search Results
2. Variability and quasi-decadal changes in the methane budget over the period 2000-2012
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Saunois, M, Bousquet, P, Poulter, B, Peregon, A, Ciais, P, Canadell, JG, Dlugokencky, EJ, Etiope, G, Bastviken, D, Houweling, S, Janssens-Maenhout, G, Tubiello, FN, Castaldi, S, Jackson, RB, Alexe, M, Arora, VK, Beerling, DJ, Bergamaschi, P, Blake, DR, Brailsford, G, Bruhwiler, L, Crevoisier, C, Crill, P, Covey, K, Frankenberg, C, Gedney, N, Höglund-Isaksson, L, Ishizawa, M, Ito, A, Joos, F, Kim, HS, Kleinen, T, Krummel, P, Lamarque, JF, Langenfelds, R, Locatelli, R, Machida, T, Maksyutov, S, Melton, JR, Morino, I, Naik, V, O'Doherty, S, Parmentier, FJW, Patra, PK, Peng, C, Peng, S, Peters, GP, Pison, I, Prinn, R, Ramonet, M, Riley, WJ, Saito, M, Santini, M, Schroeder, R, Simpson, IJ, Spahni, R, Takizawa, A, Thornton, BF, Tian, H, Tohjima, Y, Viovy, N, Voulgarakis, A, Weiss, R, Wilton, DJ, Wiltshire, A, Worthy, D, Wunch, D, Xu, X, Yoshida, Y, Zhang, B, Zhang, Z, and Zhu, Q
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Meteorology & Atmospheric Sciences ,Atmospheric Sciences ,Astronomical and Space Sciences - Abstract
Following the recent Global Carbon Project (GCP) synthesis of the decadal methane (CH4) budget over 2000-2012 (Saunois et al., 2016), we analyse here the same dataset with a focus on quasi-decadal and inter-annual variability in CH4 emissions. The GCP dataset integrates results from top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models (including process-based models for estimating land surface emissions and atmospheric chemistry), inventories of anthropogenic emissions, and data-driven approaches. The annual global methane emissions from top-down studies, which by construction match the observed methane growth rate within their uncertainties, all show an increase in total methane emissions over the period 2000-2012, but this increase is not linear over the 13 years. Despite differences between individual studies, the mean emission anomaly of the top-down ensemble shows no significant trend in total methane emissions over the period 2000-2006, during the plateau of atmospheric methane mole fractions, and also over the period 2008-2012, during the renewed atmospheric methane increase. However, the top-down ensemble mean produces an emission shift between 2006 and 2008, leading to 22 [16-32]Tg CH4yr-1 higher methane emissions over the period 2008-2012 compared to 2002-2006. This emission increase mostly originated from the tropics, with a smaller contribution from mid-latitudes and no significant change from boreal regions. The regional contributions remain uncertain in top-down studies. Tropical South America and South and East Asia seem to contribute the most to the emission increase in the tropics. However, these two regions have only limited atmospheric measurements and remain therefore poorly constrained. The sectorial partitioning of this emission increase between the periods 2002-2006 and 2008-2012 differs from one atmospheric inversion study to another. However, all top-down studies suggest smaller changes in fossil fuel emissions (from oil, gas, and coal industries) compared to the mean of the bottom-up inventories included in this study. This difference is partly driven by a smaller emission change in China from the top-down studies compared to the estimate in the Emission Database for Global Atmospheric Research (EDGARv4.2) inventory, which should be revised to smaller values in a near future. We apply isotopic signatures to the emission changes estimated for individual studies based on five emission sectors and find that for six individual top-down studies (out of eight) the average isotopic signature of the emission changes is not consistent with the observed change in atmospheric 13CH4. However, the partitioning in emission change derived from the ensemble mean is consistent with this isotopic constraint. At the global scale, the top-down ensemble mean suggests that the dominant contribution to the resumed atmospheric CH4 growth after 2006 comes from microbial sources (more from agriculture and waste sectors than from natural wetlands), with an uncertain but smaller contribution from fossil CH4 emissions. In addition, a decrease in biomass burning emissions (in agreement with the biomass burning emission databases) makes the balance of sources consistent with atmospheric 13CH4 observations. In most of the top-down studies included here, OH concentrations are considered constant over the years (seasonal variations but without any inter-annual variability). As a result, the methane loss (in particular through OH oxidation) varies mainly through the change in methane concentrations and not its oxidants. For these reasons, changes in the methane loss could not be properly investigated in this study, although it may play a significant role in the recent atmospheric methane changes as briefly discussed at the end of the paper.
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- 2017
3. Global wetland contribution to 2000-2012 atmospheric methane growth rate dynamics
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Poulter, B, Bousquet, P, Canadell, JG, Ciais, P, Peregon, A, Saunois, M, Arora, VK, Beerling, DJ, Brovkin, V, Jones, CD, Joos, F, Gedney, N, Ito, A, Kleinen, T, Koven, CD, McDonald, K, Melton, JR, Peng, C, Peng, S, Prigent, C, Schroeder, R, Riley, WJ, Saito, M, Spahni, R, Tian, H, Taylor, L, Viovy, N, Wilton, D, Wiltshire, A, Xu, X, Zhang, B, Zhang, Z, and Zhu, Q
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methanogenesis ,wetlands ,methane ,Meteorology & Atmospheric Sciences - Abstract
Increasing atmospheric methane (CH4) concentrations have contributed to approximately 20% of anthropogenic climate change. Despite the importance of CH4 as a greenhouse gas, its atmospheric growth rate and dynamics over the past two decades, which include a stabilization period (1999-2006), followed by renewed growth starting in 2007, remain poorly understood. We provide an updated estimate of CH4 emissions from wetlands, the largest natural global CH4 source, for 2000-2012 using an ensemble of biogeochemical models constrained with remote sensing surface inundation and inventory-based wetland area data. Between 2000-2012, boreal wetland CH4 emissions increased by 1.2 Tg yr-1 (-0.2-3.5 Tg yr-1), tropical emissions decreased by 0.9 Tg yr-1 (-3.2-1.1 Tg yr-1), yet globally, emissions remained unchanged at 184 22 Tg yr-1. Changing air temperature was responsible for increasing high-latitude emissions whereas declines in low-latitude wetland area decreased tropical emissions; both dynamics are consistent with features of predicted centennial-scale climate change impacts on wetland CH4 emissions. Despite uncertainties in wetland area mapping, our study shows that global wetland CH4 emissions have not contributed significantly to the period of renewed atmospheric CH4 growth, and is consistent with findings from studies that indicate some combination of increasing fossil fuel and agriculture-related CH4 emissions, and a decrease in the atmospheric oxidative sink.
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- 2017
4. The global methane budget 2000-2012
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Saunois, M, Bousquet, P, Poulter, B, Peregon, A, Ciais, P, Canadell, JG, Dlugokencky, EJ, Etiope, G, Bastviken, D, Houweling, S, Janssens-Maenhout, G, Tubiello, FN, Castaldi, S, Jackson, RB, Alexe, M, Arora, VK, Beerling, DJ, Bergamaschi, P, Blake, DR, Brailsford, G, Brovkin, V, Bruhwiler, L, Crevoisier, C, Crill, P, Covey, K, Curry, C, Frankenberg, C, Gedney, N, Höglund-Isaksson, L, Ishizawa, M, Ito, A, Joos, F, Kim, HS, Kleinen, T, Krummel, P, Lamarque, JF, Langenfelds, R, Locatelli, R, Machida, T, Maksyutov, S, McDonald, KC, Marshall, J, Melton, JR, Morino, I, Naik, V, O'Doherty, S, Parmentier, FJW, Patra, PK, Peng, C, Peng, S, Peters, GP, Pison, I, Prigent, C, Prinn, R, Ramonet, M, Riley, WJ, Saito, M, Santini, M, Schroeder, R, Simpson, IJ, Spahni, R, Steele, P, Takizawa, A, Thornton, BF, Tian, H, Tohjima, Y, Viovy, N, Voulgarakis, A, Van Weele, M, Van Der Werf, GR, Weiss, R, Wiedinmyer, C, Wilton, DJ, Wiltshire, A, Worthy, D, Wunch, D, Xu, X, Yoshida, Y, Zhang, B, Zhang, Z, and Zhu, Q
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Atmospheric Sciences ,Geochemistry ,Physical Geography and Environmental Geoscience - Abstract
The global methane (CH4) budget is becoming an increasingly important component for managing realistic pathways to mitigate climate change. This relevance, due to a shorter atmospheric lifetime and a stronger warming potential than carbon dioxide, is challenged by the still unexplained changes of atmospheric CH4 over the past decade. Emissions and concentrations of CH4 are continuing to increase, making CH4 the second most important human-induced greenhouse gas after carbon dioxide. Two major difficulties in reducing uncertainties come from the large variety of diffusive CH4 sources that overlap geographically, and from the destruction of CH4 by the very short-lived hydroxyl radical (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate research on the methane cycle, and producing regular (g1/4 biennial) updates of the global methane budget. This consortium includes atmospheric physicists and chemists, biogeochemists of surface and marine emissions, and socio-economists who study anthropogenic emissions. Following Kirschke et al. (2013), we propose here the first version of a living review paper that integrates results of top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models, inventories and data-driven approaches (including process-based models for estimating land surface emissions and atmospheric chemistry, and inventories for anthropogenic emissions, data-driven extrapolations). For the 2003-2012 decade, global methane emissions are estimated by top-down inversions at 558g Tgg CH4g yrg'1, range 540-568. About 60g % of global emissions are anthropogenic (range 50-65g %). Since 2010, the bottom-up global emission inventories have been closer to methane emissions in the most carbon-intensive Representative Concentrations Pathway (RCP8.5) and higher than all other RCP scenarios. Bottom-up approaches suggest larger global emissions (736g Tgg CH4g yrg'1, range 596-884) mostly because of larger natural emissions from individual sources such as inland waters, natural wetlands and geological sources. Considering the atmospheric constraints on the top-down budget, it is likely that some of the individual emissions reported by the bottom-up approaches are overestimated, leading to too large global emissions. Latitudinal data from top-down emissions indicate a predominance of tropical emissions (g1/4 64g % of the global budget, http://doi.org/10.3334/CDIAC/GLOBAL-METHANE-BUDGET-2016-V1.1) and the Global Carbon Project.
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- 2016
5. The terrestrial carbon budget of South and Southeast Asia
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Cervarich, M, Shu, S, Jain, AK, Arneth, A, Canadell, J, Friedlingstein, P, Houghton, RA, Kato, E, Koven, C, Patra, P, Poulter, B, Sitch, S, Stocker, B, Viovy, N, Wiltshire, A, and Zeng, N
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Meteorology & Atmospheric Sciences - Abstract
Accomplishing the objective of the current climate policies will require establishing carbon budget and flux estimates in each region and county of the globe by comparing and reconciling multiple estimates including the observations and the results of top-down atmospheric carbon dioxide (CO2) inversions and bottom-up dynamic global vegetation models. With this in view, this study synthesizes the carbon source/sink due to net ecosystem productivity (NEP), land cover land use change (E LUC), fires and fossil burning (E FIRE) for the South Asia (SA), Southeast Asia (SEA) and South and Southeast Asia (SSEA = SA + SEA) and each country in these regions using the multiple top-down and bottom-up modeling results. The terrestrial net biome productivity (NBP = NEP - E LUC - E FIRE) calculated based on bottom-up models in combination with E FIRE based on GFED4s data show net carbon sinks of 217 ±147, 10 ±55, and 227 ±279 TgC yr-1 for SA, SEA, and SSEA. The top-down models estimated NBP net carbon sinks were 20 ±170, 4 ±90 and 24 ±180 TgC yr-1. In comparison, regional emissions from the combustion of fossil fuels were 495, 275, and 770 TgC yr-1, which are many times higher than the NBP sink estimates, suggesting that the contribution of the fossil fuel emissions to the carbon budget of SSEA results in a significant net carbon source during the 2000s. When considering both NBP and fossil fuel emissions for the individual countries within the regions, Bhutan and Laos were net carbon sinks and rest of the countries were net carbon source during the 2000s. The relative contributions of each of the fluxes (NBP, NEP, E LUC, and E FIRE, fossil fuel emissions) to a nation's net carbon flux varied greatly from country to country, suggesting a heterogeneous dominant carbon fluxes on the country-level throughout SSEA.
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- 2016
6. Role of CO2, climate and land use in regulating the seasonal amplitude increase of carbon fluxes in terrestrial ecosystems: A multimodel analysis
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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
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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.
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- 2016
7. Greening of the Earth and its drivers
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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
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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.
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- 2016
8. Global Carbon Budget 2015
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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
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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
9. Simulating boreal forest carbon dynamics after stand-replacing fire disturbance: insights from a global process-based vegetation model
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Yue, C., Ciais, P., Luyssaert, S., Cadule, P., Harden, J., Randerson, J., Bellassen, V., Wang, T., Piao, S. L, Poulter, B., and Viovy, N.
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boreal forest ,carbon cycle ,carbon dioxide ,forest fire ,global change ,self thinning ,stand structure ,vegetation dynamics ,Alaska ,Canada ,United States - Abstract
Stand-replacing fires are the dominant fire type in North American boreal forests. They leave a historical legacy of a mosaic landscape of different aged forest cohorts. This forest age dynamics must be included in vegetation models to accurately quantify the role of fire in the historical and current regional forest carbon balance. The present study adapted the global process-based vegetation model ORCHIDEE to simulate the CO2 emissions from boreal forest fire and the subsequent recovery after a stand-replacing fire; the model represents postfire new cohort establishment, forest stand structure and the self-thinning process. Simulation results are evaluated against observations of three clusters of postfire forest chronosequences in Canada and Alaska. The variables evaluated include: fire carbon emissions, CO2 fluxes (gross primary production, total ecosystem respiration and net ecosystem exchange), leaf area index, and biometric measurements (aboveground biomass carbon, forest floor carbon, woody debris carbon, stand individual density, stand basal area, and mean diameter at breast height). When forced by local climate and the atmospheric CO2 history at each chronosequence site, the model simulations generally match the observed CO2 fluxes and carbon stock data well, with model-measurement mean square root of deviation comparable with the measurement accuracy (for CO2 flux ~100 g C m−2 yr−1, for biomass carbon ~1000 g C m−2 and for soil carbon ~2000 g C m−2). We find that the current postfire forest carbon sink at the evaluation sites, as observed by chronosequence methods, is mainly due to a combination of historical CO2 increase and forest succession. Climate change and variability during this period offsets some of these expected carbon gains. The negative impacts of climate were a likely consequence of increasing water stress caused by significant temperature increases that were not matched by concurrent increases in precipitation. Our simulation results demonstrate that a global vegetation model such as ORCHIDEE is able to capture the essential ecosystem processes in fire-disturbed boreal forests and produces satisfactory results in terms of both carbon fluxes and carbon-stock evolution after fire. This makes the model suitable for regional simulations in boreal regions where fire regimes play a key role in the ecosystem carbon balance.
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- 2013
10. Trends in the sources and sinks of carbon dioxide
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Le Quéré, C, Raupach, MR, Canadell, JG, Marland, G, Bopp, L, Ciais, P, Conway, TJ, Doney, SC, Feely, RA, Foster, P, Friedlingstein, P, Gurney, K, Houghton, RA, House, JI, Huntingford, C, Levy, PE, Lomas, MR, Majkut, J, Metzl, N, Ometto, JP, Peters, GP, Prentice, IC, Randerson, JT, Running, SW, Sarmiento, JL, Schuster, U, Sitch, S, Takahashi, T, Viovy, N, Van Der Werf, GR, and Woodward, FI
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Meteorology & Atmospheric Sciences - Abstract
Efforts to control climate change require the stabilization of atmospheric CO 2 concentrations. This can only be achieved through a drastic reduction of global CO 2 emissions. Yet fossil fuel emissions increased by 29% between 2000 and 2008, in conjunction with increased contributions from emerging economies, from the production and international trade of goods and services, and from the use of coal as a fuel source. In contrast, emissions from land-use changes were nearly constant. Between 1959 and 2008, 43% of each year's CO 2 emissions remained in the atmosphere on average; the rest was absorbed by carbon sinks on land and in the oceans. In the past 50 years, the fraction of CO 2 emissions that remains in the atmosphere each year has likely increased, from about 40% to 45%, and models suggest that this trend was caused by a decrease in the uptake of CO 2 by the carbon sinks in response to climate change and variability. Changes in the CO 2 sinks are highly uncertain, but they could have a significant influence on future atmospheric CO 2 levels. It is therefore crucial to reduce the uncertainties. © 2009 Macmillan Publishers Limited. All rights reserved.
- Published
- 2009
11. Simulating carbon and water fluxes over croplands with ORCHIDEE-STICS model : Multi-site evaluation and sensitivity to management drivers
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Li, L., Vuichard, N., Viovy, N., Ciais, P., Béziat, P., Cellier, P., Ceschia, E., Eugster, W., Grünwald, T., Laboratoire des Sciences du Climat et de l'Environnement (LSCE), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Centre National de la Recherche Scientifique (CNRS), Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
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[SDU]Sciences of the Universe [physics] - Abstract
International audience; Cropland ecosystem is one of the most uncertain components of the terrestrial Carbon budget at European scale. In this context, a dual effort has been initiated within the CarboEurope-IP project named as the Cropland Synthesis Activity that aims 1) to monitor and analyse C flux over crop sites and 2) to develop and refine crop model's simulations from site to continental scale. Here, we will present the results obtained with the ORCHIDEE-STICS model within the frame of this activity. In this coupled model, the agronomy-oriented model STICS provides its calculated Leaf Area Index (LAI) to the dynamic global vegetation model ORCHIDEE in order to better calculate the Growth Primary Production (GPP) and related C fluxes for crop ecosystem. With this model we performed simulations on several wheat and maize sites. Overall, ORCHIDEE-STICS agrees well with the observations especially for wheat. We will assess from the misfit between model and data, where structural improvements of the model are needed, and what is the beneficial effect of these improvements. Four main forms of model improvements will be tested : i) optimal adjustment of generic physiological parameters of ORCHIDEE, ii) adjustment of agricultural technology, iii) adjustment of crop varieties phenological parameters and iv) realistic reproduction of each site cultivation history. All this information being rather uncertain at the European scale, this assessment is particularly of importance and will help to rank priorities for future model's developments. The model data comparison will focus on NEE, GPP, Reco fluxes, but also involve latent and sensible heat flux observation.
- Published
- 2023
12. Potential impacts of climate change on the productivity and soil carbon stocks of managed grasslands
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Puche, N. J. B., primary, Kirschbaum, M. U. F., additional, Viovy, N., additional, and Chabbi, Abad, additional
- Published
- 2023
- Full Text
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13. Are Land-Use Change Emissions in Southeast Asia Decreasing or Increasing?
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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.
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- 2022
14. Historical Carbon Dioxide Emissions Caused by Land-Use Changes are Possibly Larger than Assumed
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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.
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- 2017
- Full Text
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15. Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5
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Dufresne, J.-L., Foujols, M.-A., Denvil, S., Caubel, A., Marti, O., Aumont, O., Balkanski, Y., Bekki, S., Bellenger, H., Benshila, R., Bony, S., Bopp, L., Braconnot, P., Brockmann, P., Cadule, P., Cheruy, F., Codron, F., Cozic, A., Cugnet, D., de Noblet, N., Duvel, J.-P., Ethé, C., Fairhead, L., Fichefet, T., Flavoni, S., Friedlingstein, P., Grandpeix, J.-Y., Guez, L., Guilyardi, E., Hauglustaine, D., Hourdin, F., Idelkadi, A., Ghattas, J., Joussaume, S., Kageyama, M., Krinner, G., Labetoulle, S., Lahellec, A., Lefebvre, M.-P., Lefevre, F., Levy, C., Li, Z. X., Lloyd, J., Lott, F., Madec, G., Mancip, M., Marchand, M., Masson, S., Meurdesoif, Y., Mignot, J., Musat, I., Parouty, S., Polcher, J., Rio, C., Schulz, M., Swingedouw, D., Szopa, S., Talandier, C., Terray, P., Viovy, N., and Vuichard, N.
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- 2013
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16. Climate warming from managed grasslands cancels the cooling effect of carbon sinks in sparsely grazed and natural grasslands
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Chang, J., Gasser, T., Smith, P., Herrero, M., Havlik, P., Obersteiner, M., Guenet, B., Goll, D.S., Li, W., Naipal, V., Peng, S., Qiu, C., Tian, H., Viovy, N., Yue, C., Zhu, D., Chang, J., Gasser, T., Smith, P., Herrero, M., Havlik, P., Obersteiner, M., Guenet, B., Goll, D.S., Li, W., Naipal, V., Peng, S., Qiu, C., Tian, H., Viovy, N., Yue, C., and Zhu, D.
- Abstract
Grasslands absorb and release carbon dioxide (CO2), emit methane (CH4) from grazing livestock, and emit nitrous oxide (N2O) from soils. Little is known about how the fluxes of these three greenhouse gases, from managed and natural grasslands worldwide, have contributed to past climate change, or the roles of managed pastures versus natural grasslands. Here, global trends and regional patterns of the full greenhouse gas balance of grasslands are estimated for the period 1750 to 2012. A new spatially explicit land surface model is applied, to separate the direct effects of human activities from land management and the indirect effects from climate change, increasing CO2 and regional changes in nitrogen deposition. Direct human management activities are simulated to have caused grasslands to switch from a sink to a source of greenhouse gas, because of increased livestock numbers and accelerated conversion of natural lands to pasture. However, climate change drivers contributed a net carbon sink in soil organic matter, mainly from the increased productivity of grasslands due to increased CO2 and nitrogen deposition. The net radiative forcing of all grasslands is currently close to neutral, but has been increasing since the 1960s. Here, we show that the net global climate warming caused by managed grassland cancels the net climate cooling from carbon sinks in sparsely grazed and natural grasslands. In the face of future climate change and increased demand for livestock products, these findings highlight the need to use sustainable management to preserve and enhance soil carbon storage in grasslands and to reduce greenhouse gas emissions from managed grasslands.
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- 2021
17. Global-Scale Assessment of Vegetation Phenology Using NOAA/AVHRR Satellite Measurements
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Moulin, S., Kergoat, L., Viovy, N., and Dedieu, G.
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- 1997
18. The Global Methane Budget 2000–2017
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Saunois, M., Stavert, A.R., Poulter, B., Bousquet, P., Canadell, J.G., Jackson, R.B., Raymond, P.A., Dlugokencky, E.J., Houweling, S., Patra, Prabir K., Ciais, P., Arora, V.K., Bastviken, D., Bergamaschi, P., Blake, D.R., Brailsford, G., Bruhwiler, L., Carlson, K.M., Carrol, M., Castaldi, S., Chandra, N., Crevoisier, C., Crill, P.M., Covey, K., Curry, C.L., Etiope, G., Frankenberg, C., Gedney, N., Hegglin, M.I., Höglund-Isaksson, L., Hugelius, G., Ishizawa, M., Ito, A., Janssens-Maenhout, G.reet, Jensen, K.M., Joos, F., Kleinen, T., Krummel, P.B., Langenfelds, R.L., Laruelle, G.G., Liu, L., Machida, T., Maksyutov, S., McDonald, K.C., McNorton, J., Miller, P.A., Melton, J.R., Morino, I., Müller, J., Murguia-Flores, F., Naik, V., Niwa, Y., Noce, S., O'Doherty, S., Parker, R.J., Peng, C., Peng, S., Peters, G.P., Prigent, C., Prinn, R., Ramonet, M., Regnier, P., Riley, W.J., Rosentreter, J.A., Segers, A., Simpson, I.J., Shi, H., Smith, S.J., Steele, L. P., Thornton, B.F., Tian, H., Tohjima, Y., Tubiello, F.N., Tsuruta, A., Viovy, N., Voulgarakis, A., Weber, T.S., van Weele, M., van der Werf, G.R., Weiss, R.F., Worthy, D., Wunch, D., Yin, Y., Yoshida, Y., Zhang, W., Zhang, Z., Zhao, Y., Zheng, B., Zhu, Q., Zhuang, Q., Saunois, M., Stavert, A.R., Poulter, B., Bousquet, P., Canadell, J.G., Jackson, R.B., Raymond, P.A., Dlugokencky, E.J., Houweling, S., Patra, Prabir K., Ciais, P., Arora, V.K., Bastviken, D., Bergamaschi, P., Blake, D.R., Brailsford, G., Bruhwiler, L., Carlson, K.M., Carrol, M., Castaldi, S., Chandra, N., Crevoisier, C., Crill, P.M., Covey, K., Curry, C.L., Etiope, G., Frankenberg, C., Gedney, N., Hegglin, M.I., Höglund-Isaksson, L., Hugelius, G., Ishizawa, M., Ito, A., Janssens-Maenhout, G.reet, Jensen, K.M., Joos, F., Kleinen, T., Krummel, P.B., Langenfelds, R.L., Laruelle, G.G., Liu, L., Machida, T., Maksyutov, S., McDonald, K.C., McNorton, J., Miller, P.A., Melton, J.R., Morino, I., Müller, J., Murguia-Flores, F., Naik, V., Niwa, Y., Noce, S., O'Doherty, S., Parker, R.J., Peng, C., Peng, S., Peters, G.P., Prigent, C., Prinn, R., Ramonet, M., Regnier, P., Riley, W.J., Rosentreter, J.A., Segers, A., Simpson, I.J., Shi, H., Smith, S.J., Steele, L. P., Thornton, B.F., Tian, H., Tohjima, Y., Tubiello, F.N., Tsuruta, A., Viovy, N., Voulgarakis, A., Weber, T.S., van Weele, M., van der Werf, G.R., Weiss, R.F., Worthy, D., Wunch, D., Yin, Y., Yoshida, Y., Zhang, W., Zhang, Z., Zhao, Y., Zheng, B., Zhu, Q., and Zhuang, Q.
- Abstract
Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH4 yr−1 (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH4 yr−1 or ∼ 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4 yr−1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 Tg CH4 yr−1 larger than our estimat
- Published
- 2020
19. Simulating the fluxes of CO 2 and N 2O in European grasslands with the Pasture Simulation Model (PaSim)
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Calanca, P., Vuichard, N., Campbell, C., Viovy, N., Cozic, A., Fuhrer, J., and Soussana, J.-F.
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- 2007
- Full Text
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20. Europe-wide reduction in primary productivity caused by the heat and drought in 2003
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Ciais, Ph., Reichstein, M., Viovy, N., Granier, A., Ogee, J., Allard, V., Aubinet, M., Buchmann, N., Bernhofer, Chr., Carrara, A., Chevallier, F., De Noblet, N., Friend, A. D., Friedlingstein, P., Grunwald, T., Heinesch, B., Keronen, P., Knohl, A., Krinner, G., Loustau, D., Manca, G., Matteucci, G., Miglietta, F., Ourcival, J. M., Papale, D., Pilegaard, K., Rambal, S., Seufert, G., Soussana, J. F., Sanz, M. J., Schulze, E. D., Vesala, T., and Valentini, R.
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Environmental issues ,Science and technology ,Zoology and wildlife conservation - Abstract
Author(s): Ph. Ciais (corresponding author) [1]; M. Reichstein [2, 3]; N. Viovy [1]; A. Granier [4]; J. Ogée [5]; V. Allard [6]; M. Aubinet [7]; N. Buchmann [8]; Chr. Bernhofer [...]
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- 2005
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21. Direct and seasonal legacy effects of the 2018 heat wave and drought on European ecosystem productivity
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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
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- 2020
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- View/download PDF
22. Impacts of climate change on temperate forests and interaction with management.
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Loustau, D., primary, Ogée, J., additional, Dufrêne, E., additional, Déqué, M., additional, Dupouey, J. L., additional, Badeau, V., additional, Viovy, N., additional, Ciais, P., additional, Desprez-Loustau, M. L., additional, Roques, A., additional, Chuine, I., additional, and Mouillot, F., additional
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- 2007
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23. Increased Global Land Carbon Sink Due to Aerosol‐Induced Cooling
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Zhang, Y., Goll, D., Bastos, A., Balkanski, Y., Boucher, O., Cescatti, A., Collier, M., Gasser, T., Ghattas, J., Li, L., Piao, S., Viovy, N., Zhu, D., Ciais, P., Zhang, Y., Goll, D., Bastos, A., Balkanski, Y., Boucher, O., Cescatti, A., Collier, M., Gasser, T., Ghattas, J., Li, L., Piao, S., Viovy, N., Zhu, D., and Ciais, P.
- Abstract
Anthropogenic aerosols have contributed to historical climate change through their interactions with radiation and clouds. In turn, climate change due to aerosols has impacted the C cycle. Here we use a set of offline simulations made with the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model driven by bias-corrected climate fields from simulations of three Coupled Model Intercomparison Project Phase 5 (CMIP5) Earth system models (ESMs; IPSL-CM5A-LR, CSIRO-Mk3.6.0, and GISS-E2-R) to quantify the climate-related impacts of aerosols on land carbon fluxes during 1860–2005. We found that climate change from anthropogenic aerosols (CCAA) globally cooled the climate, and increased land carbon storage, or cumulative net biome production (NBP), by 11.6–41.8 PgC between 1860 and 2005. The increase in NBP from CCAA mainly occurs in the tropics and northern midlatitudes, primarily due to aerosol-induced cooling. At high latitudes, cooling caused stronger decrease in gross primary production (GPP) than in total ecosystem respiration (TER), leading to lower NBP. At midlatitudes, cooling-induced decrease in TER is stronger than that of GPP, resulting in NBP increase. At low latitudes, NBP was also enhanced due to the cooling-induced GPP increase, but precipitation decline from CCAA may negate the effect of temperature. The three ESMs show large divergence in low-latitude CCAA precipitation response to aerosols, which results in considerable uncertainties in regional estimations of CCAA effects on carbon fluxes. Our results suggest that better understanding and simulation of how anthropogenic aerosols affect precipitation in ESMs is required for a more accurate attribution of aerosol effects on the terrestrial carbon cycle.
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- 2019
24. Impact of the 2015-16 El Nino on the terrestrial carbon cycle constrained by bottom-up and top-down approaches
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Bastos, A., Friedlingstein, P., Sitch, S., Chen, C., Mialon, A., Wigneron, J., Arora, V., Briggs, P., Canadell, J., Ciais, P., Chevallier, F., Cheng, L., Delire, C., Haverd, V., Jain, A., Joos, F., Kato, E., Lienert, S., Lombardozzi, D., Melton, J., Myneni, R., Nabel, J., https://orcid.org/0000-0002-8122-5206, Pongratz, J., https://orcid.org/0000-0003-0372-3960, Poulter, B., Rödenbeck, C., Séférian, R., Tian, H., van Eck, C., Viovy, N., Vuichard, N., Walker, A., Wiltshire, A., Yang, J., Zaehle, S., Zeng, N., and Zhu, D.
- Abstract
Evaluating the response of the land carbon sink to the anomalies in temperature and drought imposed by El Niño events provides insights into the present-day carbon cycle and its climate-driven variability. It is also a necessary step to build confidence in terrestrial ecosystems models' response to the warming and drying stresses expected in the future over many continents, and particularly in the tropics. Here we present an in-depth analysis of the response of the terrestrial carbon cycle to the 2015/2016 El Niño that imposed extreme warming and dry conditions in the tropics and other sensitive regions. First, we provide a synthesis of the spatio-temporal evolution of anomalies in net land–atmosphere CO2 fluxes estimated by two in situ measurements based on atmospheric inversions and 16 land-surface models (LSMs) from TRENDYv6. Simulated changes in ecosystem productivity, decomposition rates and fire emissions are also investigated. Inversions and LSMs generally agree on the decrease and subsequent recovery of the land sink in response to the onset, peak and demise of El Niño conditions and point to the decreased strength of the land carbon sink: by 0.4–0.7 PgC yr−1 (inversions) and by 1.0 PgC yr−1 (LSMs) during 2015/2016. LSM simulations indicate that a decrease in productivity, rather than increase in respiration, dominated the net biome productivity anomalies in response to ENSO throughout the tropics, mainly associated with prolonged drought conditions.This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications’.
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- 2018
25. Interactions between nitrogen deposition, land cover conversion, and climate change determine the contemporary carbon balance of Europe
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Churkina, G., Zaehle, S., Hughes, J., Viovy, N., Chen, Y., Jung, M., Heumann, B., Ramankutty, N., Heimann, M., Jones, C., Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
- Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere ,lcsh:Geology ,lcsh:QH501-531 ,lcsh:QH540-549.5 ,lcsh:QE1-996.5 ,lcsh:Life ,lcsh:Ecology ,[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment ,ComputingMilieux_MISCELLANEOUS - Abstract
European ecosystems are thought to take up large amounts of carbon, but neither the rate nor the contributions of the underlying processes are well known. In the second half of the 20th century, carbon dioxide concentrations have risen by more that 100 ppm, atmospheric nitrogen deposition has more than doubled, and European mean temperatures were increasing by 0.02 °C yr−1. The extents of forest and grasslands have increased with the respective rates of 5800 km2 yr−1 and 1100 km2 yr−1 as agricultural land has been abandoned at a rate of 7000 km2 yr−1. In this study, we analyze the responses of European land ecosystems to the aforementioned environmental changes using results from four process-based ecosystem models: BIOME-BGC, JULES, ORCHIDEE, and O-CN. The models suggest that European ecosystems sequester carbon at a rate of 56 TgC yr−1 (mean of four models for 1951–2000) with strong interannual variability (±88 TgC yr−1, average across models) and substantial inter-model uncertainty (±39 TgC yr−1). Decadal budgets suggest that there has been a continuous increase in the mean net carbon storage of ecosystems from 85 TgC yr−1 in 1980s to 108 TgC yr−1 in 1990s, and to 114 TgC yr−1 in 2000–2007. The physiological effect of rising CO2 in combination with nitrogen deposition and forest re-growth have been identified as the important explanatory factors for this net carbon storage. Changes in the growth of woody vegetation are suggested as an important contributor to the European carbon sink. Simulated ecosystem responses were more consistent for the two models accounting for terrestrial carbon-nitrogen dynamics than for the two models which only accounted for carbon cycling and the effects of land cover change. Studies of the interactions of carbon-nitrogen dynamics with land use changes are needed to further improve the quantitative understanding of the driving forces of the European land carbon balance.
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- 2018
26. Corrigendum to 'Impact of CO2 and climate on the Last Glacial Maximum vegetation: results from the ORCHIDEE/IPSL models' published in Clim. Past, 7, 557–577, 2011
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Woillez, M.-N., Kageyama, M., Krinner, G., De Noblet-Ducoudré, N., Viovy, N., Mancip, M., 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), Modélisation du climat (CLIM), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Extrèmes : Statistiques, Impacts et Régionalisation (ESTIMR), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), and Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)
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[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere ,lcsh:GE1-350 ,lcsh:Environmental pollution ,lcsh:Environmental protection ,lcsh:TD172-193.5 ,lcsh:TD169-171.8 ,[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment ,ComputingMilieux_MISCELLANEOUS ,lcsh:Environmental sciences - Abstract
International audience
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- 2018
27. Global carbon budget 2018 [Data Paper]
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Le Quéré, C., Andrew, R. M., Friedlingstein, P., Sitch, S., Hauck, J., Pongratz, J., Pickers, P. A., Korsbakken, J. I., Peters, G. P., Canadell, J. G., Arneth, A., Arora, V. K., Barbero, L., Bastos, A., Bopp, L., Chevallier, F., Chini, L. P., Ciais, P., Doney, S. C., Gkritzalis, T., Goll, D. S., Harris, I., Haverd, V., Hoffman, F. M., Hoppema, M., Houghton, R. A., Hurtt, G., Ilyina, T., Jain, A. K., Johannessen, T., Jones, C. D., Kato, E., Keeling, R. F., Goldewijk, K. K., Landschutzer, P., Lefèvre, Nathalie, Lienert, S., Liu, Z., Lombardozzi, D., Metzl, N., Munro, D. R., Nabel, Jems, Nakaoka, S., Neill, C., Olsen, A., Ono, T., Patra, P., Peregon, A., Peters, W., Peylin, P., Pfeil, B., Pierrot, D., Poulter, B., Rehder, G., Resplandy, L., Robertson, E., Rocher, M., Rodenbeck, C., Schuster, U., Schwinger, J., Seferian, R., Skjelvan, I., Steinhoff, T., Sutton, A., Tans, P. P., Tian, H. Q., Tilbrook, B., Tubiello, F. N., van der Laan-Luijkx, I. T., van der Werf, G. R., Viovy, N., Walker, A. P., Wiltshire, A. J., Wright, R., Zaehle, S., and Zheng, B.
- 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 (E-FF) are based on energy statistics and cement production data, while emissions from land use and land-use change (E-LUC), 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 (G(ATM)) is computed from the annual changes in concentration. The ocean CO2 sink (S-OCEAN) and terrestrial CO2 sink (S-LAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (B-IM), 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 +/- 1 sigma. For the last decade available (2008-2017), E-FF was 9.4 +/- 0.5 GtC yr(-1), E-LUC 1.5 +/- 0.7 GtC yr(-1), G(ATM) 4.7 +/- 0.02 GtC yr(-1), S-OCEAN 2.4 +/- 0.5 GtC yr(-1), and S-LAND 3.2 +/- 0.8 GtC yr(-1), with a budget imbalance B-IM of 0.5 GtC yr(-1) indicating overestimated emissions and/or underestimated sinks. For the year 2017 alone, the growth in E-FF was about 1.6 % and emissions increased to 9.9 +/- 0.5 GtC yr(-1). Also for 2017, E-LUC was 1.4 +/- 0.7 GtC yr(-1), G(ATM) was 4.6 +/- 0.2 GtC yr(-1), S-OCEAN was 2.5 +/- 0.5 GtC yr(-1), and S-LAND was 3.8 +/- 0.8 GtC yr(-1), with a B-IM of 0.3 GtC. The global atmospheric CO2 concentration reached 405.0 +/- 0.1 ppm averaged over 2017. For 2018, preliminary data for the first 6-9 months indicate a renewed growth in E-FF of +2.7 % (range of 1.8 % to 3.7 %) based on national emission projections for China, the US, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. The analysis presented here shows that the mean and trend in the five components of the global carbon budget are consistently estimated over the period of 1959-2017, but discrepancies of up to 1 GtC yr(-1) persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations show (1) no consensus in the mean and trend in land -use change emissions, (2) a persistent low agreement among the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models, originating outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding the global carbon cycle compared with previous publications of this data set (Le Quere et al., 2018, 2016, 2015a, b, 2014, 2013). All results presented here can be downloaded from
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- 2018
28. Contrasting interannual atmospheric CO2 variabilities and their terrestrial mechanisms for two types of El Niños
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Wang, J., Zeng, N., Wang, M., Jiang, F., Chen, J., Friedlingstein, P., Jain, A., Jiang, Z., Ju, W., Lienert, S., Nabel, J., https://orcid.org/0000-0002-8122-5206, Sitch, S., Viovy, N., Wang, H., Wiltshire, A., Nanjing University (NJU), Institute of Atmospheric Physics [Beijing] (IAP), Chinese Academy of Sciences [Beijing] (CAS), Nanjing University of Information Science and Technology (NUIST), College of Engineering, Mathematics and Physical Sciences [Exeter] (EMPS), University of Exeter, University of Illinois at Urbana-Champaign [Urbana], University of Illinois System, University of Bern, Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, College of Life and Environmental Sciences [Exeter], Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
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[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere ,530 Physics ,[SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology - Abstract
El Niño has two different flavors, eastern Pacific (EP) and central Pacific (CP) El Niños, with different global teleconnections. However, their different impacts on the interannual carbon cycle variability remain unclear. Here we compared the behaviors of interannual atmospheric CO2 variability and analyzed their terrestrial mechanisms during these two types of El Niños, based on the Mauna Loa (MLO) CO2 growth rate (CGR) and the Dynamic Global Vegetation Model's (DGVM) historical simulations. The composite analysis showed that evolution of the MLO CGR anomaly during EP and CP El Niños had three clear differences: (1) negative or neutral precursors in the boreal spring during an El Niño developing year (denoted as "yr0"), (2) strong or weak amplitudes, and (3) durations of the peak from December (yr0) to April during an El Niño decaying year (denoted as "yr1") compared to October (yr0) to January (yr1) for a CP El Niño, respectively. The global land–atmosphere carbon flux (FTA) simulated by multi-models was able to capture the essentials of these characteristics. We further found that the gross primary productivity (GPP) over the tropics and the extratropical Southern Hemisphere (Trop + SH) generally dominated the global FTA variations during both El Niño types. Regional analysis showed that during EP El Niño events significant anomalous carbon uptake caused by increased precipitation and colder temperatures, corresponding to the negative precursor, occurred between 30° S and 20° N from January (yr0) to June (yr0). The strongest anomalous carbon releases, largely due to the reduced GPP induced by low precipitation and warm temperatures, occurred between the equator and 20° N from February (yr1) to August (yr1). In contrast, during CP El Niño events, clear carbon releases existed between 10° N and 20° S from September (yr0) to September (yr1), resulting from the widespread dry and warm climate conditions. Different spatial patterns of land temperatures and precipitation in different seasons associated with EP and CP El Niños accounted for the evolutionary characteristics of GPP, terrestrial ecosystem respiration (TER), and the resultant FTA. Understanding these different behaviors of interannual atmospheric CO2 variability, along with their terrestrial mechanisms during EP and CP El Niños, is important because the CP El Niño occurrence rate might increase under global warming.
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- 2018
29. Reconciling global-model estimates and country reporting of anthropogenic forest CO 2 sinks
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Grassi, G., House, J., Kurz, W.A., Cescatti, A., Houghton, R.A., Peters, G.P., Sanz, M.J., Viñas, R.A., Alkama, R., Arneth, A., Bondeau, A., Dentener, F., Fader, M., Federici, S., Friedlingstein, P., Jain, A.K., Kato, E., Koven, C.D., Lee, D., Nabel, J.E.M.S., Nassikas, A.A., Perugini, L., Rossi, S., Sitch, S., Viovy, N., Wiltshire, A., Zaehle, S., Grassi, G., House, J., Kurz, W.A., Cescatti, A., Houghton, R.A., Peters, G.P., Sanz, M.J., Viñas, R.A., Alkama, R., Arneth, A., Bondeau, A., Dentener, F., Fader, M., Federici, S., Friedlingstein, P., Jain, A.K., Kato, E., Koven, C.D., Lee, D., Nabel, J.E.M.S., Nassikas, A.A., Perugini, L., Rossi, S., Sitch, S., Viovy, N., Wiltshire, A., and Zaehle, S.
- Abstract
Achieving the long-term temperature goal of the Paris Agreement requires forest-based mitigation. Collective progress towards this goal will be assessed by the Paris Agreement s Global stocktake. At present, there is a discrepancy of about 4 GtCO 2 yr -1 in global anthropogenic net land-use emissions between global models (reflected in IPCC assessment reports) and aggregated national GHG inventories (under the UNFCCC). We show that a substantial part of this discrepancy (about 3.2 GtCO 2 yr -1 ) can be explained by conceptual differences in anthropogenic forest sink estimation, related to the representation of environmental change impacts and the areas considered as managed. For a more credible tracking of collective progress under the Global stocktake, these conceptual differences between models and inventories need to be reconciled. We implement a new method of disaggregation of global land model results that allows greater comparability with GHG inventories. This provides a deeper understanding of model inventory differences, allowing more transparent analysis of forest-based mitigation and facilitating a more accurate Global stocktake. (c) 2018, The Author(s), under exclusive licence to Springer Nature Limited.
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- 2018
30. Asymmetric responses of primary productivity to altered precipitation simulated by ecosystem models across three long-term grassland sites
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Wu, Donghai, Ciais, Philippe, Viovy, N., Knapp, Alan K., Wilcox, Kevin, Bahn, Michael, Smith, Melinda, Vicca, Sara, Fatichi, Simone, Zscheischler, Jakob, He, Yue, Harper, Anna, Sitch, Stephen, Meir, Patrick, Wu, Donghai, Ciais, Philippe, Viovy, N., Knapp, Alan K., Wilcox, Kevin, Bahn, Michael, Smith, Melinda, Vicca, Sara, Fatichi, Simone, Zscheischler, Jakob, He, Yue, Harper, Anna, Sitch, Stephen, and Meir, Patrick
- Abstract
Field measurements of aboveground net primary productivity (ANPP) in temperate grasslands suggest that both positive and negative asymmetric responses to changes in precipitation (P) may occur. Under normal range of precipitation variability, wet years typically result in ANPP gains being larger than ANPP declines in dry years (positive asymmetry), whereas increases in ANPP are lower in magnitude in extreme wet years compared to reductions during extreme drought (negative asymmetry). Whether the current generation of ecosystem models with a coupled carbon–water system in grasslands are capable of simulating these asymmetric ANPP responses is an unresolved question. In this study, we evaluated the simulated responses of temperate grassland primary productivity to scenarios of altered precipitation with 14 ecosystem models at three sites: Shortgrass steppe (SGS), Konza Prairie (KNZ) and Stubai Valley meadow (STU), spanning a rainfall gradient from dry to moist. We found that (1) the spatial slopes derived from modeled primary productivity and precipitation across sites were steeper than the temporal slopes obtained from inter-annual variations, which was consistent with empirical data; (2) the asymmetry of the responses of modeled primary productivity under normal inter-annual precipitation variability differed among models, and the mean of the model ensemble suggested a negative asymmetry across the three sites, which was contrary to empirical evidence based on filed observations; (3) the mean sensitivity of modeled productivity to rainfall suggested greater negative response with reduced precipitation than positive response to an increased precipitation under extreme conditions at the three sites; and (4) gross primary productivity (GPP), net primary productivity (NPP), aboveground NPP (ANPP) and belowground NPP (BNPP) all showed concave-down nonlinear responses to altered precipitation in all the models, but with different curvatures and mean values. Our results in
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- 2018
31. The global carbon budget 1959--2011
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Le Quéré, C., Andres, R. J., Boden, T., Conway, T., Houghton, R. A., House, J. I., Marland, G., Peters, G. P., van der Werf, G., Ahlström, A., Andrew, R. M., Bopp, L., Canadell, J. G., Ciais, P., Doney, S. C., Enright, C., Friedlingstein, P., Huntingford, C., Jain, A. K., Jourdain, C., Kato, E., Keeling, R. F., Klein Goldewijk, K., Levis, S., Levy, P., Lomas, M., Poulter, B., Raupach, M. R., Schwinger, J., Sitch, S., Stocker, B. D., Viovy, N., Zaehle, S., and Zeng, N.
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010504 meteorology & atmospheric sciences ,530 Physics ,13. Climate action ,11. Sustainability ,15. Life on land ,010501 environmental sciences ,7. Clean energy ,01 natural sciences ,0105 earth and related environmental sciences - Abstract
Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the climate policy process, and project future climate change. Present-day analysis requires the combination of a range of data, algorithms, statistics and model estimates and their interpretation by a broad scientific community. Here we describe datasets and a methodology developed by the global carbon cycle science community to quantify all major components of the global carbon budget, including their uncertainties. We discuss changes compared to previous estimates, consistency within and among components, and methodology and data limitations. Based on energy statistics, we estimate that the global emissions of CO2 from fossil fuel combustion and cement production were 9.5 ± 0.5 PgC yr−1 in 2011, 3.0 percent above 2010 levels. We project these emissions will increase by 2.6% (1.9–3.5%) in 2012 based on projections of Gross World Product and recent changes in the carbon intensity of the economy. Global net CO2 emissions from Land-Use Change, including deforestation, are more difficult to update annually because of data availability, but combined evidence from land cover change data, fire activity in regions undergoing deforestation and models suggests those net emissions were 0.9 ± 0.5 PgC yr−1 in 2011. The global atmospheric CO2 concentration is measured directly and reached 391.38 ± 0.13 ppm at the end of year 2011, increasing 1.70 ± 0.09 ppm yr−1 or 3.6 ± 0.2 PgC yr−1 in 2011. Estimates from four ocean models suggest that the ocean CO2 sink was 2.6 ± 0.5 PgC yr−1 in 2011, implying a global residual terrestrial CO2 sink of 4.1 ± 0.9 PgC yr−1. All uncertainties are reported as ±1 sigma (68% confidence assuming Gaussian error distributions that the real value lies within the given interval), reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. This paper is intended to provide a baseline to keep track of annual carbon budgets in the future. All carbon data presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_V2012).
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- 2013
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32. Land-use and land-cover change carbon emissions between 1901 and 2012 constrained by biomass observations
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Li, W, Ciais, P, Peng, S, Yue, C, Wang, Y, Thurner, M, Saatchi, SS, Arneth, A, Avitabile, V, Carvalhais, N, Harper, AB, Kato, E, Koven, C, Liu, YY, Nabel, JEMS, Pan, Y, Pongratz, J, Poulter, B, Pugh, TAM, Santoro, M, Sitch, S, Stocker, BD, Viovy, N, Wiltshire, A, Yousefpour, R, Zaehle, S, Li, W, Ciais, P, Peng, S, Yue, C, Wang, Y, Thurner, M, Saatchi, SS, Arneth, A, Avitabile, V, Carvalhais, N, Harper, AB, Kato, E, Koven, C, Liu, YY, Nabel, JEMS, Pan, Y, Pongratz, J, Poulter, B, Pugh, TAM, Santoro, M, Sitch, S, Stocker, BD, Viovy, N, Wiltshire, A, Yousefpour, R, and Zaehle, S
- Abstract
The use of dynamic global vegetation models (DGVMs) to estimate CO2 emissions from land-use and land-cover change (LULCC) offers a new window to account for spatial and temporal details of emissions and for ecosystem processes affected by LULCC. One drawback of LULCC emissions from DGVMs, however, is lack of observation constraint. Here, we propose a new method of using satellite- and inventory-based biomass observations to constrain historical cumulative LULCC emissions (ELUCc) from an ensemble of nine DGVMs based on emerging relationships between simulated vegetation biomass and ELUCc. This method is applicable on the global and regional scale. The original DGVM estimates of ELUCc range from 94 to 273PgC during 1901-2012. After constraining by current biomass observations, we derive a best estimate of 155±50PgC (1σ Gaussian error). The constrained LULCC emissions are higher than prior DGVM values in tropical regions but significantly lower in North America. Our emergent constraint approach independently verifies the median model estimate by biomass observations, giving support to the use of this estimate in carbon budget assessments. The uncertainty in the constrained ELUCc is still relatively large because of the uncertainty in the biomass observations, and thus reduced uncertainty in addition to increased accuracy in biomass observations in the future will help improve the constraint. This constraint method can also be applied to evaluate the impact of land-based mitigation activities.
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- 2017
33. Variability and quasi-decadal changes in the methane budget over the period 2000–2012
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Saunois, M., Bousquet, P., Poulter, B., Peregon, A., Ciais, P., Canadell, J. G., Dlugokencky, E. J., Etiope, G., Bastviken, D., Houweling, S., Janssens-Maenhout, G., Tubiello, F. N., Castaldi, S., Jackson, R. B., Alexe, M., Arora, V. K., Beerling, D. J., Bergamaschi, P., Blake, D. R., Brailsford, G., Bruhwiler, L., Crevoisier, C., Crill, Patrick, Covey, K., Frankenberg, C., Gedney, N., Höglund-Isaksson, L., Ishizawa, M., Ito, A., Joos, F., Kim, H. -S, Kleinen, T., Krummel, P., Lamarque, J. -F, Langenfelds, R., Locatelli, R., Machida, T., Maksyutov, S., Melton, J. R., Morino, I., Naik, V., O'Doherty, S., Parmentier, F. -JW., Patra, P. K., Peng, C., Peng, S., Peters, G. P., Pison, I., Prinn, R., Ramonet, M., Riley, W. J., Saito, M., Santini, M., Schroeder, R., Simpson, I. J., Spahni, R., Takizawa, A., Thornton, Brett F., Tian, H., Tohjima, Y., Viovy, N., Voulgarakis, A., Weiss, R., Wilton, D. J., Wiltshire, A., Worthy, D., Wunch, D., Xu, X., Yoshida, Y., Zhang, B., Zhang, Z., Zhu, Q., Saunois, M., Bousquet, P., Poulter, B., Peregon, A., Ciais, P., Canadell, J. G., Dlugokencky, E. J., Etiope, G., Bastviken, D., Houweling, S., Janssens-Maenhout, G., Tubiello, F. N., Castaldi, S., Jackson, R. B., Alexe, M., Arora, V. K., Beerling, D. J., Bergamaschi, P., Blake, D. R., Brailsford, G., Bruhwiler, L., Crevoisier, C., Crill, Patrick, Covey, K., Frankenberg, C., Gedney, N., Höglund-Isaksson, L., Ishizawa, M., Ito, A., Joos, F., Kim, H. -S, Kleinen, T., Krummel, P., Lamarque, J. -F, Langenfelds, R., Locatelli, R., Machida, T., Maksyutov, S., Melton, J. R., Morino, I., Naik, V., O'Doherty, S., Parmentier, F. -JW., Patra, P. K., Peng, C., Peng, S., Peters, G. P., Pison, I., Prinn, R., Ramonet, M., Riley, W. J., Saito, M., Santini, M., Schroeder, R., Simpson, I. J., Spahni, R., Takizawa, A., Thornton, Brett F., Tian, H., Tohjima, Y., Viovy, N., Voulgarakis, A., Weiss, R., Wilton, D. J., Wiltshire, A., Worthy, D., Wunch, D., Xu, X., Yoshida, Y., Zhang, B., Zhang, Z., and Zhu, Q.
- Abstract
Following the recent Global Carbon Project (GCP) synthesis of the decadal methane (CH4) budget over 2000–2012 (Saunois et al., 2016), we analyse here the same dataset with a focus on quasi-decadal and inter-annual variability in CH4 emissions. The GCP dataset integrates results from top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models (including process-based models for estimating land surface emissions and atmospheric chemistry), inventories of anthropogenic emissions, and data-driven approaches. The annual global methane emissions from top-down studies, which by construction match the observed methane growth rate within their uncertainties, all show an increase in total methane emissions over the period 2000–2012, but this increase is not linear over the 13 years. Despite differences between individual studies, the mean emission anomaly of the top-down ensemble shows no significant trend in total methane emissions over the period 2000–2006, during the plateau of atmospheric methane mole fractions, and also over the period 2008–2012, during the renewed atmospheric methane increase. However, the top-down ensemble mean produces an emission shift between 2006 and 2008, leading to 22 [16–32] Tg CH4 yr−1 higher methane emissions over the period 2008–2012 compared to 2002–2006. This emission increase mostly originated from the tropics, with a smaller contribution from mid-latitudes and no significant change from boreal regions. The regional contributions remain uncertain in top-down studies. Tropical South America and South and East Asia seem to contribute the most to the emission increase in the tropics. However, these two regions have only limited atmospheric measurements and remain therefore poorly constrained. The sectorial partitioning of this emission increase between the periods 2002–2006 and 2008–2012 differs from one atmospheric inversion study to another. However, all top-down studies sugg
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- 2017
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34. Effect of climate change, CO2 trends, nitrogen addition, and land-cover and management intensity changes on the carbon balance of European grasslands
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Chang, J. F., Ciais, P., Viovy, N., Vuichard, N., Herrero, M., Havlik, P., Wang, X. H., Sultan, Benjamin, and Soussana, J. F.
- Subjects
carbon balance ,climate change ,management intensity ,land-cover change ,European grassland ,ORCHIDEE-GM - Abstract
Several lines of evidence point to European managed grassland ecosystems being a sink of carbon. In this study, we apply ORCHIDEE-GM a process-based carbon cycle model that describes specific management practices of pastures and the dynamics of carbon cycling in response to changes in climatic and biogeochemical drivers. The model is used to simulate changes in the carbon balance [i.e., net biome production (NBP)] of European grasslands over 1991-2010 on a 25kmx25km grid. The modeled average trend in NBP is 1.8-2.0g Cm(-2)yr(-2) during the past two decades. Attribution of this trend suggests management intensity as the dominant driver explaining NBP trends in the model (36-43% of the trend due to all drivers). A major change in grassland management intensity has occurred across Europe resulting from reduced livestock numbers. This change has inadvertently' enhanced soil C sequestration and reduced N2O and CH4 emissions by 1.2-1.5 Gt CO2-equivalent, offsetting more than 7% of greenhouse gas emissions in the whole European agricultural sector during the period 1991-2010. Land-cover change, climate change and rising CO2 also make positive and moderate contributions to the NBP trend (between 24% and 31% of the trend due to all drivers). Changes in nitrogen addition (including fertilization and atmospheric deposition) are found to have only marginal net effect on NBP trends. However, this may not reflect reality because our model has only a very simple parameterization of nitrogen effects on photosynthesis. The sum of NBP trends from each driver is larger than the trend obtained when all drivers are varied together, leaving a residual - nonattributed - term (22-26% of the trend due to all drivers) indicating negative interactions between drivers.
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- 2016
35. Global carbon budget 2016
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Le Quéré, C., Andrew, R.M., Canadell, J.G., Sitch, S., Korsbakken, J.I., Peters, G.P., Manning, A.C., Boden, T.A., Tans, P.P., Houghton, R.A., Keeling, R.F., Alin, S., Andrews, O.D., Anthoni, P., Barbero, L., Bopp, L., Chevallier, F., Chini, L.P., Ciais, P., Currie, K., Delire, C., Doney, S.C., Friedlingstein, P., Gkritzalis, T., Harris, I., Hauck, J., Haverd, V., Hoppema, M., Goldewijk, K.K., Jain, A.K., Kato, E., Körtzinger, A., Landschützer, P., Lefèvre, N., Lenton, A., Lienert, S., Lombardozzi, D., Melton, J.R., Metzl, N., Millero, F., Monteiro, P.M.S., Munro, D.R., Nabel, J.E.M.S., Nakaoka, S., O'Brien, K., Olsen, A., Omar, A.M., Ono, T., Pierrot, D., Poulter, B., Rödenbeck, C., Salisbury, J., Schuster, U., Schwinger, J., Séférian, R., Skjelvan, I., Stocker, B.D., Sutton, A.J., Takahashi, T., Tian, H., Tilbrook, B., van der Laan-Luijkx, I.T., van der Werf, G.R., Viovy, N., Walker, A.P., 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 all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates and consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models. We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2006–2015), EFF was 9.3 ± 0.5 GtC yr−1, ELUC 1.0 ± 0.5 GtC yr−1, GATM 4.5 ± 0.1 GtC yr−1, SOCEAN 2.6 ± 0.5 GtC yr−1, and SLAND 3.1 ± 0.9 GtC yr−1. For year 2015 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1, showing a slowdown in growth of these emissions compared to the average growth of 1.8 % yr−1 that took place during 2006–2015. Also, for 2015, ELUC was 1.3 ± 0.5 GtC yr−1, GATM was 6.3 ± 0.2 GtC yr−1, SOCEAN was 3.0 ± 0.5 GtC yr−1, and SLAND was 1.9 ± 0.9 GtC yr−1. GATM was higher in 2015 compared to the past decade (2006–2015), reflecting a smaller SLAND for that year. The global atmospheric CO2 concentration reached 399.4 ± 0.1 ppm averaged over 2015. For 2016, preliminary data indicate the continuation of low growth in EFF with +0.2 % (range of −1.0 to +1.8 %) based on national emissions projections for China and USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. In spite of the low growth of EFF in 2016, the growth rate in atmospheric CO2 concentration is expected to be relatively high because of the persistence of the smaller residual terrestrial sink (SLAND) in response to El Niño conditions of 2015–2016. From this projection of EFF and assumed constant ELUC for 2016, cumulative emissions of CO2 will reach 565 ± 55 GtC (2075 ± 205 GtCO2) for 1870–2016, about 75 % from EFF and 25 % from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quéré et al., 2015b, a, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2016).
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- 2016
36. Global carbon budget 2014
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Le Quéré, C., Moriarty, R., Andrew, R. M., Peters, G. P., Ciais, P., Friedlingstein, P., Jones, S. D., Sitch, S., Tans, P., Arneth, A., Boden, T. A., Bopp, L., Bozec, Y., Canadell, J. G., Chevallier, F., Cosca, C. E., Harris, I., Hoppema, M., Houghton, R. A., House, J. I., Jain, A., Johannessen, T., Kato, E., Keeling, R. F., Kitidis, V., Klein Goldewijk, K., Koven, C., Landa, C. S., Landschützer, P., Lenton, A., Lima, I. D., Marland, G., Mathis, J. T., Metzl, N., Nojiri, Y., Olsen, A., Ono, T., Peters, W., Pfeil, B., Poulter, B., Raupach, M. R., Regnier, P., Rödenbeck, C., Saito, S., Salisbury, J. E., Schuster, U., Schwinger, J., Séférian, R., Segschneider, J., Steinhoff, T., Stocker, B. D., Sutton, A. J., Takahashi, T., Tilbrook, B., van der Werf, G. R., Viovy, N., Wang, Y.-P., Wanninkhof, R., Wiltshire, A., Zeng, N., Environmental Sciences, LS Economische Geschiedenis, and Leerstoel Aarts
- Abstract
Accurate assessment of anthropogenic carbon dioxide (CO2)emissions and their redistribution among the atmosphere, ocean, andterrestrial biosphere is important to better understand the globalcarbon cycle, support the development of climate policies, and projectfuture climate change. Here we describe datasets and a methodology toquantify all major components of the global carbon budget, includingtheir uncertainties, based on the combination of a range of data,algorithms, statistics and model estimates and their interpretation by abroad scientific community. We discuss changes compared to previousestimates, consistency within and among components, alongsidemethodology and data limitations. CO2 emissions from fossilfuel combustion and cement production (EFF) are based onenergy statistics and cement production data, respectively, whileemissions from Land-Use Change (ELUC), mainly deforestation,are based on combined evidence from land-cover change data, fireactivity associated with deforestation, and models. The globalatmospheric CO2 concentration is measured directly and itsrate of growth (GATM) is computed from the annual changes inconcentration. The mean ocean CO2 sink (SOCEAN) isbased on observations from the 1990s, while the annual anomalies andtrends are estimated with ocean models. The variability inSOCEAN is evaluated with data products based on surveys ofocean CO2 measurements. The global residual terrestrialCO2 sink (SLAND) is estimated by the difference ofthe other terms of the global carbon budget and compared to results ofindependent Dynamic Global Vegetation Models forced by observed climate,CO2 and land cover change (some including nitrogen-carboninteractions). We compare the variability and mean land and ocean fluxesto estimates from three atmospheric inverse methods for three broadlatitude bands. All uncertainties are reported as ±1σ,reflecting the current capacity to characterise the annual estimates ofeach component of the global carbon budget. For the last decadeavailable (2004-2013), EFF was 8.9 ± 0.4 GtCyr-1, ELUC 0.9 ± 0.5 GtC yr-1,GATM 4.3 ± 0.1 GtC yr-1, SOCEAN2.6 ± 0.5 GtC yr-1, and SLAND 2.9 ±0.8 GtC yr-1. For year 2013 alone, EFF grew to 9.9± 0.5 GtC yr-1, 2.3% above 2012, contining the growthtrend in these emissions. ELUC was 0.9 ± 0.5 GtCyr-1, GATM was 5.4 ± 0.2 GtCyr-1, SOCEAN was 2.9 ± 0.5 GtCyr-1 and SLAND was 2.5 ± 0.9 GtCyr-1. GATM was high in 2013 reflecting a steadyincrease in EFF and smaller and opposite changes betweenSOCEAN and SLAND compared to the past decade(2004-2013). The global atmospheric CO2 concentration reached395.31 ± 0.10 ppm averaged over 2013. We estimate thatEFF will increase by 2.5% (1.3-3.5%) to 10.1 ± 0.6 GtCin 2014 (37.0 ± 2.2 GtCO2 yr-1), 65% aboveemissions in 1990, based on projections of World Gross Domestic Productand recent changes in the carbon intensity of the economy. From thisprojection of EFF and assumed constant ELUC for2014, cumulative emissions of CO2 will reach about 545± 55 GtC (2000 ± 200 GtCO2) for 1870-2014,about 75% from EFF and 25% from ELUC. This paperdocuments changes in the methods and datasets used in this new carbonbudget compared with previous publications of this living dataset (LeQuéré et al., 2013, 2014). All observations presented herecan be downloaded from the Carbon Dioxide Information Analysis Center(doi:10.3334/CDIAC/GCP_2014). Italic font highlights significant methodological changesand results compared to the Le Quéré et al. (2015)manuscript that accompanies the previous version of this living data.
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- 2015
37. Global carbon budget 2014
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Canadell, J. G., Tilbrook, B., Raupach, M. R., House, J. I., Salisbury, J. E., Keeling, R. F., Steinhoff, T., Moriarty, R., Wanninkhof, R., Lenton, A., Andrew, R. M., Poulter, B., Koven, C., Schuster, U., Peters, G. P., Landa, C. S., Arneth, A., Bopp, L., Johannessen, T., Bozec, Y., Wang, Y.-P., Cosca, C. E., Ciais, P., Mathis, J. T., Tans, P., Viovy, N., Harris, I., Landschützer, P., Lima, I. D., Takahashi, T., Friedlingstein, P., Jain, A. K., Metzl, N., Regnier, P., Olsen, A., Hoppema, M., Jones, S. D., Le Quéré, C., Chevallier, F., Sitch, S., Klein Goldewijk, K., Marland, G., Boden, T. A., Ono, T., Houghton, R. A., Peters, W., Kato, E., Nojiri, Y., Peng, S., Wiltshire, A., Chini, L. P., Rödenbeck, C., Segschneider, J., Saito, S., Schwinger, J., Sutton, A. J., Zeng, N., Van Der Werf, G. R., Stocker, Benjamin, Séférian, R., Pfeil, B., and Kitidis, V.
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530 Physics - Published
- 2015
- Full Text
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38. The global methane budget 2000–2012
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Saunois, M., Bousquet, P., Poulter, B., Peregon, A., Ciais, P., Canadell, J. G., Dlugokencky, E. J., Etiope, G., Bastviken, D., Houweling, S., Janssens-Maenhout, G., Tubiello, F. N., Castaldi, S., Jackson, R. B., Alexe, M., Arora, V. K., Beerling, D. J., Bergamaschi, P., Blake, D. R., Brailsford, G., Brovkin, V., Bruhwiler, L., Crevoisier, C., Crill, Patrick, Covey, K., Curry, C., Frankenberg, C., Gedney, N., Höglund-Isaksson, L., Ishizawa, M., Ito, A., Joos, F., Kim, H. -S, Kleinen, T., Krummel, P., Lamarque, J. -F, Langenfelds, R., Locatelli, R., Machida, T., Maksyutov, S., McDonald, K. C., Marshall, J., Melton, J. R., Morino, I., Naik, V., O'Doherty, S., Parmentier, F. -JW., Patra, P. K., Peng, C., Peng, S., Peters, G. P., Pison, I., Prigent, C., Prinn, R., Ramonet, M., Riley, W. J., Saito, M., Santini, M., Schroeder, R., Simpson, I. J., Spahni, R., Steele, P., Takizawa, A., Thornton, Brett F., Tian, H., Tohjima, Y., Viovy, N., Voulgarakis, A., van Weele, M., van der Werf, G. R., Weiss, R., Wiedinmyer, C., Wilton, D. J., Wiltshire, A., Worthy, D., Wunch, D., Xu, X., Yoshida, Y., Zhang, B., Zhang, Z., Zhu, Q., Saunois, M., Bousquet, P., Poulter, B., Peregon, A., Ciais, P., Canadell, J. G., Dlugokencky, E. J., Etiope, G., Bastviken, D., Houweling, S., Janssens-Maenhout, G., Tubiello, F. N., Castaldi, S., Jackson, R. B., Alexe, M., Arora, V. K., Beerling, D. J., Bergamaschi, P., Blake, D. R., Brailsford, G., Brovkin, V., Bruhwiler, L., Crevoisier, C., Crill, Patrick, Covey, K., Curry, C., Frankenberg, C., Gedney, N., Höglund-Isaksson, L., Ishizawa, M., Ito, A., Joos, F., Kim, H. -S, Kleinen, T., Krummel, P., Lamarque, J. -F, Langenfelds, R., Locatelli, R., Machida, T., Maksyutov, S., McDonald, K. C., Marshall, J., Melton, J. R., Morino, I., Naik, V., O'Doherty, S., Parmentier, F. -JW., Patra, P. K., Peng, C., Peng, S., Peters, G. P., Pison, I., Prigent, C., Prinn, R., Ramonet, M., Riley, W. J., Saito, M., Santini, M., Schroeder, R., Simpson, I. J., Spahni, R., Steele, P., Takizawa, A., Thornton, Brett F., Tian, H., Tohjima, Y., Viovy, N., Voulgarakis, A., van Weele, M., van der Werf, G. R., Weiss, R., Wiedinmyer, C., Wilton, D. J., Wiltshire, A., Worthy, D., Wunch, D., Xu, X., Yoshida, Y., Zhang, B., Zhang, Z., and Zhu, Q.
- Abstract
The global methane (CH4) budget is becoming an increasingly important component for managing realistic pathways to mitigate climate change. This relevance, due to a shorter atmospheric lifetime and a stronger warming potential than carbon dioxide, is challenged by the still unexplained changes of atmospheric CH4 over the past decade. Emissions and concentrations of CH4 are continuing to increase, making CH4 the second most important human-induced greenhouse gas after carbon dioxide. Two major difficulties in reducing uncertainties come from the large variety of diffusive CH4 sources that overlap geographically, and from the destruction of CH4 by the very short-lived hydroxyl radical (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate research on the methane cycle, and producing regular (∼ biennial) updates of the global methane budget. This consortium includes atmospheric physicists and chemists, biogeochemists of surface and marine emissions, and socio-economists who study anthropogenic emissions. Following Kirschke et al. (2013), we propose here the first version of a living review paper that integrates results of top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models, inventories and data-driven approaches (including process-based models for estimating land surface emissions and atmospheric chemistry, and inventories for anthropogenic emissions, data-driven extrapolations). For the 2003–2012 decade, global methane emissions are estimated by top-down inversions at 558 Tg CH4 yr−1, range 540–568. About 60 % of global emissions are anthropogenic (range 50–65 %). Since 2010, the bottom-up global emission inventories have been closer to methane emissions in the most carbon-intensive Representative Concentrations Pathway (RCP8.5) and higher than all other RCP scenarios. Bott
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- 2016
- Full Text
- View/download PDF
39. Global Carbon Budget 2016
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Environmental Sciences, Le Quéré, C., Andrew, R. M., Canadell, J. G., Sitch, S., Korsbakken, J. I., Peters, G. P., Manning, A. C., Boden, T. A., Tans, P. P., Houghton, R. A., Keeling, R. F., Alin, S., Andrews, O. D., Anthoni, P., Barbero, L., Bopp, L., Chevallier, F., Chini, L. P., Ciais, P., Currie, K., Delire, C., Doney, S. C., Friedlingstein, P., Gkritzalis, T., Harris, I., Hauck, J., Haverd, V., Hoppema, M., Klein Goldewijk, K., Jain, A. K., Kato, E., Körtzinger, A., Landschützer, P., Lefèvre, N., Lenton, A., Lienert, S., Lombardozzi, D., Melton, J. R., Metzl, N., Millero, F., Monteiro, P. M. S., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S.-I., O'Brien, K., Olsen, A., Omar, A. M., Ono, T., Pierrot, D., Poulter, B., Rödenbeck, C., Salisbury, J., Schuster, U., Schwinger, J., Séférian, R., Skjelvan, I., Stocker, B. D., Sutton, A. J., Takahashi, T., Tian, H., Tilbrook, B., van der Laan-Luijkx, I. T., van der Werf, G. R., Viovy, N., Walker, A. P., Wiltshire, A. J., Zaehle, S., Environmental Sciences, Le Quéré, C., Andrew, R. M., Canadell, J. G., Sitch, S., Korsbakken, J. I., Peters, G. P., Manning, A. C., Boden, T. A., Tans, P. P., Houghton, R. A., Keeling, R. F., Alin, S., Andrews, O. D., Anthoni, P., Barbero, L., Bopp, L., Chevallier, F., Chini, L. P., Ciais, P., Currie, K., Delire, C., Doney, S. C., Friedlingstein, P., Gkritzalis, T., Harris, I., Hauck, J., Haverd, V., Hoppema, M., Klein Goldewijk, K., Jain, A. K., Kato, E., Körtzinger, A., Landschützer, P., Lefèvre, N., Lenton, A., Lienert, S., Lombardozzi, D., Melton, J. R., Metzl, N., Millero, F., Monteiro, P. M. S., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S.-I., O'Brien, K., Olsen, A., Omar, A. M., Ono, T., Pierrot, D., Poulter, B., Rödenbeck, C., Salisbury, J., Schuster, U., Schwinger, J., Séférian, R., Skjelvan, I., Stocker, B. D., Sutton, A. J., Takahashi, T., Tian, H., Tilbrook, B., van der Laan-Luijkx, I. T., van der Werf, G. R., Viovy, N., Walker, A. P., Wiltshire, A. J., and Zaehle, S.
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- 2016
40. Global Carbon Budget 2016
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Le Quéré, Corinne, Andrew, R.M., Canadell, J.G., Sitch, S., Korsbakken, J.I., Peters, G.P., Manning, A.C., Boden, T.A., Tans, P.P., Houghton, R.A., Keeling, R.F., Alin, S., Andrews, O.D., Anthoni, P., Barbero, L., Bopp, L., Chevallier, F., Chini, L.P., Ciais, P., Currie, K., Delire, C., Doney, S.C., Friedlingstein, P., Gkritzalis, T., Harris, I., Hauck, Judith, Haverd, V., Hoppema, Mario, Klein Goldewijk, K., Jain, A.K., Kato, E., Körtzinger, A., Landschützer, P., Lefèvre, N., Lenton, A., Lienert, S., Lombardozzi, D., Melton, J.R., Metzl, N., Millero, F., Monteiro, P.M.S., Munro, D.R., Nabel, J.E.M.S., Nakaoka, S.-i., O'Brien, K., Olsen, A., Omar, A.M., Ono, T., Pierrot, D., Poulter, B., Rödenbeck, C., Salisbury, J., Schuster, U., Schwinger, J., Séférian, R., Skjelvan, I., Stocker, B.D., Sutton, A.J., Takahashi, T., Tian, H., Tilbrook, B., van der Laan-Luijkx, I.T., van der Werf, G.R., Viovy, N., Walker, A.P., Wiltshire, A.J., Zaehle, S., Le Quéré, Corinne, Andrew, R.M., Canadell, J.G., Sitch, S., Korsbakken, J.I., Peters, G.P., Manning, A.C., Boden, T.A., Tans, P.P., Houghton, R.A., Keeling, R.F., Alin, S., Andrews, O.D., Anthoni, P., Barbero, L., Bopp, L., Chevallier, F., Chini, L.P., Ciais, P., Currie, K., Delire, C., Doney, S.C., Friedlingstein, P., Gkritzalis, T., Harris, I., Hauck, Judith, Haverd, V., Hoppema, Mario, Klein Goldewijk, K., Jain, A.K., Kato, E., Körtzinger, A., Landschützer, P., Lefèvre, N., Lenton, A., Lienert, S., Lombardozzi, D., Melton, J.R., Metzl, N., Millero, F., Monteiro, P.M.S., Munro, D.R., Nabel, J.E.M.S., Nakaoka, S.-i., O'Brien, K., Olsen, A., Omar, A.M., Ono, T., Pierrot, D., Poulter, B., Rödenbeck, C., Salisbury, J., Schuster, U., Schwinger, J., Séférian, R., Skjelvan, I., Stocker, B.D., Sutton, A.J., Takahashi, T., Tian, H., Tilbrook, B., van der Laan-Luijkx, I.T., van der Werf, G.R., Viovy, N., Walker, A.P., Wiltshire, A.J., and Zaehle, S.
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- 2016
41. LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soil moisture Model Intercomparison Project – aims, setup and expected outcome
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van den Hurk, B., Kim, H., Krinner, G., Seneviratne, S.I., Derksen, C., Oki, T., Douville, H., Colin, J., Ducharne, A., Cheruy, F., Viovy, N., Puma, M.J., Wada, Y., Li, W., Jia, B., Alessandri, A., Lawrence, D.M., Weedon, G.P., Ellis, Richard, Hagemann, S., Mao, J., Flanner, M.G., Zampieri, M., Materia, S., Law, R.M., Sheffield, J., van den Hurk, B., Kim, H., Krinner, G., Seneviratne, S.I., Derksen, C., Oki, T., Douville, H., Colin, J., Ducharne, A., Cheruy, F., Viovy, N., Puma, M.J., Wada, Y., Li, W., Jia, B., Alessandri, A., Lawrence, D.M., Weedon, G.P., Ellis, Richard, Hagemann, S., Mao, J., Flanner, M.G., Zampieri, M., Materia, S., Law, R.M., and Sheffield, J.
- Abstract
The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). The solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both strongly affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. However, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).
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- 2016
42. Combining livestock production information in a process-based vegetation model to reconstruct the history of grassland management
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Chang, J., Ciais, P., Herrero, M., Havlik, P., Campioli, M., Zhang, X., Bai, Y., Viovy, N., Joiner, J., Wang, X., Peng, S., Yue, C., Piao, Shilong, Wang, Tao, Hauglustaine, D.A., Soussana, J.-F., Peregon, A., Kosykh, N., Mironycheva-Tokareva, N., Chang, J., Ciais, P., Herrero, M., Havlik, P., Campioli, M., Zhang, X., Bai, Y., Viovy, N., Joiner, J., Wang, X., Peng, S., Yue, C., Piao, Shilong, Wang, Tao, Hauglustaine, D.A., Soussana, J.-F., Peregon, A., Kosykh, N., and Mironycheva-Tokareva, N.
- Abstract
Grassland management type (grazed or mown) and intensity (intensive or extensive) play a crucial role in the greenhouse gas balance and surface energy budget of this biome, both at field scale and at large spatial scale. However, global gridded historical information on grassland management intensity is not available. Combining modelled grass-biomass productivity with statistics of the grass-biomass demand by livestock, we reconstruct gridded maps of grassland management intensity from 1901 to 2012. These maps include the minimum area of managed vs. maximum area of unmanaged grasslands and the fraction of mown vs. grazed area at a resolution of 0.5° by 0.5°. The grass-biomass demand is derived from a livestock dataset for 2000, extended to cover the period 1901–2012. The grass-biomass supply (i.e. forage grass from mown grassland and biomass grazed) is simulated by the process-based model ORCHIDEE-GM driven by historical climate change, rising CO2 concentration, and changes in nitrogen fertilization. The global area of managed grassland obtained in this study increases from 6.1 × 106 km2 in 1901 to 12.3 × 106 km2 in 2000, although the expansion pathway varies between different regions. ORCHIDEE-GM also simulated augmentation in global mean productivity and herbage-use efficiency over managed grassland during the 20th century, indicating a general intensification of grassland management at global scale but with regional differences. The gridded grassland management intensity maps are model dependent because they depend on modelled productivity. Thus specific attention was given to the evaluation of modelled productivity against a series of observations from site-level net primary productivity (NPP) measurements to two global satellite products of gross primary productivity (GPP) (MODIS-GPP and SIF data). Generally, ORCHIDEE-GM captures the spatial pattern, seasonal cycle, and interannual variability of grassland productivity at global scale well and thus is appro
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- 2016
43. Effect of climate change, CO2 trends, nitrogen addition, land cover and management intensity change on the carbon balance of European grasslands
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Chang, J., Ciais, P., Viovy, N., Vuichard, N., Havlik, P., Wang, H., Sultan, B., Soussana, J.-F., Chang, J., Ciais, P., Viovy, N., Vuichard, N., Havlik, P., Wang, H., Sultan, B., and Soussana, J.-F.
- Abstract
Several lines of evidence point to European managed grassland ecosystems being a sink of carbon. In this study, we apply ORCHIDEE-GM a process-based carbon cycle model that describes specific management practices of pastures and the dynamics of carbon cycling in response to changes in climatic and biogeochemical drivers. The model is used to simulate changes in the carbon balance (i.e., Net Biome Production, NBP) of European grasslands over 1991-2010 on a 25 km x 25 km grid. The modeled average trend of NBP is 1.8 - 2.0 g C m^-2 yr^-2 during the past two decades. Attribution of this trend suggests management intensity as the dominant driver explaining NBP trends in the model (36% - 43% of the trend due to all drivers). A major change in grassland management intensity has occurred across Europe resulting from reduced livestock numbers. This change has 'inadvertently' enhanced soil C sequestration and reduced N2O and CH4 emissions by 1.2 - 1.5 Gt CO2-equivalent, offsetting more than 7% of greenhoue gas emissions in the whole European agricultural sector during the period 1991-2010. Land-cover change, climate change and rising CO2 also make positive and moderate contributions to the NBP trend (between 24% and 31% of the trend due to all drivers). Change in nitrogen addition (including fertilization and atmospheric deposition) is found to have only marginal net effect on NBP trends. However, this may not reflect reality because our model has only a very simple parameterization of nitrogen-effects on photosynthesis. The sum of NBP trends from each driver is larger than the trend obtained when all drivers are varied together, leaving a residual - nn-attributed - term (22% - 26% of the trend due to all drivers) indicating negative interactions between drivers.
- Published
- 2016
44. Global carbon budget 2013
- Author
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Le Quéré, C., Peters, G. P., Andres, R. J., Andrew, R. M., Boden, T. A., Ciais, P., Friedlingstein, P., Houghton, R. A., Marland, G., Moriarty, R., Sitch, S., Tans, P., Arneth, A., Arvanitis, A., Bakker, D. C E, Bopp, L., Canadell, J. G., Chini, L. P., Doney, S. C., Harper, A., Harris, I., House, J. I., Jain, A. K., Jones, S. D., Kato, E., Keeling, R. F., Klein Goldewijk, Kees, Körtzinger, A., Koven, C., Lefèvre, N., Maignan, F., Omar, A., Ono, T., Park, G. H., Pfeil, B., Poulter, B., Raupach, M. R., Regnier, P., Rödenbeck, C., Saito, S., Schwinger, J., Segschneider, J., Stocker, B. D., Takahashi, T., Tilbrook, B., Van Heuven, S., Viovy, N., Wanninkhof, R., Wiltshire, A., Zaehle, S., and Environmental Sciences
- Subjects
Earth and Planetary Sciences(all) - Abstract
Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates, consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil-fuel combustion and cement production (EFF) are based on energy statistics, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (G ATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated for the first time in this budget with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2 and land cover change (some including nitrogen-carbon interactions). All uncertainties are reported as ±1σ , reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2003-2012), EFF was 8.6±0.4 GtC yr-1, ELUC 0.9±0.5 GtC yr-1, GATM 4.3±0.1 GtC yr-1, SOCEAN 2.5±0.5 GtC yr -1, and SLAND 2.8±0.8 GtC yr-1. For year 2012 alone, EFF grew to 9.7±0.5 GtC yr-1, 2.2% above 2011, reflecting a continued growing trend in these emissions, G ATM was 5.1±0.2 GtC yr-1, SOCEAN was 2.9±0.5 GtC yr-1, and assuming an ELUC of 1.0±0.5 GtC yr-1 (based on the 2001-2010 average), S LAND was 2.7±0.9 GtC yr-1. GATM was high in 2012 compared to the 2003-2012 average, almost entirely reflecting the high EFF. The global atmospheric CO2 concentration reached 392.52±0.10 ppm averaged over 2012. We estimate that EFF will increase by 2.1% (1.1- 3.1 %) to 9.9±0.5 GtC in 2013, 61% above emissions in 1990, based on projections of world gross domestic product and recent changes in the carbon intensity of the economy.With this projection, cumulative emissions ofCO2 will reach about 535±55 GtC for 1870-2013, about 70% from EFF (390±20 GtC) and 30% from ELUC (145±50 GtC). This paper also documents any changes in the methods and data sets used in this new carbon budget from previous budgets (Le Quéré et al., 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP-2013-V2.3).
- Published
- 2014
45. Global carbon budget 2013
- Author
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Omar, A., Tans, P., Kato, E., Tilbrook, B., Jones, S. D., House, J. I., Boden, T. A., Peters, G. P., Pfeil, B., Stocker, B. D., Harris, I., Wiltshire, A., Raupach, M. R., Canadell, J. G., Schwinger, J., Arneth, A., Poulter, B., Ono, T., Lefèvre, N., Körtzinger, A., Park, G.-H., Saito, S., Le Quéré, C., Maignan, F., Keeling, R. F., Harper, A., Andrew, R. M., Wanninkhof, R., Bakker, D. C. E., Regnier, P., Doney, S. C., Ciais, P., Houghton, R. A., Van Heuven, S., Bopp, L., Zaehle, S., Viovy, N., Arvanitis, A., Jain, A. K., Marland, G., Chini, L. P., Sitch, S., Moriarty, R., Friedlingstein, P., Andres, R. J., Klein Goldewijk, K., Rödenbeck, C., Koven, C., Takahashi, T., and Segschneider, J.
- Subjects
530 Physics - Abstract
Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates, consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil-fuel combustion and cement production (EFF) are based on energy statistics, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (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 for the first time in this budget with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2 and land cover change (some including nitrogen–carbon interactions). All uncertainties are reported as ± 1 σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2003–2012), EFF was 8.6 ± 0.4 GtC yr − 1, ELUC 0.9 ± 0.5 GtC yr − 1, GATM 4.3 ± 0.1 GtC yr − 1, S OCEAN 2.5 ± 0.5 GtC yr − 1, and S LAND 2.8 ± 0.8 GtC yr − 1. For year 2012 alone, EFF grew to 9.7 ± 0.5 GtC yr − 1, 2.2 % above 2011, reflecting a continued growing trend in these emissions, GATM was 5.1 ± 0.2 GtC yr − 1, SOCEANwas 2.9 ± 0.5 GtC yr −1, and assuming an ELU Cof 1.0 ± 0.5 GtC yr − 1 (based on the 2001–2010 average), SLAND was 2.7 ± 0.9 GtC yr − 1. GATM was high in 2012 compared to the 2003–2012 average, almost entirely reflecting the high EFF. The global atmospheric CO2 con- centration reached 392.52 ± 0.10 ppm averaged over 2012. We estimate that EFF will increase by 2.1 % (1.1–3.1 %) to 9.9 ± 0.5 GtC in 2013, 61 % above emissions in 1990, based on projections of world gross domestic product and recent changes in the carbon intensity of the economy. With this projection, cumulative emissions of CO2 will reach about 535 ± 55 GtC for 1870–2013, about 70 % from EFF (390 ± 20 GtC) and 30 % from ELUC (145 ± 50 GtC). This paper also documents any changes in the methods and data sets used in this new carbon budget from previous budgets (Le Quéré et al., 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center.
- Published
- 2014
- Full Text
- View/download PDF
46. Modeling sugar cane yield with a process-based model from site to continental scale: uncertainties arising from model structure and parameter values
- Author
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VALADE, A., CIAIS, P., VUICHARD, N., VIOVY, N., CAUBEL, A., HUTH, N., MARIN, F. R., MARTINÉ, J.-F., LSCE, CEA-CNRS, CSIRO, FABIO RICARDO MARIN, CNPTIA, and Cirad.
- Subjects
Models ,Modelos ,Cana-de-açúcar ,Sugarcane ,Modelagem - Abstract
This study reveals the spatial and temporal patterns of uncertainty variability for a highly parameterized agro-LSM and calls for more systematic uncertainty analyses of such models.
- Published
- 2014
47. ORCHIDEE-CROP (v0), a new process-based agro-land surface model: model description and evaluation over Europe
- Author
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Wu, X., primary, Vuichard, N., additional, Ciais, P., additional, Viovy, N., additional, de Noblet-Ducoudré, N., additional, Wang, X., additional, Magliulo, V., additional, Wattenbach, M., additional, Vitale, L., additional, Di Tommasi, P., additional, Moors, E. J., additional, Jans, W., additional, Elbers, J., additional, Ceschia, E., additional, Tallec, T., additional, Bernhofer, C., additional, Grünwald, T., additional, Moureaux, C., additional, Manise, T., additional, Ligne, A., additional, Cellier, P., additional, Loubet, B., additional, Larmanou, E., additional, and Ripoche, D., additional
- Published
- 2016
- Full Text
- View/download PDF
48. Global Carbon Budget 2015
- Author
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Leerstoel Ridder, Environmental Sciences, Sub Algemeen Math. Inst, Le Quéré, C., Moriarty, R., Andrew, R. M., Canadell, J. G., Sitch, S., Korsbakken, J. I., Friedlingstein, P., Peters, G. P., Andres, R. J., Boden, T. A., Houghton, R. A., House, J. I., Keeling, R. F., Tans, P., Arneth, A., Bakker, D. C. E., Barbero, L., Bopp, L., Chang, J., Chevallier, F., Chini, L. P., Ciais, P., Fader, M., Feely, R. A., Gkritzalis, T., Harris, I., Hauck, J., Ilyina, T., Jain, A. K., Kato, E., Kitidis, V., Klein Goldewijk, K., Koven, C., Landschützer, P., Lauvset, S. K., Lefèvre, N., Lenton, A., Lima, I. D., Metzl, N., Millero, F., Munro, D. R., Murata, A., Nabel, J. E. M. S., Nakaoka, S., Nojiri, Y., O'Brien, K., Olsen, A., Ono, T., Pérez, F. F., Pfeil, B., Pierrot, D., Poulter, B., Rehder, G., Rödenbeck, C., Saito, S., Schuster, U., Schwinger, J., Séférian, R., Steinhoff, T., Stocker, B. D., Sutton, A. J., Takahashi, T., Tilbrook, B., van der Laan-Luijkx, I. T., van der Werf, G. R., van Heuven, S., Vandemark, D., Viovy, N., Wiltshire, A., Zaehle, S., Zeng, N., Leerstoel Ridder, Environmental Sciences, Sub Algemeen Math. Inst, Le Quéré, C., Moriarty, R., Andrew, R. M., Canadell, J. G., Sitch, S., Korsbakken, J. I., Friedlingstein, P., Peters, G. P., Andres, R. J., Boden, T. A., Houghton, R. A., House, J. I., Keeling, R. F., Tans, P., Arneth, A., Bakker, D. C. E., Barbero, L., Bopp, L., Chang, J., Chevallier, F., Chini, L. P., Ciais, P., Fader, M., Feely, R. A., Gkritzalis, T., Harris, I., Hauck, J., Ilyina, T., Jain, A. K., Kato, E., Kitidis, V., Klein Goldewijk, K., Koven, C., Landschützer, P., Lauvset, S. K., Lefèvre, N., Lenton, A., Lima, I. D., Metzl, N., Millero, F., Munro, D. R., Murata, A., Nabel, J. E. M. S., Nakaoka, S., Nojiri, Y., O'Brien, K., Olsen, A., Ono, T., Pérez, F. F., Pfeil, B., Pierrot, D., Poulter, B., Rehder, G., Rödenbeck, C., Saito, S., Schuster, U., Schwinger, J., Séférian, R., Steinhoff, T., Stocker, B. D., Sutton, A. J., Takahashi, T., Tilbrook, B., van der Laan-Luijkx, I. T., van der Werf, G. R., van Heuven, S., Vandemark, D., Viovy, N., Wiltshire, A., Zaehle, S., and Zeng, N.
- Published
- 2015
49. Global carbon budget 2014
- Author
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Environmental Sciences, LS Economische Geschiedenis, Leerstoel Aarts, Le Quéré, C., Moriarty, R., Andrew, R. M., Peters, G. P., Ciais, P., Friedlingstein, P., Jones, S. D., Sitch, S., Tans, P., Arneth, A., Boden, T. A., Bopp, L., Bozec, Y., Canadell, J. G., Chevallier, F., Cosca, C. E., Harris, I., Hoppema, M., Houghton, R. A., House, J. I., Jain, A., Johannessen, T., Kato, E., Keeling, R. F., Kitidis, V., Klein Goldewijk, K., Koven, C., Landa, C. S., Landschützer, P., Lenton, A., Lima, I. D., Marland, G., Mathis, J. T., Metzl, N., Nojiri, Y., Olsen, A., Ono, T., Peters, W., Pfeil, B., Poulter, B., Raupach, M. R., Regnier, P., Rödenbeck, C., Saito, S., Salisbury, J. E., Schuster, U., Schwinger, J., Séférian, R., Segschneider, J., Steinhoff, T., Stocker, B. D., Sutton, A. J., Takahashi, T., Tilbrook, B., van der Werf, G. R., Viovy, N., Wang, Y.-P., Wanninkhof, R., Wiltshire, A., Zeng, N., Environmental Sciences, LS Economische Geschiedenis, Leerstoel Aarts, Le Quéré, C., Moriarty, R., Andrew, R. M., Peters, G. P., Ciais, P., Friedlingstein, P., Jones, S. D., Sitch, S., Tans, P., Arneth, A., Boden, T. A., Bopp, L., Bozec, Y., Canadell, J. G., Chevallier, F., Cosca, C. E., Harris, I., Hoppema, M., Houghton, R. A., House, J. I., Jain, A., Johannessen, T., Kato, E., Keeling, R. F., Kitidis, V., Klein Goldewijk, K., Koven, C., Landa, C. S., Landschützer, P., Lenton, A., Lima, I. D., Marland, G., Mathis, J. T., Metzl, N., Nojiri, Y., Olsen, A., Ono, T., Peters, W., Pfeil, B., Poulter, B., Raupach, M. R., Regnier, P., Rödenbeck, C., Saito, S., Salisbury, J. E., Schuster, U., Schwinger, J., Séférian, R., Segschneider, J., Steinhoff, T., Stocker, B. D., Sutton, A. J., Takahashi, T., Tilbrook, B., van der Werf, G. R., Viovy, N., Wang, Y.-P., Wanninkhof, R., Wiltshire, A., and Zeng, N.
- Published
- 2015
50. Recent trends and drivers of regional sources and sinks of carbon dioxide
- Author
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Sitch, S., Friedlingstein, P., Gruber, N., Jones, S.D., Murray-Tortarolo, G., Ahlström, A., Doney, S.C., Graven, H., Heinze, C., Huntingford, C., Levis, S., Levy, P.E., Lomas, M., Poulter, B., Viovy, N., Zaehle, S., Zeng, N., Arneth, A., Bonan, G., Bopp, L., Canadell, J.G., Chevallier, F., Ciais, P., Ellis, R., Gloor, M., Peylin, P., Piao, S.L., Le Quéré, C., Smith, B., Zhu, Z., Myneni, R., Sitch, S., Friedlingstein, P., Gruber, N., Jones, S.D., Murray-Tortarolo, G., Ahlström, A., Doney, S.C., Graven, H., Heinze, C., Huntingford, C., Levis, S., Levy, P.E., Lomas, M., Poulter, B., Viovy, N., Zaehle, S., Zeng, N., Arneth, A., Bonan, G., Bopp, L., Canadell, J.G., Chevallier, F., Ciais, P., Ellis, R., Gloor, M., Peylin, P., Piao, S.L., Le Quéré, C., Smith, B., Zhu, Z., and Myneni, R.
- Abstract
The land and ocean absorb on average just over half of the anthropogenic emissions of carbon dioxide (CO2) every year. These CO2 "sinks" are modulated by climate change and variability. Here we use a suite of nine dynamic global vegetation models (DGVMs) and four ocean biogeochemical general circulation models (OBGCMs) to estimate trends driven by global and regional climate and atmospheric CO2 in land and oceanic CO2 exchanges with the atmosphere over the period 1990–2009, to attribute these trends to underlying processes in the models, and to quantify the uncertainty and level of inter-model agreement. The models were forced with reconstructed climate fields and observed global atmospheric CO2; land use and land cover changes are not included for the DGVMs. Over the period 1990–2009, the DGVMs simulate a mean global land carbon sink of −2.4 ± 0.7 Pg C yr−1 with a small significant trend of −0.06 ± 0.03 Pg C yr−2 (increasing sink). Over the more limited period 1990–2004, the ocean models simulate a mean ocean sink of −2.2 ± 0.2 Pg C yr−1 with a trend in the net C uptake that is indistinguishable from zero (−0.01 ± 0.02 Pg C yr−2). The two ocean models that extended the simulations until 2009 suggest a slightly stronger, but still small, trend of −0.02 ± 0.01 Pg C yr−2. Trends from land and ocean models compare favourably to the land greenness trends from remote sensing, atmospheric inversion results, and the residual land sink required to close the global carbon budget. Trends in the land sink are driven by increasing net primary production (NPP), whose statistically significant trend of 0.22 ± 0.08 Pg C yr−2 exceeds a significant trend in heterotrophic respiration of 0.16 ± 0.05 Pg C yr−2 – primarily as a consequence of widespread CO2 fertilisation of plant production. Most of the land-based trend in simulated net carbon uptake originates from natural ecosystems in the tropics (−0.04 ± 0.01 Pg C yr−2), with almost no trend over the northern land region, where rece
- Published
- 2015
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