FLUXNET is a global network of micrometeorological flux measurement sites that measure the exchanges of carbon dioxide, water vapor, and energy between the biosphere and atmosphere. At present over 140 sites are operating on a long-term and continuous basis. Vegetation under study includes temperate conifer and broadleaved (deciduous and evergreen) forests, tropical and boreal forests, crops, grasslands, chaparral, wetlands, and tundra. Sites exist on five continents and their latitudinal distribution ranges from 70°N to 30°S. FLUXNET has several primary functions. First, it provides infrastructure for compiling, archiving, and distributing carbon, water, and energy flux measurement, and meteorological, plant, and soil data to the science community. (Data and site information are available online at the FLUXNET Web site, http://www-eosdis.ornl.gov/FLUXNET/.) Second, the project supports calibration and flux intercomparison activities. This activity ensures that data from the regional networks are intercomparable. And third, FLUXNET supports the synthesis, discussion, and communication of ideas and data by supporting project scientists, workshops, and visiting scientists. The overarching goal is to provide information for validating computations of net primary productivity, evaporation, and energy absorption that are being generated by sensors mounted on the NASA Terra satellite. Data being compiled by FLUXNET are being used to quantify and compare magnitudes and dynamics of annual ecosystem carbon and water balances, to quantify the response of stand-scale carbon dioxide and water vapor flux densities to controlling biotic and abiotic factors, and to validate a hierarchy of soil-plant-atmosphere trace gas exchange models. Findings so far include 1) net C0 2 exchange of temperate broadleaved forests increases by about 5.7 g C m~2 day-1 for each additional day that the growing season is extended; 2) the sensitivity of net ecosystem C0 2 exchange to sunlight doubles if the sky is cloudy rather than clear; 3) the spectrum of C0 2 flux density exhibits peaks at timescales of days, weeks, and years, and a spectral gap exists at the month timescale; 4) the optimal temperature of net C0 2 exchange varies with mean summer temperature; and 5) stand age affects carbon dioxide and water vapor flux densities.

Heightened awareness of global change issues within both science and political communities has increased interest in using the global network of eddy covariance flux towers to more fully understand the impacts of natural and anthropogenic phenomena on the global carbon balance. Comparisons of net ecosystem exchange (F NEE ) responses are being made among biome types, phenology patterns, and stress conditions. The comparisons are usually performed on annual sums of F NEE ; however, the average data coverage during a year is only 65%. Therefore, robust and consistent gap filling methods are required.We review several methods of gap filling and apply them to data sets available from the EUROFLUX and AmeriFlux databases. The methods are based on mean diurnal variation (MDV), look-up tables (LookUp), and nonlinear regressions (Regr.), and the impact of different gap filling methods on the annual sum of F NEE is investigated. The difference between annual F NEE filled by MDV compared to F NEE filled by Regr. ranged from −45 to +200 g C m −2 per year (MDV−Regr.). Comparing LookUp and Regr. methods resulted in a difference (LookUp−Regr.) ranging from −30 to +150 g C m −2 per year.We also investigated the impact of replacing measurements at night, when turbulent mixing is insufficient. The nighttime correction for low friction velocities (u * ) shifted annual F NEE on average by +77 g C m −2 per year, but in certain cases as much as +185 g C m −2 per year.Our results emphasize the need to standardize gap filling-methods for improving the comparability of flux data products from regional and global flux networks.

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

Abstract. 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 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. CO 2 emissions from fossil fuels and industry (E FF ) are based on energy statistics and cement production data, respectively, while emissions from land-use change (E LUC ), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO 2 concentration is measured directly and its rate of growth (G ATM ) is computed from the annual changes in concentration. The mean ocean CO 2 sink (S OCEAN ) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in S OCEAN is evaluated with data products based on surveys of ocean CO 2 measurements. The global residual terrestrial CO 2 sink (S LAND ) 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)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015), E FF was 9.3 ± 0.5 GtC yr −1 , E LUC 1.0 ± 0.5 GtC yr −1 , G ATM 4.5 ± 0.1 GtC yr −1 , S OCEAN 2.6 ± 0.5 GtC yr −1 , and S LAND 3.1 ± 0.9 GtC yr −1 . For year 2015 alone, the growth in E FF 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, E LUC was 1.3 ± 0.5 GtC yr −1 , G ATM was 6.3 ± 0.2 GtC yr −1 , S OCEAN was 3.0 ± 0.5 GtC yr −1 , and S LAND was 1.9 ± 0.9 GtC yr −1 . G ATM was higher in 2015 compared to the past decade (2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015), reflecting a smaller S LAND for that year. The global atmospheric CO 2 concentration reached 399.4 ± 0.1 ppm averaged over 2015. For 2016, preliminary data indicate the continuation of low growth in E FF 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 correc...

Abstract. FLUXNET comprises globally distributed eddy-covariance-based estimates of carbon fluxes between the biosphere and the atmosphere. Since eddy covariance flux towers have a relatively small footprint and are distributed unevenly across the world, upscaling the observations is necessary to obtain global-scale estimates of biosphere–atmosphere exchange. Based on cross-consistency checks with atmospheric inversions, sun-induced fluorescence (SIF) and dynamic global vegetation models (DGVMs), here we provide a systematic assessment of the latest upscaling efforts for gross primary production (GPP) and net ecosystem exchange (NEE) of the FLUXCOM initiative, where different machine learning methods, forcing data sets and sets of predictor variables were employed. Spatial patterns of mean GPP are consistent across FLUXCOM and DGVM ensembles (R2>0.94 at 1∘ spatial resolution) while the majority of DGVMs show, for 70 % of the land surface, values outside the FLUXCOM range. Global mean GPP magnitudes for 2008–2010 from FLUXCOM members vary within 106 and 130 PgC yr−1 with the largest uncertainty in the tropics. Seasonal variations in independent SIF estimates agree better with FLUXCOM GPP (mean global pixel-wise R2∼0.75) than with GPP from DGVMs (mean global pixel-wise R2∼0.6). Seasonal variations in FLUXCOM NEE show good consistency with atmospheric inversion-based net land carbon fluxes, particularly for temperate and boreal regions (R2>0.92). Interannual variability of global NEE in FLUXCOM is underestimated compared to inversions and DGVMs. The FLUXCOM version which also uses meteorological inputs shows a strong co-variation in interannual patterns with inversions (R2=0.87 for 2001–2010). Mean regional NEE from FLUXCOM shows larger uptake than inversion and DGVM-based estimates, particularly in the tropics with discrepancies of up to several hundred grammes of carbon per square metre per year. These discrepancies can only partly be reconciled by carbon loss pathways that are implicit in inversions but not captured by the flux tower measurements such as carbon emissions from fires and water bodies. We hypothesize that a combination of systematic biases in the underlying eddy covariance data, in particular in tall tropical forests, and a lack of site history effects on NEE in FLUXCOM are likely responsible for the too strong tropical carbon sink estimated by FLUXCOM. Furthermore, as FLUXCOM does not account for CO2 fertilization effects, carbon flux trends are not realistic. Overall, current FLUXCOM estimates of mean annual and seasonal cycles of GPP as well as seasonal NEE variations provide useful constraints of global carbon cycling, while interannual variability patterns from FLUXCOM are valuable but require cautious interpretation. Exploring the diversity of Earth observation data and of machine learning concepts along with improved quality and quantity of flux tower measurements will facilitate further improvements of the FLUXCOM approach overall.

The net ecosystem exchange of CO2 between forests and the atmosphere, measured by eddy covariance, is the small difference between two large fluxes of photosynthesis and respiration. Chamber measurements of soil surface CO2 efflux (Fs), wood respiration (Fw) and foliage respiration (Ff) help identify the contributions of these individual components to net ecosystem exchange. Models developed from the chamber data also provide independent estimates of respiration costs. We measured CO2 efflux with chambers periodically in 1996–97 in a ponderosa pine forest in Oregon, scaled these measurements to the ecosystem, and computed annual totals for respiration by component. We also compared estimated half‐hourly ecosystem respiration at night (Fnc) with eddy covariance measurements. Mean foliage respiration normalized to 10 °C was 0.20 μmol m–2 (hemi‐leaf surface area) s–1, and reached a maximum of 0.24 μmol m–2 HSA s–1 between days 162 and 208. Mean wood respiration normalized to 10 °C was 5.9 μmol m–3 sapwood s–1, with slightly higher rates in mid‐summer, when growth occurs. There was no significant difference (P > 0.10) between wood respiration of young (45 years) and old trees (250 years). Soil surface respiration normalized to 10 °C ranged from 0.7 to 3.0 μmol m–2 (ground) s–1 from days 23 to 329, with the lowest rates in winter and highest rates in late spring. Annual CO2 flux from soil surface, foliage and wood was 683, 157, and 54 g C m–2 y–1, with soil fluxes responsible for 76% of ecosystem respiration. The ratio of net primary production to gross primary production was 0.45, consistent with values for conifer sites in Oregon and Australia, but higher than values reported for boreal coniferous forests. Below‐ground carbon allocation (root turnover and respiration, estimated as Fs– litterfall carbon) consumed 61% of GPP; high ratios such as this are typical of sites with more water and nutrient constraints. The chamber estimates were moderately correlated with change in CO2 storage in the canopy (Fstor) on calm nights (friction velocity u* < 0.25 m s–1; R2 = 0.60); Fstor was not significantly different from summed chamber estimates. On windy nights (u* > 0.25 m s–1), the sum of turbulent flux measured above the canopy by eddy covariance and Fstor was only weakly correlated with summed chamber estimates (R2 = 0.14); the eddy covariance estimates were lower than chamber estimates by 50%.

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We compared carbon storage and fluxes in young and old ponderosa pine stands in Oregon, including plant and soil storage, net primary productivity, respiration fluxes, eddy flux estimates of net ecosystem exchange (NEE), and Biome‐BGC simulations of fluxes. The young forest (Y site) was previously an old‐growth ponderosa pine forest that had been clearcut in 1978, and the old forest (O site), which has never been logged, consists of two primary age classes (50 and 250 years old). Total ecosystem carbon content (vegetation, detritus and soil) of the O forest was about twice that of the Y site (21 vs. 10 kg C m−2 ground), and significantly more of the total is stored in living vegetation at the O site (61% vs. 15%). Ecosystem respiration (Re) was higher at the O site (1014 vs. 835 g C m−2 year−1), and it was largely from soils at both sites (77% of Re). The biological data show that above‐ground net primary productivity (ANPP), NPP and net ecosystem production (NEP) were greater at the O site than the Y site. Monte Carlo estimates of NEP show that the young site is a source of CO2 to the atmosphere, and is significantly lower than NEP(O) by c. 100 g C m−2 year−1. Eddy covariance measurements also show that the O site was a stronger sink for CO2 than the Y site. Across a 15‐km swath in the region, ANPP ranged from 76 g C m−2 year−1 at the Y site to 236 g C m−2 year−1 (overall mean 158 ± 14 g C m−2 year−1). The lowest ANPP values were for the youngest and oldest stands, but there was a large range of ANPP for mature stands. Carbon, water and nitrogen cycle simulations with the Biome‐BGC model suggest that disturbance type and frequency, time since disturbance, age‐dependent changes in below‐ground allocation, and increasing atmospheric concentration of CO2 all exert significant control on the net ecosystem exchange of carbon at the two sites. Model estimates of major carbon flux components agree with budget‐based observations to within ± 20%, with larger differences for NEP and for several storage terms. Simulations showed the period of regrowth required to replace carbon lost during and after a stand‐replacing fire (O) or a clearcut (Y) to be between 50 and 100 years. In both cases, simulations showed a shift from net carbon source to net sink (on an annual basis) 10–20 years after disturbance. These results suggest that the net ecosystem production of young stands may be low because heterotrophic respiration, particularly from soils, is higher than the NPP of the regrowth. The amount of carbon stored in long‐term pools (biomass and soils) in addition to short‐term fluxes has important implications for management of forests in the Pacific North‐west for carbon sequestration.