Accurate assessment of anthropogenic carbon dioxide (CO₂) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe 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) and terrestrial CO₂ sink (S_LAND) are estimated with global process models constrained by observations. 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 understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2010–2019), E_FOS 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), and E_LUC was 1.6 ± 0.7 GtC yr⁻¹. For the same decade, G_ATM was 5.1 ± 0.02 GtC yr⁻¹ (2.4 ± 0.01 ppm yr⁻¹), S_OCEAN 2.5 ± 0.6 GtC yr⁻¹, and S_LAND 3.4 ± 0.9 GtC yr⁻¹, with a budget imbalance B_IM of −0.1 GtC yr⁻¹ indicating a near balance between estimated sources and sinks over the last decade. For the year 2019 alone, the growth in E_FOS was only about 0.1 % with fossil emissions increasing to 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 E_LUC 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, G_ATM was 5.4 ± 0.2 GtC yr⁻¹ (2.5 ± 0.1 ppm yr⁻¹), S_OCEAN was 2.6 ± 0.6 GtC yr⁻¹, and S_LAND was 3.1 ± 1.2 GtC yr⁻¹, with a B_IM of 0.3 GtC. The global atmospheric CO₂ concentration reached 409.85 ± 0.1 ppm averaged over 2019. Preliminary data for 2020, accounting for the COVID-19-induced changes in emissions, suggest a decrease in E_FOS relative to 2019 of about −7 % (median estimate) based on individual estimates from four studies of −6 %, −7 %, −7 % (−3 % to −11 %), and −13 %. Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2019, but discrepancies of up to 1 GtC yr⁻¹ persist for the representation of semi-decadal variability in CO₂ fluxes. Comparison of estimates from diverse approaches and observations shows (1) no consensus in the mean and trend in land-use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO₂ flux in the northern extra-tropics, and (3) an apparent discrepancy between the different methods for the ocean sink outside the tropics, particularly in the Southern Ocean. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (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).

Government policies during the COVID-19 pandemic have drastically altered patterns of energy demand around the world. Many international borders were closed and populations were confined to their homes, which reduced transport and changed consumption patterns. Here we compile government policies and activity data to estimate the decrease in CO₂ emissions during forced confinements. Daily global CO₂ emissions decreased by –17% (–11 to –25% for ±1σ) by early April 2020 compared with the mean 2019 levels, just under half from changes in surface transport. At their peak, emissions in individual countries decreased by –26% on average. The impact on 2020 annual emissions depends on the duration of the confinement, with a low estimate of –4% (–2 to –7%) if prepandemic conditions return by mid-June, and a high estimate of –7% (–3 to –13%) if some restrictions remain worldwide until the end of 2020. Government actions and economic incentives postcrisis will likely influence the global CO₂ emissions path for decades.

Recent wildfire outbreaks around the world have prompted concern that climate change is increasing fire incidence, threatening human livelihood and biodiversity, and perpetuating climate change. Here, we review current understanding of the impacts of climate change on fire weather (weather conditions conducive to the ignition and spread of wildfires) and the consequences for regional fire activity as mediated by a range of other bioclimatic factors (including vegetation biogeography, productivity and lightning) and human factors (including ignition, suppression, and land use). Through supplemental analyses, we present a stocktake of regional trends in fire weather and burned area (BA) during recent decades, and we examine how fire activity relates to its bioclimatic and human drivers. Fire weather controls the annual timing of fires in most world regions and also drives inter‐annual variability in BA in the Mediterranean, the Pacific US and high latitude forests. Increases in the frequency and extremity of fire weather have been globally pervasive due to climate change during 1979–2019, meaning that landscapes are primed to burn more frequently. Correspondingly, increases in BA of ∼50% or higher have been seen in some extratropical forest ecoregions including in the Pacific US and high‐latitude forests during 2001–2019, though interannual variability remains large in these regions. Nonetheless, other bioclimatic and human factors can override the relationship between BA and fire weather. For example, BA in savannahs relates more strongly to patterns of fuel production or to the fragmentation of naturally fire‐prone landscapes by agriculture. Similarly, BA trends in tropical forests relate more strongly to deforestation rates and forest degradation than to changing fire weather. Overall, BA has reduced by 27% globally in the past two decades, due in large part to a decline in BA in African savannahs. According to climate models, the prevalence and extremity of fire weather has already emerged beyond its pre‐industrial variability in the Mediterranean due to climate change, and emergence will become increasingly widespread at additional levels of warming. Moreover, several of the major wildfires experienced in recent years, including the Australian bushfires of 2019/2020, have occurred amidst fire weather conditions that were considerably more likely due to climate change. Current fire models incompletely reproduce the observed spatial patterns of BA based on their existing representations of the relationships between fire and its bioclimatic and human controls, and historical trends in BA also vary considerably across models. Advances in the observation of fire and understanding of its controlling factors are supporting the addition or optimization of a range of processes in models. Overall, climate change is exerting a pervasive upwards pressure on fire globally by increasing the frequency and intensity of fire weather, and this upwards pressure will escalate with each increment of global warming. Improvements to fire models and a better understanding of the interactions between climate, climate extremes, humans and fire are required to predict future fire activity and to mitigate against its consequences.

The desire to promote Natural Flood Management (NFM) has not yet been matched by implementation. In part, this reflects the lack of scientific evidence regarding the ability of NFM measures to contribute to risk reduction at the national scale. Broad scale understanding, as exemplified for Great Britain in this paper, is necessary evidence for policy development and a prerequisite for implementation at scale. This does not imply a lack of confidence in the wider benefits that NFM provide (for biodiversity, carbon sequestration, well‐being and many others), but without credible quantified flood risk reduction evidence, progress has been slow. This paper integrates national‐scale hydrological models (using SHETRAN and HBV‐TYN) and fluvial flood risk analysis (using the Future Flood Explorer, FFE) to quantify the flood risk reduction benefits of NFM across Great Britain under conditions of future climate and socio‐economic change. An optimisation of these benefits is presented considering alternative NFM policy ambitions and other demands on land (urban development, agriculture, and biodiversity). The findings suggest NFM has the potential to make a significant contribution to national flood risk reduction when implemented as part of a portfolio of measures. An optimisation through to 2100 suggests investment in NFM achieves a benefit‐to‐cost ratio of ~3 to 5 (based on the reduction in Expected Annual Damage (EAD) to residential properties alone). By the 2050s, this equates to an ~£80 m reduction in EAD under a scenario of low population growth and a 2°C rise in global warming by 2100. This increases to £110 m given a scenario of high population growth and a 4°C rise. Assuming current levels of adaptation continue in all other aspects of flood risk management, this represents ~9%–13% of the reduction in EAD achieved by the portfolio as a whole. By the 2080s, the contribution of NFM to risk reduction increases to ~£110 and ~£145 m under these two scenarios. These figures are based on the reduction in EAD to residential properties alone, and do not include the substantial co‐benefits that would also accrue.

Prescribed (Rx) and controlled fires are an important land management tool used globally for a variety of reasons, including the reduction of hazardous fuel loads, ecological conservation, agriculture, and natural resource management. Its use has important implications for wildfire risk, biodiversity, and carbon storage. However, the use of Rx and controlled fires is highly dependent upon weather conditions, requiring a weather window during which a careful balance of temperature, moisture, and wind ensure that the burns achieve their objectives while minimizing ecological damage or risk to human lives or assets. The planning and execution of Rx burns must also consider how these weather conditions interact with the local vegetation and ecology. As fire weather is projected to grow more extreme under the impacts of climate change, there is a growing need to monitor this effect on the ability to carry out Rx burning.Here, we introduce a new dataset, GlobalRx, which includes around 140,000 records of Rx and other controlled fires from 16 countries, encompassing 207 ecoregions and 13 biomes around the world. For each record, we have geolocated values of various metrics of fire weather and fire danger (e.g. fire weather indices, vapour pressure deficit) from the ERA5 meteorological reanalysis, as well as the biome, ecoregion, fuelbed type, and protected area status from global thematic layers. We demonstrate the usefulness of this dataset for analyzing viable meteorological windows under which Rx fires may be conducted across diverse environmental settings in the present climate, as well as how these Rx burning windows may shift under the threats of climate change. This dataset has potential to shed light on how Rx burning windows may shift under future climate change, as well as opportunities to understand other drivers and effects of Rx burning.This project has been supported by valuable contributions from non-public data from a consortium of data providers: Parks Canada, South Africa National Parks, Brazilian Institute of the Environment and Renewable Natural Resources, East-Pyrenees Prescribed Burning Team, Institute for Nature Conservation and Forests (Portugal), Regional Forest Fire Service (Italy), Russian Federal Forestry Agency, H2020 LifeTaiga Project, Government of the Principality of Asturias, Council of Andalucía, Council of Galicia, Forestry England, National Forestry Commission of Mexico, ZEBRIS Geo-IT GmbH, Hokkaido University, Pau Costa Foundation, Asian Forest Cooperation Organization.