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Global estimates of the land carbon sink are often based on simulations by terrestrial biosphere models (TBMs). The use of a large number of models that differ in their underlying hypotheses, structure and parameters is one way to assess the uncertainty in the historical land carbon sink. Here we show that the atmospheric forcing datasets used to drive these TBMs represent a significant source of uncertainty that is currently not systematically accounted for in land carbon cycle evaluations. We present results from three TBMs each forced with three different historical atmospheric forcing reconstructions over the period 1850–2015. We perform an analysis of variance to quantify the relative uncertainty in carbon fluxes arising from the models themselves, atmospheric forcing, and model-forcing interactions. We find that atmospheric forcing in this set of simulations plays a dominant role on uncertainties in global gross primary productivity (GPP) (75% of variability) and autotrophic respiration (90%), and a significant but reduced role on net primary productivity and heterotrophic respiration (30%). Atmospheric forcing is the dominant driver (52%) of variability for the net ecosystem exchange flux, defined as the difference between GPP and respiration (both autotrophic and heterotrophic respiration). In contrast, for wildfire-driven carbon emissions model uncertainties dominate and, as a result, model uncertainties dominate for net ecosystem productivity. At regional scales, the contribution of atmospheric forcing to uncertainty shows a very heterogeneous pattern and is smaller on average than at the global scale. We find that this difference in the relative importance of forcing uncertainty between global and regional scales is related to large differences in regional model flux estimates, which partially offset each other when integrated globally, while the flux differences driven by forcing are mainly consistent across the world and therefore add up to a larger fractional contribution to global uncertainty.

 

Drylands cover ca. 40% of the land surface and are hypothesised to play a major role in the global carbon cycle, controlling both long-term trends and interannual variation. These insights originate from land surface models (LSMs) that have not been extensively calibrated and evaluated for water-limited ecosystems. We need to learn more about dryland carbon dynamics, particularly as the transitory response and rapid turnover rates of semi-arid systems may limit their function as a carbon sink over multi-decadal scales. We quantified aboveground biomass carbon (AGC; inferred from SMOS L-band vegetation optical depth) and gross primary productivity (GPP; from PML-v2 inferred from MODIS observations) and tested their spatial and temporal correspondence with estimates from the TRENDY ensemble of LSMs. We found strong correspondence in GPP between LSMs and PML-v2 both in spatial patterns (Pearson’s r = 0.9 for TRENDY-mean) and in inter-annual variability, but not in trends. Conversely, for AGC we found lesser correspondence in space (Pearson’s r = 0.75 for TRENDY-mean, strong biases for individual models) and in the magnitude of inter-annual variability compared to satellite retrievals. These disagreements likely arise from limited representation of ecosystem responses to plant water availability, fire, and photodegradation that drive dryland carbon dynamics. We assessed inter-model agreement and drivers of long-term change in carbon stocks over centennial timescales. This analysis suggested that the simulated trend of increasing carbon stocks in drylands is in soils and primarily driven by increased productivity due to CO 2 enrichment. However, there is limited empirical evidence of this 50-year sink in dryland soils. Our findings highlight important uncertainties in simulations of dryland ecosystems by current LSMs, suggesting a need for continued model refinements and for greater caution when interpreting LSM estimates with regards to current and future carbon dynamics in drylands and by extension the global carbon cycle. 

Abstract Despite their sparse vegetation, dryland regions exert a huge influence over global biogeochemical cycles because they cover more than 40% of the world surface (Schimel 2010 Science 327 418–9). It is thought that drylands dominate the inter-annual variability (IAV) and long-term trend in the global carbon (C) cycle (Poulter et al 2014 Nature 509 600–3, Ahlstrom et al 2015 Science 348 895–9, Zhang et al 2018 Glob. Change Biol . 24 3954–68). Projections of the global land C sink therefore rely on accurate representation of dryland C cycle processes; however, the dynamic global vegetation models (DGVMs) used in future projections have rarely been evaluated against dryland C flux data. Here, we carried out an evaluation of 14 DGVMs (TRENDY v7) against net ecosystem exchange (NEE) data from 12 dryland flux sites in the southwestern US encompassing a range of ecosystem types (forests, shrub- and grasslands). We find that all the models underestimate both mean annual C uptake/release as well as the magnitude of NEE IAV, suggesting that improvements in representing dryland regions may improve global C cycle projections. Across all models, the sensitivity and timing of ecosystem C uptake to plant available moisture was at fault. Spring biases in gross primary production (GPP) dominate the underestimate of mean annual NEE, whereas models’ lack of GPP response to water availability in both spring and summer monsoon are responsible for inability to capture NEE IAV. Errors in GPP moisture sensitivity at high elevation forested sites were more prominent during the spring, while errors at the low elevation shrub and grass-dominated sites were more important during the monsoon. We propose a range of hypotheses for why model GPP does not respond sufficiently to changing water availability that can serve as a guide for future dryland DGVM developments. Our analysis suggests that improvements in modeling C cycle processes across more than a quarter of the Earth’s land surface could be achieved by addressing the moisture sensitivity of dryland C uptake. 

Abstract. Evapotranspiration (ET) is critical in linking global water, carbon andenergy cycles. However, direct measurement of global terrestrial ET is notfeasible. Here, we first reviewed the basic theory and state-of-the-artapproaches for estimating global terrestrial ET, including remote-sensing-based physical models, machine-learning algorithms and land surfacemodels (LSMs). We then utilized 4 remote-sensing-based physical models,2 machine-learning algorithms and 14 LSMs to analyze the spatial andtemporal variations in global terrestrial ET. The results showed that theensemble means of annual global terrestrial ET estimated by these threecategories of approaches agreed well, with values ranging from 589.6 mm yr−1(6.56×104 km3 yr−1) to 617.1 mm yr−1(6.87×104 km3 yr−1). For the period from 1982 to 2011, boththe ensembles of remote-sensing-based physical models and machine-learningalgorithms suggested increasing trends in global terrestrial ET (0.62 mm yr−2 with a significance level of p<0.05 and 0.38 mm yr−2 with a significance level of p<0.05,respectively). In contrast, the ensemble mean of the LSMs showed nostatistically significant change (0.23 mm yr−2, p>0.05),although many of the individual LSMs reproduced an increasing trend.Nevertheless, all 20 models used in this study showed that anthropogenicEarth greening had a positive role in increasing terrestrial ET. Theconcurrent small interannual variability, i.e., relative stability, found inall estimates of global terrestrial ET, suggests that a potentialplanetary boundary exists in regulating global terrestrial ET, with the value of this boundary beingaround 600 mm yr−1. Uncertainties among approaches were identified inspecific regions, particularly in the Amazon Basin and arid/semiaridregions. Improvements in parameterizing water stress and canopy dynamics,the utilization of new available satellite retrievals and deep-learning methods,and model–data fusion will advance our predictive understanding of globalterrestrial ET. 

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions andtheir redistribution among the atmosphere, ocean, and terrestrial biospherein a changing climate is critical to better understand the global carboncycle, support the development of climate policies, and project futureclimate change. Here we describe and synthesize datasets and methodology toquantify the five major components of the global carbon budget and theiruncertainties. Fossil CO2 emissions (EFOS) are based on energystatistics and cement production data, while emissions from land-use change(ELUC), mainly deforestation, are based on land use and land-use changedata and bookkeeping models. Atmospheric CO2 concentration is measureddirectly, and its growth rate (GATM) is computed from the annualchanges in concentration. The ocean CO2 sink (SOCEAN) is estimatedwith global ocean biogeochemistry models and observation-baseddata products. The terrestrial CO2 sink (SLAND) is estimated withdynamic global vegetation models. The resulting carbon budget imbalance(BIM), the difference between the estimated total emissions and theestimated changes in the atmosphere, ocean, and terrestrial biosphere, is ameasure of imperfect data and understanding of the contemporary carboncycle. All uncertainties are reported as ±1σ. For the firsttime, an approach is shown to reconcile the difference in our ELUCestimate with the one from national greenhouse gas inventories, supportingthe assessment of collective countries' climate progress. For the year 2020, EFOS declined by 5.4 % relative to 2019, withfossil emissions at 9.5 ± 0.5 GtC yr−1 (9.3 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 0.9 ± 0.7 GtC yr−1, for a total anthropogenic CO2 emission of10.2 ± 0.8 GtC yr−1 (37.4 ± 2.9 GtCO2). Also, for2020, GATM was 5.0 ± 0.2 GtC yr−1 (2.4 ± 0.1 ppm yr−1), SOCEAN was 3.0 ± 0.4 GtC yr−1, and SLANDwas 2.9 ± 1 GtC yr−1, with a BIM of −0.8 GtC yr−1. Theglobal atmospheric CO2 concentration averaged over 2020 reached 412.45 ± 0.1 ppm. Preliminary data for 2021 suggest a rebound in EFOSrelative to 2020 of +4.8 % (4.2 % to 5.4 %) globally. Overall, the mean and trend in the components of the global carbon budgetare consistently estimated over the period 1959–2020, but discrepancies ofup to 1 GtC yr−1 persist for the representation of annual tosemi-decadal variability in CO2 fluxes. Comparison of estimates frommultiple approaches and observations shows (1) a persistent largeuncertainty in the estimate of land-use changes emissions, (2) a lowagreement between the different methods on the magnitude of the landCO2 flux in the northern extra-tropics, and (3) a discrepancy betweenthe different methods on the strength of the ocean sink over the lastdecade. This living data update documents changes in the methods and datasets used in this new global carbon budget and the progress in understandingof the global carbon cycle compared with previous publications of this dataset (Friedlingstein et al., 2020, 2019; LeQuéré et al., 2018b, a, 2016, 2015b, a, 2014, 2013). Thedata presented in this work are available at https://doi.org/10.18160/gcp-2021 (Friedlingstein et al., 2021). 

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions andtheir redistribution among the atmosphere, ocean, and terrestrial biospherein a changing climate – the “global carbon budget” – is important tobetter understand the global carbon cycle, support the development ofclimate policies, and project future climate change. Here we describe andsynthesize data sets and methodology to quantify the five major componentsof the global carbon budget and their uncertainties. Fossil CO2emissions (EFOS) are based on energy statistics and cement productiondata, while emissions from land-use change (ELUC), mainlydeforestation, are based on land use and land-use change data andbookkeeping models. Atmospheric CO2 concentration is measured directlyand its growth rate (GATM) is computed from the annual changes inconcentration. The ocean CO2 sink (SOCEAN) and terrestrialCO2 sink (SLAND) are estimated with global process modelsconstrained by observations. The resulting carbon budget imbalance(BIM), the difference between the estimated total emissions and theestimated changes in the atmosphere, ocean, and terrestrial biosphere, is ameasure of imperfect data and understanding of the contemporary carboncycle. All uncertainties are reported as ±1σ. For the lastdecade available (2010–2019), EFOS was 9.6 ± 0.5 GtC yr−1 excluding the cement carbonation sink (9.4 ± 0.5 GtC yr−1 when the cement carbonation sink is included), andELUC was 1.6 ± 0.7 GtC yr−1. For the same decade, GATM was 5.1 ± 0.02 GtC yr−1 (2.4 ± 0.01 ppm yr−1), SOCEAN 2.5 ±  0.6 GtC yr−1, and SLAND 3.4 ± 0.9 GtC yr−1, with a budgetimbalance BIM of −0.1 GtC yr−1 indicating a near balance betweenestimated sources and sinks over the last decade. For the year 2019 alone, thegrowth in EFOS was only about 0.1 % with fossil emissions increasingto 9.9 ± 0.5 GtC yr−1 excluding the cement carbonation sink (9.7 ± 0.5 GtC yr−1 when cement carbonation sink is included), and ELUC was 1.8 ± 0.7 GtC yr−1, for total anthropogenic CO2 emissions of 11.5 ± 0.9 GtC yr−1 (42.2 ± 3.3 GtCO2). Also for 2019, GATM was5.4 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEANwas 2.6 ± 0.6 GtC yr−1, and SLAND was 3.1 ± 1.2 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2concentration reached 409.85 ± 0.1 ppm averaged over 2019. Preliminarydata for 2020, accounting for the COVID-19-induced changes in emissions,suggest a decrease in EFOS relative to 2019 of about −7 % (medianestimate) based on individual estimates from four studies of −6 %, −7 %,−7 % (−3 % to −11 %), and −13 %. Overall, the mean and trend in thecomponents of the global carbon budget are consistently estimated over theperiod 1959–2019, but discrepancies of up to 1 GtC yr−1 persist for therepresentation of semi-decadal variability in CO2 fluxes. Comparison ofestimates from diverse approaches and observations shows (1) no consensusin 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 ofthe land CO2 flux in the northern extra-tropics, and (3) an apparentdiscrepancy between the different methods for the ocean sink outside thetropics, particularly in the Southern Ocean. This living data updatedocuments changes in the methods and data sets used in this new globalcarbon budget and the progress in understanding of the global carbon cyclecompared with previous publications of this data set (Friedlingstein et al.,2019; Le Quéré et al., 2018b, a, 2016, 2015b, a, 2014,2013). The data presented in this work are available at https://doi.org/10.18160/gcp-2020 (Friedlingstein et al., 2020). 

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions andtheir redistribution among the atmosphere, ocean, and terrestrial biosphere– the “global carbon budget” – is important to better understand theglobal carbon cycle, support the development of climate policies, andproject future climate change. Here we describe data sets and methodology toquantify the five major components of the global carbon budget and theiruncertainties. Fossil CO2 emissions (EFF) are based on energystatistics and cement production data, while emissions from land use change(ELUC), mainly deforestation, are based on land use and land use changedata and bookkeeping models. Atmospheric CO2 concentration is measureddirectly and its growth rate (GATM) is computed from the annual changesin concentration. The ocean CO2 sink (SOCEAN) and terrestrialCO2 sink (SLAND) are estimated with global process modelsconstrained by observations. The resulting carbon budget imbalance(BIM), the difference between the estimated total emissions and theestimated changes in the atmosphere, ocean, and terrestrial biosphere, is ameasure of imperfect data and understanding of the contemporary carboncycle. All uncertainties are reported as ±1σ. For the lastdecade 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 budgetimbalance BIM of 0.4 GtC yr−1 indicating overestimated emissionsand/or underestimated sinks. For the year 2018 alone, the growth in EFF wasabout 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 anthropogenicCO2 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, theUSA, the EU, and India and projections of gross domestic product correctedfor recent changes in the carbon intensity of the economy for the rest ofthe world. Overall, the mean and trend in the five components of the globalcarbon budget are consistently estimated over the period 1959–2018, butdiscrepancies of up to 1 GtC yr−1 persist for the representation ofsemi-decadal variability in CO2 fluxes. A detailed comparison amongindividual estimates and the introduction of a broad range of observationsshows (1) no consensus in the mean and trend in land use change emissionsover the last decade, (2) a persistent low agreement between the differentmethods on the magnitude of the land CO2 flux in the northernextra-tropics, and (3) an apparent underestimation of the CO2variability by ocean models outside the tropics. This living data updatedocuments changes in the methods and data sets used in this new globalcarbon budget and the progress in understanding of the global carbon cyclecompared with previous publications of this data set (Le Quéré etal., 2018a, b, 2016, 2015a, b, 2014, 2013). The data generated bythis work are available at https://doi.org/10.18160/gcp-2019 (Friedlingsteinet al., 2019). 

Abstract. Accurate assessment of anthropogenic carbon dioxide(CO2) emissions and their redistribution among the atmosphere,ocean, and terrestrial biosphere – the “global carbon budget” – isimportant to better understand the global carbon cycle, support thedevelopment of climate policies, and project future climate change. Here wedescribe data sets and methodology to quantify the five major components ofthe global carbon budget and their uncertainties. Fossil CO2emissions (EFF) are based on energy statistics and cementproduction data, while emissions from land use and land-use change (ELUC),mainly deforestation, are based on land use and land-use change data andbookkeeping models. Atmospheric CO2 concentration is measureddirectly and its growth rate (GATM) is computed from the annualchanges in concentration. The ocean CO2 sink (SOCEAN)and terrestrial CO2 sink (SLAND) are estimated withglobal process models constrained by observations. The resulting carbonbudget imbalance (BIM), the difference between the estimatedtotal emissions and the estimated changes in the atmosphere, ocean, andterrestrial biosphere, is a measure of imperfect data and understanding ofthe contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2008–2017), EFF was9.4±0.5 GtC yr−1, ELUC 1.5±0.7 GtC yr−1, GATM 4.7±0.02 GtC yr−1,SOCEAN 2.4±0.5 GtC yr−1, and SLAND 3.2±0.8 GtC yr−1, with a budget imbalance BIM of0.5 GtC yr−1 indicating overestimated emissions and/or underestimatedsinks. For the year 2017 alone, the growth in EFF was about 1.6 %and emissions increased to 9.9±0.5 GtC yr−1. Also for 2017,ELUC was 1.4±0.7 GtC yr−1, GATM was 4.6±0.2 GtC yr−1, SOCEAN was 2.5±0.5 GtC yr−1, and SLAND was 3.8±0.8 GtC yr−1,with a BIM of 0.3 GtC. The global atmosphericCO2 concentration reached 405.0±0.1 ppm averaged over 2017.For 2018, preliminary data for the first 6–9 months indicate a renewedgrowth in EFF of +2.7 % (range of 1.8 % to 3.7 %) basedon national emission projections for China, the US, the EU, and India andprojections of gross domestic product corrected for recent changes in thecarbon intensity of the economy for the rest of the world. The analysispresented here shows that the mean and trend in the five components of theglobal carbon budget are consistently estimated over the period of 1959–2017,but discrepancies of up to 1 GtC yr−1 persist for the representationof semi-decadal variability in CO2 fluxes. A detailed comparisonamong individual estimates and the introduction of a broad range ofobservations show (1) no consensus in the mean and trend in land-use changeemissions, (2) a persistent low agreement among the different methods onthe magnitude of the land CO2 flux in the northern extra-tropics,and (3) an apparent underestimation of the CO2 variability by oceanmodels, originating outside the tropics. This living data update documentschanges in the methods and data sets used in this new global carbon budgetand the progress in understanding the global carbon cycle compared withprevious publications of this data set (Le Quéré et al., 2018, 2016,2015a, b, 2014, 2013). All results presented here can be downloaded fromhttps://doi.org/10.18160/GCP-2018.