Accurate assessment of anthropogenic carbon dioxide (CO 2 ) 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 CO 2 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 CO 2 concentration is measured directly and its growth rate (G ATM ) is computed from the annual changes in concentration. The ocean CO 2 sink (S OCEAN ) and terrestrial CO 2 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 ±1σ . 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 CO 2 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 CO 2 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 CO 2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO 2 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 c...

[1] The TransCom 3 experiment was begun to explore the estimation of carbon sources and sinks via the inversion of simulated tracer transport. We build upon previous TransCom work by presenting the seasonal inverse results which provide estimates of carbon flux for 11 land and 11 ocean regions using 12 atmospheric transport models. The monthly fluxes represent the mean seasonal cycle for the 1992 to 1996 time period. The spread among the model results is larger than the average of their estimated flux uncertainty in the northern extratropics and vice versa in the tropical regions. In the northern land regions, the model spread is largest during the growing season. Compared to a seasonally balanced biosphere prior flux generated by the CASA model, we find significant changes to the carbon exchange in the European region with greater growing season net uptake which persists into the fall months. Both Boreal North America and Boreal Asia show lessened net uptake at the onset of the growing season with Boreal Asia also exhibiting greater peak growing season net uptake. Temperate Asia shows a dramatic springward shift in the peak timing of growing season net uptake relative to the neutral CASA flux while Temperate North America exhibits a broad flattening of the seasonal cycle. In most of the ocean regions, the inverse fluxes exhibit much greater seasonality than that implied by the DpCO 2 derived fluxes though this may be due, in part, to misallocation of adjacent land flux. In the Southern Ocean, the austral spring and fall exhibits much less carbon uptake than implied by DpCO 2 derived fluxes. Sensitivity testing indicates that the inverse estimates are not overly influenced by the prior flux choices. Considerable agreement exists between the model mean, annual mean results of this study and that of the previously published TransCom annual mean inversion. The differences that do exist are in poorly constrained regions and tend to exhibit compensatory fluxes in order to match the global mass constraint. The differences between the estimated fluxes and the prior model over the northern land regions could be due to the prior model respiration response to temperature. Significant phase differences, such as that in the Temperate Asia region, may be due to the limited observations for that region. Finally, differences in the boreal land regions between the prior model and the estimated fluxes may be a reflection of the timing of spring thaw and an imbalance in respiration versus photosynthesis.

Spatial and temporal variations of atmospheric CO 2 concentrations contain information about surface sources and sinks, which can be quantitatively interpreted through tracer transport inversion. Previous CO 2 inversion calculations obtained differing results due to different data, methods and transport models used. To isolate the sources of uncertainty, we have conducted a set of annual mean inversion experiments in which 17 different transport models or model variants were used to calculate regional carbon sources and sinks from the same data with a standardized method. Simulated transport is a significant source of uncertainty in these calculations, particularly in the response to prescribed "background" fluxes due to fossil fuel combustion, a balanced terrestrial biosphere, and air-sea gas exchange. Individual model-estimated fluxes are often a direct reflection of their response to these background fluxes. Models that generate strong surface maxima near background exchange locations tend to require larger uptake near those locations. Models with weak surface maxima tend to have less uptake in those same regions but may infer small sources downwind. In some cases, individual model flux estimates cannot be analyzed through simple relationships to background flux responses but are

This study presents the global climate model IPSL-CM6A-LR developed at Institut Pierre-Simon Laplace (IPSL) to study natural climate variability and climate response to natural and anthropogenic forcings as part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). This article describes the different model components, their coupling, and the simulated climate in comparison to previous model versions. We focus here on the representation of the physical climate along with the main characteristics of the global carbon cycle. The model's climatology, as assessed from a range of metrics (related in particular to radiation, temperature, precipitation, and wind), is strongly improved in comparison to previous model versions. Although they are reduced, a number of known biases and shortcomings (e.g., double Intertropical Convergence Zone [ITCZ], frequency of midlatitude wintertime blockings, and El Niño-Southern Oscillation [ENSO] dynamics) persist. The equilibrium climate sensitivity and transient climate response have both increased from the previous climate model IPSL-CM5A-LR used in CMIP5. A large ensemble of more than 30 members for the historical period (1850-2018) and a smaller ensemble for a range of emissions scenarios (until 2100 and 2300) are also presented and discussed.Plain Language Summary Climate models are unique tools to investigate the characteristics and behavior of the climate system. While climate models and their components are developed gradually over the years, the sixth phase of the Coupled Model Intercomparison Project (CMIP6) has been the

Global‐scale results of the new O‐CN terrestrial biosphere model coupling the carbon (C) and nitrogen (N) cycles show that the model produces realistic estimates of present‐day C and N stocks and fluxes, despite some regional biases. N availability strongly affects high‐latitude foliage area and foliage N, limiting vegetation productivity and present‐day high‐latitude net C uptake. Anthropogenic N deposition is predicted to have increased net primary productivity due to increases in foliage area and foliage N, contributing 0.2–0.5 Pg C yr−1 to the 1990s global net C uptake. While O‐CN's modeled global 1990s terrestrial net C uptake (2.4 Pg C yr−1) is similar to the estimate not accounting for anthropogenic N inputs and N dynamics (2.6 Pg C yr−1), its latitudinal distribution and the sensitivity of the terrestrial C balance to its driving factors are substantially altered by N dynamics, with important implications for future trajectories of the global carbon cycle.

A recent increase in extreme flooding in Amazonia is linked to intensification of the atmospheric east-west Walker circulation.

Abstract.We developed an iterative inverse method to infer inter-annual sources and sinks of methyl chloroform (MCF) from atmospheric measurements, on a monthly basis. The methodology is presented and used to estimate two decades of OH variability between 1980 and 2000, using varying meteorology. When OH concentrations are adjusted with loose prior errors and MCF emissions are adjusted within inventory bounds, we show that substantial OH inter-annual variability (8.5±1.0% of the mean) and trend (−0.7%.yr −1 ) are necessary to match MCF observations. This result is confirmed by a series of sensitivity tests addressing main limitations of previous studies. However, we show that it is also possible to match MCF observations with a 65% reduction of OH year-to-year variations and a 60% reduction of absolute OH trend, but still a consistency of inferred emissions with inventory values at a ±2σ level. On the other hand, the phase of inferred OH variations is a more robust feature of our set of inversions. Overall, MCF inversions can only provide a range of OH variations unless inventory uncertainties are further reduced.

No abstract