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Non-technical summary: We identify a set of essential recent advances in climate change research with high policy relevance, across natural and social sciences: (1) looming inevitability and implications of overshooting the 1.5°C warming limit, (2) urgent need for a rapid and managed fossil fuel phase-out, (3) challenges for scaling carbon dioxide removal, (4) uncertainties regarding the future contribution of natural carbon sinks, (5) intertwinedness of the crises of biodiversity loss and climate change, (6) compound events, (7) mountain glacier loss, (8) human immobility in the face of climate risks, (9) adaptation justice, and (10) just transitions in food systems. Technical summary The IPCC Assessment Reports offer the scientific foundation for international climate negotiations and constitute an unmatched resource for climate change researchers. However, the assessment cycles take multiple years. As a contribution to cross- and interdisciplinary understanding across diverse climate change research communities, we have streamlined an annual process to identify and synthesise essential research advances. We collected input from experts on different fields using an online questionnaire and prioritised a set of ten key research insights with high policy relevance. This year we focus on: (1) looming overshoot of the 1.5°C warming limit, (2) urgency of phasing-out fossil fuels, (3) challenges for scaling carbon dioxide removal, (4) uncertainties regarding the future of natural carbon sinks, (5) need for join governance of biodiversity loss and climate change, (6) advances in the science of compound events, (7) mountain glacier loss, (8) human immobility in the face of climate risks, (9) adaptation justice, and (10) just transitions in food systems. We first present a succinct account of these Insights, reflect on their policy implications, and offer an integrated set of policy relevant messages. This science synthesis and science communication effort is also the basis for a report targeted to policymakers as a contribution to elevate climate science every year, in time for the UNFCCC COP. Social media summary We highlight recent and policy-relevant advances in climate change research - with input from more than 200 experts 1.

We explore the ability of the atmospheric CO2 record since 1900 to constrain the source of CO2 from land use and land cover change (hereafter "land use"), taking account of uncertainties in other terms in the global carbon budget. We find that the atmospheric constraint favors land use CO2 flux estimates with lower decadal variability and can identify potentially erroneous features, such as emission peaks around 1960 and after 2000, in some published estimates. Furthermore, we resolve an offset in the global carbon budget that is most plausibly attributed to the land use flux. This correction shifts the mean land use flux since 1900 across 20 published estimates down by 0.35 PgC year-1 to 1.04 ± 0.57 PgC year-1 , which is within the range but at the low end of these estimates. We show that the atmospheric CO2 record can provide insights into the time history of the land use flux that may reduce uncertainty in this term and improve current understanding and projections of the global carbon cycle.

This corrigendum resolves an error in figure 17 and clarifies the scope of the cement sector in figure 2. Figure 17 in the original published manuscript depicts a Kaya identity for the agriculture, forestry and other land uses (AFOLU) sector. We unintentionally excluded land-use CO2 emissions from total greenhouse gas (GHG) emissions in this identity, and depicted only agricultural GHG emissions.

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.

Global greenhouse gas (GHG) emissions can be traced to five economic sectors: energy, industry, buildings, transport and AFOLU (agriculture, forestry and other land uses). In this topical review, we synthesise the literature to explain recent trends in global and regional emissions in each of these sectors. To contextualise our review, we present estimates of GHG emissions trends by sector from 1990 to 2018, describing the major sources of emissions growth, stability and decline across ten global regions. Overall, the literature and data emphasise that progress towards reducing GHG emissions has been limited. The prominent global pattern is a continuation of underlying drivers with few signs of emerging limits to demand, nor of a deep shift towards the delivery of low and zero carbon services across sectors. We observe a moderate decarbonisation of energy systems in Europe and North America, driven by fuel switching and the increasing penetration of renewables. By contrast, in rapidly industrialising regions, fossil-based energy systems have continuously expanded, only very recently slowing down in their growth. Strong demand for materials, floor area, energy services and travel have driven emissions growth in the industry, buildings and transport sectors, particularly in Eastern Asia, Southern Asia and South-East Asia. An expansion of agriculture into carbon-dense tropical forest areas has driven recent increases in AFOLU emissions in Latin America, South-East Asia and Africa. Identifying, understanding, and tackling the most persistent and climate-damaging trends across sectors is a fundamental concern for research and policy as humanity treads deeper into the Anthropocene.

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 climate mitigation potential of terrestrial carbon dioxide removal (tCDR) methods depends critically on the timing and magnitude of their implementation. In our study, we introduce different measures of efficiency to evaluate the carbon removal potential of afforestation and reforestation (AR) and bioenergy with carbon capture and storage (BECCS) under the low-emission scenario SSP1-2.6 and in the same area. We define efficiency as the potential to sequester carbon in the biosphere in a specific area or store carbon in geological reservoirs or woody products within a certain time. In addition to carbon capture and storage (CCS), we consider the effects of fossil fuel substitution (FFS) through the usage of bioenergy for energy production, which increases the efficiency through avoided CO2 emissions. These efficiency measures reflect perspectives regarding climate mitigation, carbon sequestration, land availability, spatiotemporal dynamics, and the technological progress in FFS and CCS. We use the land component JSBACH3.2 of the Max Planck Institute Earth System Model (MPI-ESM) to calculate the carbon sequestration potential in the biosphere using an updated representation of second-generation bioenergy plants such as Miscanthus. Our spatially explicit modeling results reveal that, depending on FFS and CCS levels, BECCS sequesters 24–158 GtC by 2100, whereas AR methods sequester around 53 GtC on a global scale, with BECCS having an advantage in the long term. For our specific setup, BECCS has a higher potential in the South American grasslands and southeast Africa, whereas AR methods are more suitable in southeast China. Our results reveal that the efficiency of BECCS to sequester carbon compared to "nature-based solutions" like AR will depend critically on the upscaling of CCS facilities, replacing fossil fuels with bioenergy in the future, the time frame, and the location of tCDR deployment. [ABSTRACT FROM AUTHOR]

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 synthesise datasets and methodologies 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) 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 f CO2-products. The terrestrial CO2 sink (SLAND) 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 (BIM), a measure of imperfect data and incomplete understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2023, EFOS 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), ELUC 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, GATM was 5.9 ± 0.2 GtC yr-1 (2.79 ± 0.1 ppm yr-1), SOCEAN was 2.9 ± 0.4 GtC yr-1 and SLAND was 2.3 ± 1.0 GtC yr-1, with a near zero BIM (-0.02 GtC yr-1). The global atmospheric CO2 concentration averaged over 2023 reached 419.3 ± 0.1 ppm. Preliminary data for 2024, suggest an increase in EFOS relative to 2023 of +0.8 % (-0.3 % to 1.9 %) globally, and atmospheric CO2 concentration increased by 2.8 ppm reaching 422.5 ppm, 52 % above 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 1959–2023, 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: (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 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). [ABSTRACT FROM AUTHOR]

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'.

Historically, human uses of land have transformed and fragmented ecosystems.sup.1,2, degraded biodiversity.sup.3,4, disrupted carbon and nitrogen cycles.sup.5,6 and added prodigious quantities of greenhouse gases (GHGs) to the atmosphere.sup.7,8. However, in contrast to fossil-fuel carbon dioxide (CO.sub.2) emissions, trends and drivers of GHG emissions from land management and land-use change (together referred to as 'land-use emissions') have not been as comprehensively and systematically assessed. Here we present country-, process-, GHG- and product-specific inventories of global land-use emissions from 1961 to 2017, we decompose key demographic, economic and technical drivers of emissions and we assess the uncertainties and the sensitivity of results to different accounting assumptions. Despite steady increases in population (+144 per cent) and agricultural production per capita (+58 per cent), as well as smaller increases in emissions per land area used (+8 per cent), decreases in land required per unit of agricultural production (-70 per cent) kept global annual land-use emissions relatively constant at about 11 gigatonnes CO.sub.2-equivalent until 2001. After 2001, driven by rising emissions per land area, emissions increased by 2.4 gigatonnes CO.sub.2-equivalent per decade to 14.6 gigatonnes CO.sub.2-equivalent in 2017 (about 25 per cent of total anthropogenic GHG emissions). Although emissions intensity decreased in all regions, large differences across regions persist over time. The three highest-emitting regions (Latin America, Southeast Asia and sub-Saharan Africa) dominate global emissions growth from 1961 to 2017, driven by rapid and extensive growth of agricultural production and related land-use change. In addition, disproportionate emissions are related to certain products: beef and a few other red meats supply only 1 per cent of calories worldwide, but account for 25 per cent of all land-use emissions. Even where land-use change emissions are negligible or negative, total per capita CO.sub.2-equivalent land-use emissions remain near 0.5 tonnes per capita, suggesting the current frontier of mitigation efforts. Our results are consistent with existing knowledge--for example, on the role of population and economic growth and dietary choice--but provide additional insight into regional and sectoral trends. Trends in the rate of region- and sector-specific land-use greenhouse gas emissions in 1961-2017 show an acceleration of about 20% per decade after 2001., Author(s): Chaopeng Hong [sup.1] , Jennifer A. Burney [sup.2] , Julia Pongratz [sup.3] [sup.4] , Julia E. M. S. Nabel [sup.4] , Nathaniel D. Mueller [sup.5] [sup.6] , Robert B. [...]

Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the following questions. (1) What are the effects of LULCC on climate and biogeochemical cycling (past-future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy, and are there regional land-management strategies with the promise to help mitigate climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land use, the unique impacts of land-cover change vs. land-management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent to which impacts of enhanced CO2 concentrations on plant photosynthesis are modulated by past and future land use.LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use data set, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to LULCC. In this paper, we describe LUMIP activity (2), i.e., the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes a two-phase experimental design. Phase one features idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential land-cover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible and clearly report how the model experiments were executed.

Coordinated experimental design and implementation has become a cornerstone of global climate modelling. Model Intercomparison Projects (MIPs) enable systematic and robust analysis of results across many models, by reducing the influence of ad hoc differences in model set-up or experimental boundary conditions. As it enters its 6th phase, the Coupled Model Intercomparison Project (CMIP6) has grown significantly in scope with the design and documentation of individual simulations delegated to individual climate science communities. The Coupled Climate-Carbon Cycle Model Intercomparison Project (C4MIP) takes responsibility for design, documentation, and analysis of carbon cycle feedbacks and interactions in climate simulations. These feedbacks are potentially large and play a leading-order contribution in determining the atmospheric composition in response to human emissions of CO2 and in the setting of emissions targets to stabilize climate or avoid dangerous climate change. For over a decade, C4MIP has coordinated coupled climate-carbon cycle simulations, and in this paper we describe the C4MIP simulations that will be formally part of CMIP6. While the climate-carbon cycle community has created this experimental design, the simulations also fit within the wider CMIP activity, conform to some common standards including documentation and diagnostic requests, and are designed to complement the CMIP core experiments known as the Diagnostic, Evaluation and Characterization of Klima (DECK). C4MIP has three key strands of scientific motivation and the requested simulations are designed to satisfy their needs: (1) pre-industrial and historical simulations (formally part of the common set of CMIP6 experiments) to enable model evaluation, (2) idealized coupled and partially coupled simulations with 1% per year increases in CO2 to enable diagnosis of feedback strength and its components, (3) future scenario simulations to project how the Earth system will respond to anthropogenic activity over the 21st century and beyond. This paper documents in detail these simulations, explains their rationale and planned analysis, and describes how to set up and run the simulations. Particular attention is paid to boundary conditions, input data, and requested output diagnostics. It is important that modelling groups participating in C4MIP adhere as closely as possible to this experimental design.

Accounting for carbon fluxes from land use and land cover change (LULCC) generally requires choosing from multiple options of how to attribute the fluxes to regions and to LULCC activities. Applying a newly developed and spatially explicit bookkeeping model BLUE (bookkeeping of land use emissions), we quantify LULCC fluxes and attribute them to land use activities and countries by a range of different accounting methods. We present results with respect to a Kyoto Protocol-like "commitment" accounting period, using land use emissions of 2008-2012 as an example scenario. We assess the effect of accounting methods that vary (1) the temporal evolution of carbon stocks, (2) the state of the carbon stocks at the beginning of the period, (3) the temporal attribution of carbon fluxes during the period, and (4) treatment of LULCC fluxes that occurred prior to the beginning of the period. We show that the methodological choices result in grossly different estimates of carbon fluxes for the different attribution definitions.

Roughly one-third of anthropogenic GHG emissions are caused by agricultural and forestry activities and landuse change (collectively, 'land-use emissions'). Understanding the ultimate drivers of these emissions requires attributing emissions to specific land-use activities and products. Although quantities of land-use emissions are matters of fact, the methodological choices and assumptions required to attribute those emissions to activities and products depend on research goals and data availability. In this review, we explore several possible accounting methods. Our results highlight the sensitivity of accounting to temporal distributions of emissions and the consequences of replacing spatially-explicit data with aggregate proxies such as production or harvested area data. Different accounting options emphasize different causes of land-use emissions (e.g., proximate or indirect drivers of deforestation). To support public policies that effectively balance competing objectives, analysts should carefully consider and communicate implications of accounting choices.

The response of the global climate–carbon-cycle system to anthropogenic perturbations happens differently at different timescales. The unravelling of the memory structure underlying this timescale dependence is a major challenge in climate research. Recently the widely applied α – β – γ framework proposed by to quantify climate–carbon-cycle feedbacks has been generalized to account also for such internal memory. By means of this generalized framework, we investigate the timescale dependence of the airborne fraction for a set of Earth system models that participated in CMIP5 (Coupled Model Intercomparison Project Phase 5). The analysis is based on published simulation data from C 4 MIP-type (Coupled Climate–Carbon Cycle Model Intercomparison) experiments with these models. Independently of the considered scenario, the proposed generalization describes at global scale the reaction of the climate–carbon system to sufficiently weak perturbations. One prediction from this theory is how the timescale-resolved airborne fraction depends on the underlying feedbacks between climate and the carbon cycle. These feedbacks are expressed as timescale-resolved functions depending solely on analogues of the α , β , and γ sensitivities, introduced in the generalized framework as linear response functions. In this way a feedback-dependent quantity (airborne fraction) is predicted from feedback-independent quantities (the sensitivities). This is the key relation underlying our study. As a preparatory step, we demonstrate the predictive power of the generalized framework exemplarily for simulations with the Max Planck Institute (MPI) Earth System Model. The whole approach turns out to be valid for perturbations of up to an about 100 ppm CO 2 rise above the pre-industrial level; beyond this value the response becomes non-linear. By means of the generalized framework we then derive the timescale dependence of the airborne fraction from the underlying climate–carbon-cycle feedbacks for an ensemble of CMIP5 models. Our analysis reveals that for all studied CMIP5 models (1) the total climate–carbon-cycle feedback is negative at all investigated timescales, (2) the airborne fraction generally decreases for increasing timescales, and (3) the land biogeochemical feedback dominates the model spread in the airborne fraction at all these timescales. Qualitatively similar results were previously found by employing the original α – β – γ framework to particular perturbation scenarios, but our study demonstrates that, although obtained from particular scenario simulations, they are characteristics of the coupled climate–carbon-cycle system as such, valid at all considered timescales. These more general conclusions are obtained by accounting for the internal memory of the system as encoded in the generalized sensitivities, which in contrast to the original α , β , and γ are scenario-independent. [ABSTRACT FROM AUTHOR]