Accurate assessment of anthropogenic carbon dioxide (CO₂) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO₂ emissions (E_FOS) are based on energy statistics and cement production data, while emissions from 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) is estimated with global ocean biogeochemistry models and observation-based f CO₂ products. The terrestrial CO₂ sink (S_LAND) is estimated with dynamic global vegetation models. Additional lines of evidence on land and ocean sinks are provided by atmospheric inversions, atmospheric oxygen measurements, and Earth system models. 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 incomplete understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2022, E_FOS increased by 0.9 % relative to 2021, with fossil emissions at 9.9±0.5 Gt C yr⁻¹ (10.2±0.5 Gt C yr⁻¹ when the cement carbonation sink is not included), and E_LUC was 1.2±0.7 Gt C yr⁻¹, for a total anthropogenic CO₂ emission (including the cement carbonation sink) of 11.1±0.8 Gt C yr⁻¹ (40.7±3.2 Gt CO₂ yr⁻¹). Also, for 2022, G_ATM was 4.6±0.2 Gt C yr⁻¹ (2.18±0.1 ppm yr⁻¹; ppm denotes parts per million), S_OCEAN was 2.8±0.4 Gt C yr⁻¹, and S_LAND was 3.8±0.8 Gt C yr⁻¹, with a B_IM of −0.1 Gt C yr⁻¹ (i.e. total estimated sources marginally too low or sinks marginally too high). The global atmospheric CO₂ concentration averaged over 2022 reached 417.1±0.1 ppm. Preliminary data for 2023 suggest an increase in E_FOS relative to 2022 of +1.1 % (0.0 % to 2.1 %) globally and atmospheric CO₂ concentration reaching 419.3 ppm, 51 % above the pre-industrial level (around 278 ppm in 1750). Overall, the mean of and trend in the components of the global carbon budget are consistently estimated over the period 1959–2022, with a near-zero overall budget imbalance, although discrepancies of up to around 1 Gt C yr⁻¹ persist for the representation of annual to semi-decadal variability in CO₂ fluxes. Comparison of estimates from multiple approaches and observations shows the following: (1) a persistent large uncertainty in the estimate of land-use changes emissions, (2) a low agreement between the different methods on the magnitude of the land CO₂ flux in the northern extra-tropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living-data update documents changes in methods and data sets applied to this most recent global carbon budget as well as evolving community understanding of the global carbon cycle. The data presented in this work are available at https://doi.org/10.18160/GCP-2023 (Friedlingstein et al., 2023).

Accurate assessment of anthropogenic carbon dioxide (CO₂) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize datasets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO₂ emissions (E_FOS) are based on energy statistics and cement production data, while emissions from land-use change (E_LUC) 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 global net uptake of CO₂ by the ocean (S_OCEAN, called the ocean sink) is estimated with global ocean biogeochemistry models and observation-based fCO₂ products (fCO₂ is the fugacity of CO₂). The global net uptake of CO₂ by the land (S_LAND, called the land sink) is estimated with dynamic global vegetation models. Additional lines of evidence on land and ocean sinks are provided by atmospheric inversions, atmospheric oxygen measurements, and Earth system models. The sum of all sources and sinks results in the carbon budget imbalance (B_IM), a measure of imperfect data and incomplete understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2023, E_FOS increased by 1.3 % relative to 2022, with fossil emissions at 10.1 ± 0.5 GtC yr⁻¹ (10.3 ± 0.5 GtC yr⁻¹ when the cement carbonation sink is not included), and E_LUC was 1.0 ± 0.7 GtC yr⁻¹, for a total anthropogenic CO₂ emission (including the cement carbonation sink) of 11.1 ± 0.9 GtC yr⁻¹ (40.6 ± 3.2 GtCO₂ yr⁻¹). Also, for 2023, G_ATM was 5.9 ± 0.2 GtC yr⁻¹ (2.79 ± 0.1 ppm yr⁻¹; ppm denotes parts per million), S_OCEAN was 2.9 ± 0.4 GtC yr⁻¹, and S_LAND was 2.3 ± 1.0 GtC yr⁻¹, with a near-zero B_IM (−0.02 GtC yr⁻¹). The global atmospheric CO₂ concentration averaged over 2023 reached 419.31 ± 0.1 ppm. Preliminary data for 2024 suggest an increase in E_FOS relative to 2023 of +0.8 % (−0.2 % to 1.7 %) globally and an atmospheric CO₂ concentration increase by 2.87 ppm, reaching 422.45 ppm, 52 % above the pre-industrial level (around 278 ppm in 1750). Overall, the mean of and trend in the components of the global carbon budget are consistently estimated over the period 1959–2023, with a near-zero overall budget imbalance, although discrepancies of up to around 1 GtC yr⁻¹ persist for the representation of annual to semi-decadal variability in CO₂ fluxes. Comparison of estimates from multiple approaches and observations shows the following: (1) a persistent large uncertainty in the estimate of land-use change emissions, (2) low agreement between the different methods on the magnitude of the land CO₂ flux in the northern extra-tropics, and (3) a discrepancy between the different methods on the mean ocean sink. This living-data update documents changes in methods and datasets applied to this most recent global carbon budget as well as evolving community understanding of the global carbon cycle. The data presented in this work are available at https://doi.org/10.18160/GCP-2024 (Friedlingstein et al., 2024).

Accurate assessment of anthropogenic carbon dioxide (CO ₂ ) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesise datasets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO ₂ emissions ( E _FOS ) are based on energy and cement production data. Emissions from land-use change ( E _LUC ) are estimated by bookkeeping models based on land-use data. The global atmospheric CO ₂ growth rate ( G _ATM ) is computed from changes in concentration measured at surface stations. The global net uptake of CO ₂ by the ocean ( S _OCEAN ) is estimated with global ocean biogeochemistry models and observation-based f CO ₂ -products. The global net uptake of CO ₂ by the land ( S _LAND ) is estimated with dynamic global vegetation models. Additional lines of evidence are provided by atmospheric inversions, atmospheric oxygen measurements, ocean interior observation-based estimates, and Earth System Models. This year, we introduced corrections on the E _LUC , S _OCEAN and S _LAND estimates. The sum of all sources and sinks results in the carbon budget imbalance ( B _IM ), a measure of imperfect data and incomplete understanding of the contemporary carbon cycle. All uncertainties are reported as ± 1 σ . For the year 2024, E _FOS increased by 1.1 % relative to 2023, with fossil emissions at 10.3 ± 0.5 GtC yr ⁻¹ (including the cement carbonation sink, 0.2 GtC yr ⁻¹ ), E _LUC was 1.3 ± 0.7 GtC yr ⁻¹ , for total anthropogenic CO ₂ emissions of 11.6 ± 0.9 GtC yr ⁻¹ (42.4 ± 3.2 GtCO ₂ yr ⁻¹ ). Also, for 2024, G _ATM was 7.9 ± 0.2 GtC yr ⁻¹ (3.73 ± 0.1 ppm yr ⁻¹ ), 2.2 GtC above the 2023 growth rate. S _OCEAN was 3.4 ± 0.4 GtC yr ⁻¹ and S _LAND was 1.9 ± 1.1 GtC yr ⁻¹ , leaving a large negative B _IM (−1.7 GtC yr ⁻¹ ), suggesting that the total sink or G _ATM is strongly overestimated in 2024. The global atmospheric CO ₂ concentration averaged over 2024 reached 422.8 ± 0.1 ppm. Preliminary data for 2025 suggest an increase in E _FOS relative to 2024 of +1.0 % (0.2 % to 1.7 %) globally, and atmospheric CO ₂ concentration increasing by 2.1 ppm reaching 425.6 ppm, 53 % above the pre-industrial level (around 278 ppm in 1750). Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2024, with a near-zero overall budget imbalance, although discrepancies of up to around 1 GtC yr ⁻¹ persist for the representation of annual to decadal variability in CO ₂ fluxes. Comparison of estimates from multiple approaches and observations shows: (1) a persistent large uncertainty in the estimate of land-use change emissions, (2) a low agreement between the different methods on the magnitude of the land CO ₂ flux in the northern extra-tropics, and (3) a discrepancy between the different methods on the mean ocean sink. This living data update documents changes in methods and datasets applied to this most-recent global carbon budget as well as evolving community understanding of the global carbon cycle. The data presented in this work are available at https://doi.org/10.18160/GCP-2025 (Friedlingstein et al., 2025c).

Large stocks of soil carbon (C) and nitrogen (N) in northern permafrost soils are vulnerable to remobilization under climate change. However, there are large uncertainties in present‐day greenhouse gas (GHG) budgets. We compare bottom‐up (data‐driven upscaling and process‐based models) and top‐down (atmospheric inversion models) budgets of carbon dioxide (CO₂), methane (CH₄) and nitrous oxide (N₂O) as well as lateral fluxes of C and N across the region over 2000–2020. Bottom‐up approaches estimate higher land‐to‐atmosphere fluxes for all GHGs. Both bottom‐up and top‐down approaches show a sink of CO₂ in natural ecosystems (bottom‐up: −29 (−709, 455), top‐down: −587 (−862, −312) Tg CO₂‐C yr⁻¹) and sources of CH₄ (bottom‐up: 38 (22, 53), top‐down: 15 (11, 18) Tg CH₄‐C yr⁻¹) and N₂O (bottom‐up: 0.7 (0.1, 1.3), top‐down: 0.09 (−0.19, 0.37) Tg N₂O‐N yr⁻¹). The combined global warming potential of all three gases (GWP‐100) cannot be distinguished from neutral. Over shorter timescales (GWP‐20), the region is a net GHG source because CH₄ dominates the total forcing. The net CO₂ sink in Boreal forests and wetlands is largely offset by fires and inland water CO₂ emissions as well as CH₄ emissions from wetlands and inland waters, with a smaller contribution from N₂O emissions. Priorities for future research include the representation of inland waters in process‐based models and the compilation of process‐model ensembles for CH₄ and N₂O. Discrepancies between bottom‐up and top‐down methods call for analyses of how prior flux ensembles impact inversion budgets, more and well‐distributed in situ GHG measurements and improved resolution in upscaling techniques.

The terrestrial carbon cycle plays a critical role in modulating the interactions of climate with the Earth system, but different models often make vastly different predictions of its behavior. Efforts to reduce model uncertainty have commonly focused on model structure, namely by introducing additional processes and increasing structural complexity. However, the extent to which increased structural complexity can directly improve predictive skill is unclear. While adding processes may improve realism, the resulting models are often encumbered by a greater number of poorly determined or over-generalized parameters. To guide efficient model development, here we map the theoretical relationship between model complexity and predictive skill. To do so, we developed 16 structurally distinct carbon cycle models spanning an axis of complexity and incorporated them into a model–data fusion system. We calibrated each model at six globally distributed eddy covariance sites with long observation time series and under 42 data scenarios that resulted in different degrees of parameter uncertainty. For each combination of site, data scenario, and model, we then predicted net ecosystem exchange (NEE) and leaf area index (LAI) for validation against independent local site data. Though the maximum model complexity we evaluated is lower than most traditional terrestrial biosphere models, the complexity range we explored provides universal insight into the inter-relationship between structural uncertainty, parametric uncertainty, and model forecast skill. Specifically, increased complexity only improves forecast skill if parameters are adequately informed (e.g., when NEE observations are used for calibration). Otherwise, increased complexity can degrade skill and an intermediate-complexity model is optimal. This finding remains consistent regardless of whether NEE or LAI is predicted. Our COMPLexity EXperiment (COMPLEX) highlights the importance of robust observation-based parameterization for land surface modeling and suggests that data characterizing net carbon fluxes will be key to improving decadal predictions of high-dimensional terrestrial biosphere models.