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Climate change jeopardizes human health, global biodiversity, and sustainability of the biosphere. To make reliable predictions about climate change, scientists use Earth system models (ESMs) that integrate physical, chemical, and biological processes occurring on land, the oceans, and the atmosphere. Although critical for catalyzing coupled biogeochemical processes, microorganisms have traditionally been left out of ESMs. Here, we generate a "top 10" list of priorities, opportunities, and challenges for the explicit integration of microorganisms into ESMs. We discuss the need for coarse-graining microbial information into functionally relevant categories, as well as the capacity for microorganisms to rapidly evolve in response to climate-change drivers. Microbiologists are uniquely positioned to collect novel and valuable information necessary for next-generation ESMs, but this requires data harmonization and transdisciplinary collaboration to effectively guide adaptation strategies and mitigation policy.

Radiocarbon (14C) is a critical tool for understanding the global carbon cycle. During the Anthropocene, two new processes influenced 14C in atmospheric, land and ocean carbon reservoirs. First, 14C-free carbon derived from fossil fuel burning has diluted 14C, at rates that have accelerated with time. Second, bomb 14C produced by atmospheric nuclear weapon tests in the mid-twentieth century provided a global isotope tracer that is used to constrain rates of air-sea gas exchange, carbon turnover, large-scale atmospheric and ocean transport, and other key C cycle processes. As we write, the 14C/12C ratio of atmospheric CO2 is dropping below pre-industrial levels, and the rate of decline in the future will depend on global fossil fuel use and net exchange of bomb 14C between the atmosphere, ocean and land. This milestone coincides with a rapid increase in 14C measurement capacity worldwide. Leveraging future 14C measurements to understand processes and test models requires coordinated international effort-a decade of radiocarbon with multiple goals: (i) filling observational gaps using archives, (ii) building and sustaining observation networks to increase measurement density across carbon reservoirs, (iii) developing databases, synthesis and modelling tools and (iv) establishing metrics for identifying and verifying changes in carbon sources and sinks. This article is part of the Theo Murphy meeting issue Radiocarbon in the Anthropocene.

Abstract Microbial carbon use efficiency (CUE) affects the fate and storage of carbon in terrestrial ecosystems, but its global importance remains uncertain. Accurately modeling and predicting CUE on a global scale is challenging due to inconsistencies in measurement techniques and the complex interactions of climatic, edaphic, and biological factors across scales. The link between microbial CUE and soil organic carbon relies on the stabilization of microbial necromass within soil aggregates or its association with minerals, necessitating an integration of microbial and stabilization processes in modeling approaches. In this perspective, we propose a comprehensive framework that integrates diverse data sources, ranging from genomic information to traditional soil carbon assessments, to refine carbon cycle models by incorporating variations in CUE, thereby enhancing our understanding of the microbial contribution to carbon cycling.

Achieving climate targets requires mitigation against climate change but also understanding of the response of land and ocean carbon systems. In this context, global soil carbon stocks and their response to environmental changes are key. This paper quantifies the global soil carbon feedbacks due to changes in atmospheric CO2, and the associated climate changes, for Earth system models (ESMs) in CMIP6. A standard approach is used to calculate carbon cycle feedbacks, defined here as soil carbon-concentration (βs) and carbon-climate (γs) feedback parameters, which are also broken down into processes which drive soil carbon change. The sensitivity to CO2 is shown to dominate soil carbon changes at least up to a doubling of atmospheric CO2. However, the sensitivity of soil carbon to climate change is found to become an increasingly important source of uncertainty under higher atmospheric CO2 concentrations.

Intergovernmental Panel on Climate Change (IPCC) assessments are the trusted source of scientific evidence for climate negotiations taking place under the United Nations Framework Convention on Climate Change (UNFCCC). Evidence-based decision-making needs to be informed by up-to-date and timely information on key indicators of the state of the climate system and of the human influence on the global climate system. However, successive IPCC reports are published at intervals of 5–10 years, creating potential for an information gap between report cycles. We follow methods as close as possible to those used in the IPCC Sixth Assessment Report (AR6) Working Group One (WGI) report. We compile monitoring datasets to produce estimates for key climate indicators related to forcing of the climate system: emissions of greenhouse gases and short-lived climate forcers, greenhouse gas concentrations, radiative forcing, the Earth's energy imbalance, surface temperature changes, warming attributed to human activities, the remaining carbon budget, and estimates of global temperature extremes. The purpose of this effort, grounded in an open-data, open-science approach, is to make annually updated reliable global climate indicators available in the public domain (https://doi.org/10.5281/zenodo.11388387, Smith et al., 2024a). As they are traceable to IPCC report methods, they can be trusted by all parties involved in UNFCCC negotiations and help convey wider understanding of the latest knowledge of the climate system and its direction of travel. The indicators show that, for the 2014–2023 decade average, observed warming was 1.19 [1.06 to 1.30] °C, of which 1.19 [1.0 to 1.4] °C was human-induced. For the single-year average, human-induced warming reached 1.31 [1.1 to 1.7] °C in 2023 relative to 1850–1900. The best estimate is below the 2023-observed warming record of 1.43 [1.32 to 1.53] °C, indicating a substantial contribution of internal variability in the 2023 record. Human-induced warming has been increasing at a rate that is unprecedented in the instrumental record, reaching 0.26 [0.2–0.4] °C per decade over 2014–2023. This high rate of warming is caused by a combination of net greenhouse gas emissions being at a persistent high of 53±5.4 Gt CO2e yr−1 over the last decade, as well as reductions in the strength of aerosol cooling. Despite this, there is evidence that the rate of increase in CO2 emissions over the last decade has slowed compared to the 2000s, and depending on societal choices, a continued series of these annual updates over the critical 2020s decade could track a change of direction for some of the indicators presented here.

Terrestrial ecosystems have taken up about 32% of the total anthropogenic CO2 emissions in the past six decades1. Large uncertainties in terrestrial carbon-climate feedbacks, however, make it difficult to predict how the land carbon sink will respond to future climate change2. Interannual variations in the atmospheric CO2 growth rate (CGR) are dominated by land-atmosphere carbon fluxes in the tropics, providing an opportunity to explore land carbon-climate interactions3-6. It is thought that variations in CGR are largely controlled by temperature7-10 but there is also evidence for a tight coupling between water availability and CGR11. Here, we use a record of global atmospheric CO2, terrestrial water storage and precipitation data to investigate changes in the interannual relationship between tropical land climate conditions and CGR under a changing climate. We find that the interannual relationship between tropical water availability and CGR became increasingly negative during 1989-2018 compared to 1960-1989. This could be related to spatiotemporal changes in tropical water availability anomalies driven by shifts in El Niño/Southern Oscillation teleconnections, including declining spatial compensatory water effects9. We also demonstrate that most state-of-the-art coupled Earth System and Land Surface models do not reproduce the intensifying water-carbon coupling. Our results indicate that tropical water availability is increasingly controlling the interannual variability of the terrestrial carbon cycle and modulating tropical terrestrial carbon-climate feedbacks.

Identifying the thresholds of drought that, if crossed, suppress vegetation functioning is vital for accurate quantification of how land ecosystems respond to climate variability and change. We present a globally applicable framework to identify drought thresholds for vegetation responses to different levels of known soil-moisture deficits using four remotely sensed vegetation proxies spanning 2001-2018. The thresholds identified represent critical inflection points for changing vegetation responses from highly resistant to highly vulnerable in response to drought stress, and as a warning signal for substantial vegetation impacts. Drought thresholds varied geographically, with much lower percentiles of soil-moisture anomalies in vegetated areas covered by more forests, corresponding to a comparably stronger capacity to mitigate soil water deficit stress in forested ecosystems. Generally, those lower thresholds are detected in more humid climates. State-of-the-art land models, however, overestimated thresholds of soil moisture (i.e. overestimating drought impacts), especially in more humid areas with higher forest covers and arid areas with few forest covers. Based on climate model projections, we predict that the risk of vegetation damage will increase by the end of the twenty-first century in some hotspots like East Asia, Europe, Amazon, southern Australia and eastern and southern Africa. Our data-based results will inform projections on future drought impacts on terrestrial ecosystems and provide an effective tool for drought management.

Abstract Earth System Models (ESMs) continue to diagnose a wide range of carbon budgets for each level of global warming. Here, we present emergent constraints on the carbon budget as a function of global warming, which combine the available ESM historical simulations and future projections for a range of scenarios, with observational estimates of global warming and anthropogenic CO2 emissions to the present day. We estimate mean and likely ranges for cumulative carbon budgets for the Paris targets of 1.5 °C and 2 °C of global warming of 812 [691, 933] PgC and 1048 [881, 1216] PgC, which are more than 10% larger than the ensemble mean values from the CMIP6 models. The linearity between cumulative emissions and global warming is found to be maintained at least until 4 °C, and is consistent with an effective Transient Climate Response to Emissions (eTCRE) of 2.1 [1.8, 2.6] °C/1000PgC, from a global warming of 1.2 °C onwards.

Abstract Global climate change is often thought of as a steady and approximately predictable physical response to increasing forcings, which then requires commensurate adaptation. But adaptation has practical, cultural and biological limits, and climate change may pose unanticipated global hazards, sudden changes or other surprises–as may societal adaptation and mitigation responses. These poorly known factors could substantially affect the urgency of mitigation as well as adaptation decisions. We outline a strategy for better accommodating these challenges by making climate science more integrative, in order to identify and quantify known and novel physical risks including those arising from interactions with ecosystems and society. We need to do this even–or especially–when they are highly uncertain, and to explore risks and opportunities associated with mitigation and adaptation responses by engaging across disciplines. We argue that upcoming climate assessments need to be more risk‐aware, and suggest ways of achieving this. These strategies improve the chances of anticipating potential surprises and identifying and communicating “safe landing” pathways that meet UN Sustainable Development Goals and guide humanity toward a better future.

ABSTRACTClimate change jeopardizes human health, global biodiversity, and sustainability of the biosphere. To make reliable predictions about climate change, scientists use Earth system models (ESMs) that integrate physical, chemical, and biological processes occurring on land, the oceans, and the atmosphere. Although critical for catalyzing coupled biogeochemical processes, microorganisms have traditionally been left out of ESMs. Here, we generate a “top 10” list of priorities, opportunities, and challenges for the explicit integration of microorganisms into ESMs. We discuss the need for coarse-graining microbial information into functionally relevant categories, as well as the capacity for microorganisms to rapidly evolve in response to climate-change drivers. Microbiologists are uniquely positioned to collect novel and valuable information necessary for next-generation ESMs, but this requires data harmonization and transdisciplinary collaboration to effectively guide adaptation strategies and mitigation policy.

Abstract The Amazon is the largest continuous tropical forest in the world and plays a key role in the global carbon cycle. Human-induced disturbances and climate change have impacted the Amazon carbon balance. Here we conduct a comprehensive synthesis of existing state-of-the-art estimates of the contemporary land carbon fluxes in the Amazon using a set of bottom-up methods (i.e., dynamic vegetation models and bookkeeping models) and a top-down inversion (atmospheric inversion model) over the Brazilian Amazon and the whole Biogeographical Amazon domain. Over the whole biogeographical Amazon region bottom-up methodologies suggest a small average carbon sink over 2010-2020, in contrast to a small carbon source simulated by top-down inversion (2010-2018). However, these estimates are not significantly different from one another when accounting for their large individual uncertainties, highlighting remaining knowledge gaps, and the urgent need to reduce such uncertainties. Nevertheless, both methodologies agreed that the Brazilian Amazon has been a net carbon source during recent climate extremes and that the south-eastern Amazon was a net land carbon source over the whole study period (2010-2020). Overall, our results point to increasing human-induced disturbances (deforestation and forest degradation by wildfires) and reduction in the old-growth forest sink during drought.

The main contributor to the greenhouse gas (GHG) footprint of the cement industry is the decomposition of alkaline carbonates during clinker production. However, systematic accounts for the reverse of this process – namely carbonation of calcium oxide and other alkaline oxides and/or hydroxides within cement materials during cements' life cycles – have only recently been undertaken. Here, adopting a comprehensive analytical model, we provide the most updated estimates of CO2 uptake by cement carbonation. The accumulated amount of global CO2 uptake by cements produced from 1930 to 2021 is estimated to be 22.9 Gt CO2 (95 % confidence interval, CI: 19.6–26.6 Gt CO2). This amount includes the CO2 uptake by concrete, mortar, construction waste and kiln dust, accounting for 30.1 %, 58.5 %, 4.0 % and 7.1 % respectively. The cumulative carbon uptake by cement materials from 1930 to 2021 offsets 55.1 % of the emissions from cement production (41.6 Gt CO2, 95 % CI: 38.7–47.2 Gt CO2) over the same period, with the greater part coming from mortar (58.5 % of the total uptake). China has the highest cement carbon uptake, with cumulative carbonation of 7.06 Gt CO2 (95 % CI: 5.22–9.44 Gt CO2) since 1930. In addition, the carbon uptake amounts of the USA, EU, India and the rest of the world took 5.0 %, 23.2 %, 5.6 % and 34.8 % separately. As a result of rapidly increased production in recent years, over three-quarters of the cement carbon uptake has occurred since 1990. Additionally, our results show little impact by the COVID-19 pandemic on cement production and use, with carbon uptake reaching about 0.92 Gt CO2 (95 % CI: 0.78–1.10 Gt CO2) in 2020 and 0.96 Gt CO2 (95 % CI: 0.81–1.15 Gt CO2) in 2021. Our uniformly formatted and most updated cement uptake inventories provide coherent data-based support for including cement carbon uptake into future carbon budgets from the local to global scale. The latest version contains the uptake data till 2021, showing the global uptake's increasing pattern and offering more usable and relevant data for evaluating cement's carbon uptake capacity. All the data described in this study are accessible at https://doi.org/10.5281/zenodo.7516373 (Bing et al., 2023).

Abstract A fraction of CO2 uptake by terrestrial ecosystems is exported as organic carbon (C) through the terrestrial‐aquatic continuum. This translocated C plays a significant role in the terrestrial C balance; however, obtaining global assessments remains challenging due to the predominant reliance on empirical approaches. Leaching of dissolved organic C (DOC) from soils to rivers represents an important fraction of this C export and is assumed to drive a large proportion of the net‐heterotrophy of river systems and the related CO2 emissions. Using the model JULES‐DOCM, we projected DOC leaching trends over the 21st century based on three scenarios with high (RCP 2.6), intermediate (RCP 4.5), and low (RCP 8.5) climate mitigation efforts. The RCP 8.5 scenario led to the largest DOC leaching increase of +42% to 395 Tg C yr−1 by 2100. In comparison, RCP 2.6 and RCP 4.5 led to increases of 10% and 21%, respectively. Under RCP 8.5, the sub‐tropical zone showed the highest relative increase of 50% above current levels. In the boreal and tropical zones, the simulations revealed similar increases of 48% and 41%, respectively. However, given the pre‐eminence of the tropics in DOC leaching, the absolute increment is markedly substantial from this region (+59 Tg C yr−1). The temperate zone displayed the lowest relative increase with 35%. Our analysis identified the rising atmospheric CO2 concentration and its fertilizing effect on terrestrial NPP as the main reason for the future increase in DOC leaching.

Quantification of land surface–atmosphere fluxes of carbon dioxide (CO2) and their trends and uncertainties is essential for monitoring progress of the EU27+UK bloc as it strives to meet ambitious targets determined by both international agreements and internal regulation. This study provides a consolidated synthesis of fossil sources (CO2 fossil) and natural (including formally managed ecosystems) sources and sinks over land (CO2 land) using bottom-up (BU) and top-down (TD) approaches for the European Union and United Kingdom (EU27+UK), updating earlier syntheses (Petrescu et al., 2020, 2021). Given the wide scope of the work and the variety of approaches involved, this study aims to answer essential questions identified in the previous syntheses and understand the differences between datasets, particularly for poorly characterized fluxes from managed and unmanaged ecosystems. The work integrates updated emission inventory data, process-based model results, data-driven categorical model results, and inverse modeling estimates, extending the previous period 1990–2018 to the year 2020 to the extent possible. BU and TD products are compared with the European national greenhouse gas inventory (NGHGI) reported by parties including the year 2019 under the United Nations Framework Convention on Climate Change (UNFCCC). The uncertainties of the EU27+UK NGHGI were evaluated using the standard deviation reported by the EU member states following the guidelines of the Intergovernmental Panel on Climate Change (IPCC) and harmonized by gap-filling procedures. Variation in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), originate from within-model uncertainty related to parameterization as well as structural differences between models. By comparing the NGHGI with other approaches, key sources of differences between estimates arise primarily in activities. System boundaries and emission categories create differences in CO2 fossil datasets, while different land use definitions for reporting emissions from land use, land use change, and forestry (LULUCF) activities result in differences for CO2 land. The latter has important consequences for atmospheric inversions, leading to inversions reporting stronger sinks in vegetation and soils than are reported by the NGHGI. For CO2 fossil emissions, after harmonizing estimates based on common activities and selecting the most recent year available for all datasets, the UNFCCC NGHGI for the EU27+UK accounts for 926 ± 13 Tg C yr−1, while eight other BU sources report a mean value of 948 [937,961] Tg C yr−1 (25th, 75th percentiles). The sole top-down inversion of fossil emissions currently available accounts for 875 Tg C in this same year, a value outside the uncertainty of both the NGHGI and bottom-up ensemble estimates and for which uncertainty estimates are not currently available. For the net CO2 land fluxes, during the most recent 5-year period including the NGHGI estimates, the NGHGI accounted for −91 ± 32 Tg C yr−1, while six other BU approaches reported a mean sink of −62 [-117,-49] Tg C yr−1, and a 15-member ensemble of dynamic global vegetation models (DGVMs) reported −69 [-152,-5] Tg C yr−1. The 5-year mean of three TD regional ensembles combined with one non-ensemble inversion of −73 Tg C yr−1 has a slightly smaller spread (0th–100th percentiles of [-135,+45] Tg C yr−1), and it was calculated after removing net land–atmosphere CO2 fluxes caused by lateral transport of carbon (crop trade, wood trade, river transport, and net uptake from inland water bodies), resulting in increased agreement with the NGHGI and bottom-up approaches. Results at the category level (Forest Land, Cropland, Grassland) generally show good agreement between the NGHGI and category-specific models, but results for DGVMs are mixed. Overall, for both CO2 fossil and net CO2 land fluxes, we find that current independent approaches are consistent with the NGHGI at the scale of the EU27+UK. We conclude that CO2 emissions from fossil sources have decreased over the past 30 years in the EU27+UK, while land fluxes are relatively stable: positive or negative trends larger (smaller) than 0.07 (−0.61) Tg C yr−2 can be ruled out for the NGHGI. In addition, a gap on the order of 1000 Tg C yr−1 between CO2 fossil emissions and net CO2 uptake by the land exists regardless of the type of approach (NGHGI, TD, BU), falling well outside all available estimates of uncertainties. However, uncertainties in top-down approaches to estimate CO2 fossil emissions remain uncharacterized and are likely substantial, in addition to known uncertainties in top-down estimates of the land fluxes. The data used to plot the figures are available at https://doi.org/10.5281/zenodo.8148461 (McGrath et al., 2023).

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.

Intergovernmental Panel on Climate Change (IPCC) assessments are the trusted source of scientific evidence for climate negotiations taking place under the United Nations Framework Convention on Climate Change (UNFCCC), including the first global stocktake under the Paris Agreement that will conclude at COP28 in December 2023. Evidence-based decision-making needs to be informed by up-to-date and timely information on key indicators of the state of the climate system and of the human influence on the global climate system. However, successive IPCC reports are published at intervals of 5–10 years, creating potential for an information gap between report cycles. We follow methods as close as possible to those used in the IPCC Sixth Assessment Report (AR6) Working Group One (WGI) report. We compile monitoring datasets to produce estimates for key climate indicators related to forcing of the climate system: emissions of greenhouse gases and short-lived climate forcers, greenhouse gas concentrations, radiative forcing, surface temperature changes, the Earth's energy imbalance, warming attributed to human activities, the remaining carbon budget, and estimates of global temperature extremes. The purpose of this effort, grounded in an open data, open science approach, is to make annually updated reliable global climate indicators available in the public domain (https://doi.org/10.5281/zenodo.8000192, Smith et al., 2023a). As they are traceable to IPCC report methods, they can be trusted by all parties involved in UNFCCC negotiations and help convey wider understanding of the latest knowledge of the climate system and its direction of travel. The indicators show that human-induced warming reached 1.14 [0.9 to 1.4] ∘C averaged over the 2013–2022 decade and 1.26 [1.0 to 1.6] ∘C in 2022. Over the 2013–2022 period, human-induced warming has been increasing at an unprecedented rate of over 0.2 ∘C per decade. This high rate of warming is caused by a combination of greenhouse gas emissions being at an all-time high of 54 ± 5.3 GtCO2e over the last decade, as well as reductions in the strength of aerosol cooling. Despite this, there is evidence that increases in greenhouse gas emissions have slowed, and depending on societal choices, a continued series of these annual updates over the critical 2020s decade could track a change of direction for human influence on climate.

As the focus of climate policy shifts from pledges to implementation, there is a growing need to track progress on climate change mitigation at the country level, particularly for the land-use sector. Despite new tools and models providing unprecedented monitoring opportunities, striking differences remain in estimations of anthropogenic land-use CO2 fluxes between, on the one hand, the national greenhouse gas inventories (NGHGIs) used to assess compliance with national climate targets under the Paris Agreement and, on the other hand, the Global Carbon Budget and Intergovernmental Panel on Climate Change (IPCC) assessment reports, both based on global bookkeeping models (BMs). Recent studies have shown that these differences are mainly due to inconsistent definitions of anthropogenic CO2 fluxes in managed forests. Countries assume larger areas of forest to be managed than BMs do, due to a broader definition of managed land in NGHGIs. Additionally, the fraction of the land sink caused by indirect effects of human-induced environmental change (e.g. fertilisation effect on vegetation growth due to increased atmospheric CO2 concentration) on managed lands is treated as non-anthropogenic by BMs but as anthropogenic in most NGHGIs. We implement an approach that adds the CO2 sink caused by environmental change in countries' managed forests (estimated by 16 dynamic global vegetation models, DGVMs) to the land-use fluxes from three BMs. This sum is conceptually more comparable to NGHGIs and is thus expected to be quantitatively more similar. Our analysis uses updated and more comprehensive data from NGHGIs than previous studies and provides model results at a greater level of disaggregation in terms of regions, countries and land categories (i.e. forest land, deforestation, organic soils, other land uses). Our results confirm a large difference (6.7 GtCO2 yr−1) in global land-use CO2 fluxes between the ensemble mean of the BMs, which estimate a source of 4.8 GtCO2 yr−1 for the period 2000–2020, and NGHGIs, which estimate a sink of −1.9 GtCO2 yr−1 in the same period. Most of the gap is found on forest land (3.5 GtCO2 yr−1), with differences also for deforestation (2.4 GtCO2 yr−1), for fluxes from other land uses (1.0 GtCO2 yr−1) and to a lesser extent for fluxes from organic soils (0.2 GtCO2 yr−1). By adding the DGVM ensemble mean sink arising from environmental change in managed forests (−6.4 GtCO2 yr−1) to BM estimates, the gap between BMs and NGHGIs becomes substantially smaller both globally (residual gap: 0.3 GtCO2 yr−1) and in most regions and countries. However, some discrepancies remain and deserve further investigation. For example, the BMs generally provide higher emissions from deforestation than NGHGIs and, when adjusted with the sink in managed forests estimated by DGVMs, yield a sink that is often greater than NGHGIs. In summary, this study provides a blueprint for harmonising the estimations of anthropogenic land-use fluxes, allowing for detailed comparisons between global models and national inventories at global, regional and country levels. This is crucial to increase confidence in land-use emissions estimates, support investments in land-based mitigation strategies and assess the countries' collective progress under the Global Stocktake of the Paris Agreement. Data from this study are openly available online via the Zenodo portal (Grassi et al., 2023) at https://doi.org/10.5281/zenodo.7650360.

Abstract Anthropogenic emissions of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) have made significant contributions to global warming since the pre-industrial period and are therefore targeted in international climate policy. There is substantial interest in tracking and apportioning national contributions to climate change and informing equitable commitments to decarbonisation. Here, we introduce a new dataset of national contributions to global warming caused by historical emissions of carbon dioxide, methane, and nitrous oxide during the years 1851–2021, which are consistent with the latest findings of the IPCC. We calculate the global mean surface temperature response to historical emissions of the three gases, including recent refinements which account for the short atmospheric lifetime of CH4. We report national contributions to global warming resulting from emissions of each gas, including a disaggregation to fossil and land use sectors. This dataset will be updated annually as national emissions datasets are updated.

The remaining carbon budget represents the total amount of CO2 that can still be emitted in the future while limiting global warming to a given temperature target. Remaining carbon budget estimates range widely, however, and this uncertainty can be used to either trivialize the most ambitious mitigation targets by characterizing them as impossible, or to argue that there is ample time to allow for a gradual transition to a low-carbon economy. Neither of these extremes is consistent with our best understanding of the policy implications of remaining carbon budgets. Understanding the scientific and socio-economic uncertainties affecting the size of the remaining carbon budgets, as well as the methodological choices and assumptions that underlie their calculation, is essential before applying them as a policy tool. Here we provide recommendations on how to calculate remaining carbon budgets in a traceable and transparent way, and discuss their uncertainties and implications for both international and national climate policies.

Carbon cycle feedbacks represent large uncertainties in climate change projections, and the response of soil carbon to climate change contributes the greatest uncertainty to this. Future changes in soil carbon depend on changes in litter and root inputs from plants and especially on reductions in the turnover time of soil carbon (τs) with warming. An approximation to the latter term for the top one metre of soil (ΔCs,τ) can be diagnosed from projections made with the CMIP6 and CMIP5 Earth System Models (ESMs), and is found to span a large range even at 2 °C of global warming (-196 ± 117 PgC). Here, we present a constraint on ΔCs,τ, which makes use of current heterotrophic respiration and the spatial variability of τs inferred from observations. This spatial emergent constraint allows us to halve the uncertainty in ΔCs,τ at 2 °C to -232 ± 52 PgC.

Results from the fully and biogeochemically coupled simulations in which CO2 increases at a rate of 1%yr-1 (1pctCO2) from its preindustrial value are analyzed to quantify the magnitude of carbon-concentration and carbon-climate feedback parameters which measure the response of ocean and terrestrial carbon pools to changes in atmospheric CO2 concentration and the resulting change in global climate, respectively. The results are based on 11 comprehensive Earth system models from the most recent uncertain over land than over ocean as has been seen in existing studies. These values and their spread from 11 CMIP6 models have not changed significantly compared to CMIP5 models. The absolute values of feedback parameters are lower for land with models that include a representation of nitrogen cycle. The transient climate response to cumulative emissions (TCRE) from the 11 CMIP6 models considered here is 1.77±0.37 ° C EgC-1 and is similar to that found in CMIP5 models (1.63±0.48 °C EgC-1) but with somewhat reduced model spread. The expressions for feedback parameters based on the fully and biogeochemically coupled configurations of the 1pctCO2 simulation are simplified when the small temperature change in the biogeochemically coupled simulation is ignored. Decomposition of the terms of these simplified expressions for the feedback parameters is used to gain insight into the reasons for differing responses among ocean and land carbon cycle models.

Results from the fully and biogeochemically coupled simulations in which CO2 increases at a rate of 1%yr-1 (1pctCO2) from its preindustrial value are analyzed to quantify the magnitude of carbon-concentration and carbon-climate feedback parameters which measure the response of ocean and terrestrial carbon pools to changes in atmospheric CO2 concentration and the resulting change in global climate, respectively. The results are based on 11 comprehensive Earth system models from the most recent uncertain over land than over ocean as has been seen in existing studies. These values and their spread from 11 CMIP6 models have not changed significantly compared to CMIP5 models. The absolute values of feedback parameters are lower for land with models that include a representation of nitrogen cycle. The transient climate response to cumulative emissions (TCRE) from the 11 CMIP6 models considered here is 1.77±0.37 ° C EgC-1 and is similar to that found in CMIP5 models (1.63±0.48 °C EgC-1) but with somewhat reduced model spread. The expressions for feedback parameters based on the fully and biogeochemically coupled configurations of the 1pctCO2 simulation are simplified when the small temperature change in the biogeochemically coupled simulation is ignored. Decomposition of the terms of these simplified expressions for the feedback parameters is used to gain insight into the reasons for differing responses among ocean and land carbon cycle models.

The impact of land-use and cover-change (LUCC) on ecosystem carbon stock in China is poorly known due to large biases in existing databases. Here the authors develop a new LUCC database with corrected false signals and reveal that forest expansion is the dominant driver of China’s recent carbon sink.

The global net land sink is relatively well constrained. However, the responsible drivers and above/below-ground partitioning are highly uncertain. Model issues regarding turnover of individual plant and soil components are responsible.

Abstract Significant land greening since the 1980s has been detected through satellite observation, forest inventory, and Earth system modeling. However, whether and to what extent global land greening enhances ecosystem carbon stock remains uncertain. Here, using 40 global models, we first detected a positive correlation between the terrestrial ecosystem carbon stock and leaf area index (LAI) over time. Then, we diagnose the source of uncertainty of simulated the sensitivities of ecosystem carbon stock to LAI based on a traceability analysis. We found that the sensitivity of gross primary productivity (GPP) to LAI is the largest contributor to the model uncertainty in more than 60% of the vegetated grids. Using the ensemble of four long‐term global data sets of GPP and three satellite LAI products from 1982 to 2014, we provided an emergent constraint on the ecosystem carbon stock increase as 0.75 ± 0.46 kg C m−2 per unit LAI over global land areas. Furthermore, the biome‐based results reveal that the tropical forest regions have the highest inter‐model variation and model bias. Overall, this study identifies the uncertainty source and provides constrained estimates of the greening effect on ecosystem carbon stock at the global scale.

Biological nitrogen fixation is the main source of new nitrogen into natural terrestrial ecosystems and consequently in the nitrogen cycle in many earth system models. Representation of biological nitrogen fixation varies, and because of the tight coupling between the carbon and nitrogen cycles, previous studies have shown that this affects projected changes in net primary productivity. Here we present the first assessment of the performance of biological nitrogen fixation in models contributing to CMIP6 compared to observed and observation-constrained estimates of biological nitrogen fixation. We find that 9 out of 10 models represent global total biological nitrogen fixation within the uncertainty in recent global estimates. However, 6 out of 10 models overestimate the amount of fixation in the tropics and therefore the extent of the latitudinal gradient in the global distribution. For the SSP3-7.0 scenario of future climate change, models project increases in fixation over the 21st century of up to 80 %. However, while the historical range of biological nitrogen fixation amongst models is large (up to 140 kg N ha−1 yr−1 at the grid cell level and 43–208 Tg N yr−1 globally) this does not have explanatory power for variations within the model ensemble of net primary productivity or the coupled nitrogen–carbon cycle. Models with shared structures can have significant variations in both biological nitrogen fixation and other parts of the nitrogen cycle without differing in their net primary productivity. This points to systematic challenges in the representation of carbon–nitrogen model structures and the severe limitations of models using net primary productivity or evapotranspiration to project the biological nitrogen fixation response to elevated atmospheric carbon dioxide or other environmental changes.

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'.

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 methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) 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) is estimated with global ocean biogeochemistry models and observation-based data products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. 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 first time, an approach is shown to reconcile the difference in our ELUC estimate with the one from national greenhouse gas inventories, supporting the assessment of collective countries' climate progress. For the year 2020, EFOS declined by 5.4 % relative to 2019, with fossil 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 of 10.2 ± 0.8 GtC yr−1 (37.4 ± 2.9 GtCO2). Also, for 2020, 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 SLAND was 2.9 ± 1 GtC yr−1, with a BIM of −0.8 GtC yr−1. The global atmospheric CO2 concentration averaged over 2020 reached 412.45 ± 0.1 ppm. Preliminary data for 2021 suggest a rebound in EFOS relative to 2020 of +4.8 % (4.2 % to 5.4 %) globally. Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2020, but discrepancies of up to 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 (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 the methods and datasets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this dataset (Friedlingstein et al., 2020, 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-2021 (Friedlingstein et al., 2021).

In many regions of the world, frequent and continual dry spells are exacerbating drought conditions, which have severe impacts on vegetation biomes. Vegetation in southern Africa is among the most affected by drought. Here, we assessed the spatiotemporal characteristics of meteorological drought in southern Africa using the standardized precipitation evapotranspiration index (SPEI) over a 30-year period (1982–2011). The severity and the effects of droughts on vegetation productiveness were examined at different drought timescales (1- to 24-month timescales). In this study, we characterized vegetation using the leaf area index (LAI) after evaluating its relationship with the normalized difference vegetation index (NDVI). Correlating the LAI with the SPEI, we found that the LAI responds strongly (r=0.6) to drought over the central and southeastern parts of the region, with weaker impacts (r) over parts of Madagascar, Angola, and the western parts of South Africa. Furthermore, the latitudinal distribution of LAI responses to drought indicates a similar temporal pattern but different magnitudes across timescales. The results of the study also showed that the seasonal response across different southern African biomes varies in magnitude and occurs mostly at shorter to intermediate timescales. The semi-desert biome strongly correlates (r=0.95) to drought as characterized by the SPEI at a 6-month timescale in the MAM (March–May; summer) season, while the tropical forest biome shows the weakest response (r=0.35) at a 6-month timescale in the DJF (December–February; hot and rainy) season. In addition, we found that the spatial pattern of change of LAI and SPEI are mostly similar during extremely dry and wet years, with the highest anomaly observed in the dry year of 1991, and we found different temporal variability in global and regional responses across different biomes. We also examined how well an ensemble of state-of-the-art dynamic global vegetation models (DGVMs) simulate the LAI and its response to drought. The spatial and seasonal response of the LAI to drought is mostly overestimated in the DGVM multimodel ensemble compared to the response calculated for the observation-based data. The correlation coefficient values for the multimodel ensemble are as high as 0.76 (annual) over South Africa and 0.98 in the MAM season over the temperate grassland biome. Furthermore, the DGVM model ensemble shows positive biases (3 months or longer) in the simulation of spatial distribution of drought timescales and overestimates the seasonal distribution timescales. The results of this study highlight the areas to target for further development of DGVMs and can be used to improve the models' capability in simulating the drought–vegetation relationship.

An integrated understanding of the biogeochemical consequences of climate extremes and land use changes is needed to constrain land-surface feedbacks to atmospheric CO2 from associated climate change. Past assessments of the global carbon balance have shown particularly high uncertainty in Southeast Asia. Here, we use a combination of model ensembles to show that intensified land use change made Southeast Asia a strong source of CO2 from the 1980s to 1990s, whereas the region was close to carbon neutral in the 2000s due to an enhanced CO2 fertilization effect and absence of moderate-to-strong El Niño events. Our findings suggest that despite ongoing deforestation, CO2 emissions were substantially decreased during the 2000s, largely owing to milder climate that restores photosynthetic capacity and suppresses peat and deforestation fire emissions. The occurrence of strong El Niño events after 2009 suggests that the region has returned to conditions of increased vulnerability of carbon stocks.