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A recent temperature reconstruction of global annual temperature shows Early Holocene warmth followed by a cooling trend through the Middle to Late Holocene [Marcott SA, et al., 2013, Science 339(6124):1198–1201]. This global cooling is puzzling because it is opposite from the expected and simulated global warming trend due to the retreating ice sheets and rising atmospheric greenhouse gases. Our critical reexamination of this contradiction between the reconstructed cooling and the simulated warming points to potentially significant biases in both the seasonality of the proxy reconstruction and the climate sensitivity of current climate models.

Economic productivity is shown to peak at an annual average temperature of 13 °C and decline at high temperatures, indicating that climate change is expected to lower global incomes more than 20% by 2100. The cost of a warming climate Temperature, and therefore climate change, can affect a country's economic productivity, but it has not been clear if rich and poor countries, or different aspects of economic productivity, show similar relationships. These authors use economic data from 166 countries for the years 1960 to 2010 to uncover a universal nonlinear relationship that reconciles earlier results. Economic productivity peaks at an annual average temperature of 13 °C, and the authors explore the likelihood of global economic contraction under future warming scenarios. Growing evidence demonstrates that climatic conditions can have a profound impact on the functioning of modern human societies 1 , 2 , but effects on economic activity appear inconsistent. Fundamental productive elements of modern economies, such as workers and crops, exhibit highly non-linear responses to local temperature even in wealthy countries 3 , 4 . In contrast, aggregate macroeconomic productivity of entire wealthy countries is reported not to respond to temperature 5 , while poor countries respond only linearly 5 , 6 . Resolving this conflict between micro and macro observations is critical to understanding the role of wealth in coupled human–natural systems 7 , 8 and to anticipating the global impact of climate change 9 , 10 . Here we unify these seemingly contradictory results by accounting for non-linearity at the macro scale. We show that overall economic productivity is non-linear in temperature for all countries, with productivity peaking at an annual average temperature of 13 °C and declining strongly at higher temperatures. The relationship is globally generalizable, unchanged since 1960, and apparent for agricultural and non-agricultural activity in both rich and poor countries. These results provide the first evidence that economic activity in all regions is coupled to the global climate and establish a new empirical foundation for modelling economic loss in response to climate change 11 , 12 , with important implications. If future adaptation mimics past adaptation, unmitigated warming is expected to reshape the global economy by reducing average global incomes roughly 23% by 2100 and widening global income inequality, relative to scenarios without climate change. In contrast to prior estimates, expected global losses are approximately linear in global mean temperature, with median losses many times larger than leading models indicate.

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.

Global temperatures were exceptionally high in 2023/24. Every month from June 2023 to June 2024 set a new record, and September shattered the previous record by 0.5$0.5$ °C. The 2023 annual average approached 1.5$1.5$ °C above pre‐industrial levels. This results from both long‐term warming and internal variability, with the occurrence of an El Niño episode. However the amplitude of the 2023/24 anomalies was remarkable and surprised the scientific community. Here we analyze the rarity of 2023/24 global temperatures from a climate perspective. We show that a ‘normal’ year 2023 would have roughly equaled the previous annual record, and that the most extreme events of 2023/24 rank among the most extreme since 1940. Our analysis suggests that the 2023/24 event can be reconciled with the long‐term trend and an intense, but not implausible, peak of internal variability. Plain Language Summary 2023 was the warmest year on record at global scale, and early 2024 has continued to break records. This remarkable episode has received a great deal of attention from the general public and the scientific community. It is well established that it is linked to the long‐term global warming and the occurrence of an El Niño episode, but some temperature anomalies appeared so high, shattering previous records, that several scientists suggested that global warming may have been underestimated, which would have serious implications for future projections. Here we take a step back from the 2023/24 event, precisely quantify its rarity and compare it with other hot years. Using climate monitoring and extreme event attribution methods, we first show that at the current rate of warming, a ‘normal’ year 2023 would have equaled the ‘old’ record of 2016, even without any help of El Niño. We also find that the most extreme events of 2023/24 are among the most extreme of the entire record, but remain comparable with some past events. Our analysis thus suggests that the 2023/24 event is extreme but not incompatible with current estimates of global warming. Key Points At the current rate of global warming, a normal year 2023 would have equaled the record of 2016, without any help of El Nino The most extreme anomalies of 2023/24 rank among the most extreme of the entire record since 1940 The 2023/24 heat can be reconciled with current estimates of global warming and an extreme but not implausible peak of internal variability

Equilibrium climate sensitivity—which remains the largest uncertainty in climate projections—is constrained to a ‘likely’ range of 2.2–3.4 K by taking into account the variability of global temperature about long-term historical warming. Narrowing down long-term global warming estimates Equilibrium climate sensitivity (ECS) is the long-term change in global mean surface temperature predicted to occur in response to an instantaneous doubling of atmospheric carbon dioxide concentrations. It is an inherently artificial metric, but is nonetheless an important tool when comparing climate models, and a key point of policy discussion. The seemingly intractable range of ECS estimates complicates policy making because the response of the real climate system to the lowest and highest predicted temperature change would translate into radically different policy options. Peter Cox and colleagues now constrain climate models by their ability to simulate observed variations in climate, and conclude that ECS has a central estimate of 2.8 degrees Celsius (°C), which sits towards the middle to lower end of current estimates, and a range of 2.2–3.4 °C. Importantly, their approach allows them to almost exclude ECS estimates above 4.5 °C or below 1.5 °C. Equilibrium climate sensitivity (ECS) remains one of the most important unknowns in climate change science. ECS is defined as the global mean warming that would occur if the atmospheric carbon dioxide (CO 2 ) concentration were instantly doubled and the climate were then brought to equilibrium with that new level of CO 2 . Despite its rather idealized definition, ECS has continuing relevance for international climate change agreements, which are often framed in terms of stabilization of global warming relative to the pre-industrial climate. However, the ‘likely’ range of ECS as stated by the Intergovernmental Panel on Climate Change (IPCC) has remained at 1.5–4.5 degrees Celsius for more than 25 years 1 . The possibility of a value of ECS towards the upper end of this range reduces the feasibility of avoiding 2 degrees Celsius of global warming, as required by the Paris Agreement. Here we present a new emergent constraint on ECS that yields a central estimate of 2.8 degrees Celsius with 66 per cent confidence limits (equivalent to the IPCC ‘likely’ range) of 2.2–3.4 degrees Celsius. Our approach is to focus on the variability of temperature about long-term historical warming, rather than on the warming trend itself. We use an ensemble of climate models to define an emergent relationship 2 between ECS and a theoretically informed metric of global temperature variability. This metric of variability can also be calculated from observational records of global warming 3 , which enables tighter constraints to be placed on ECS, reducing the probability of ECS being less than 1.5 degrees Celsius to less than 3 per cent, and the probability of ECS exceeding 4.5 degrees Celsius to less than 1 per cent.

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.

The Coupled Model Intercomparison Project (phase 6) (CMIP6) global circulation models (GCMs) predict equilibrium climate sensitivity (ECS) values ranging between 1.8 and 5.7 ∘ C. To narrow this range, we group 38 GCMs into low, medium and high ECS subgroups and test their accuracy and precision in hindcasting the mean global surface warming observed from 1980–1990 to 2011–2021 in the ERA5-T2m, HadCRUT5, GISTEMP v4, and NOAAGlobTemp v5 global surface temperature records. We also compare the GCM hindcasts to the satellite-based UAH-MSU v6 lower troposphere global temperature record. We use 143 GCM ensemble averaged simulations under four slightly different forcing conditions, 688 GCM member simulations, and Monte Carlo modeling of the internal variability of the GCMs under three different model accuracy requirements. We found that the medium and high-ECS GCMs run too hot up to over 95% and 97% of cases, respectively. The low ECS GCM group agrees best with the warming values obtained from the surface temperature records, ranging between 0.52 and 0.58 ∘ C. However, when comparing the observed and GCM hindcasted warming on land and ocean regions, the surface-based temperature records appear to exhibit a significant warming bias. Furthermore, if the satellite-based UAH-MSU-lt record is accurate, actual surface warming from 1980 to 2021 may have been around 0.40 ∘ C (or less), that is up to about 30% less than what is reported by the surface-based temperature records. The latter situation implies that even the low-ECS models would have produced excessive warming from 1980 to 2021. These results suggest that the actual ECS may be relatively low, i.e. lower than 3 ∘ C or even less than 2 ∘ C if the 1980–2021 global surface temperature records contain spurious warming, as some alternative studies have already suggested. Therefore, the projected global climate warming over the next few decades could be moderate and probably not particularly alarming.

The Paris Agreement promotes forest management as a pathway towards halting climate warming through the reduction of carbon dioxide (CO 2 ) emissions 1 . However, the climate benefits from carbon sequestration through forest management may be reinforced, counteracted or even offset by concurrent management-induced changes in surface albedo, land-surface roughness, emissions of biogenic volatile organic compounds, transpiration and sensible heat flux 2 – 4 . Consequently, forest management could offset CO 2 emissions without halting global temperature rise. It therefore remains to be confirmed whether commonly proposed sustainable European forest-management portfolios would comply with the Paris Agreement—that is, whether they can reduce the growth rate of atmospheric CO 2 , reduce the radiative imbalance at the top of the atmosphere, and neither increase the near-surface air temperature nor decrease precipitation by the end of the twenty-first century. Here we show that the portfolio made up of management systems that locally maximize the carbon sink through carbon sequestration, wood use and product and energy substitution reduces the growth rate of atmospheric CO 2 , but does not meet any of the other criteria. The portfolios that maximize the carbon sink or forest albedo pass only one—different in each case—criterion. Managing the European forests with the objective of reducing near-surface air temperature, on the other hand, will also reduce the atmospheric CO 2 growth rate, thus meeting two of the four criteria. Trade-off are thus unavoidable when using European forests to meet climate objectives. Furthermore, our results demonstrate that if present-day forest cover is sustained, the additional climate benefits achieved through forest management would be modest and local, rather than global. On the basis of these findings, we argue that Europe should not rely on forest management to mitigate climate change. The modest climate effects from changes in forest management imply, however, that if adaptation to future climate were to require large-scale changes in species composition and silvicultural systems over Europe 5 , 6 , the forests could be adapted to climate change with neither positive nor negative  climate effects. Simulations of commonly proposed forest-management portfolios for Europe show that no single portfolio would meet all the requirements of the Paris Agreement, and climate benefits from forest management would be modest and local.

The recent (twentieth century) and future (twenty-first century) climate evolution in the Mediterranean region is analyzed in relation to annual mean global surface temperature change. The CMIP5 (Coupled Model Intercomparison Project, Phase 5) simulations, the CRU (Climate Research Unit) observational gridded dataset, and two twentieth century reanalyzes (ECMWF, European Center for Medium range Weather Forecasts) and NOAA ESRL (National Oceanic and Atmospheric Administration-Earth System Research Laboratory) are used. These datasets to large extent agree that in the twentieth century: (a) Mediterranean regional and global temperatures have warmed at a similar rate until the 1980s and (b) decadal variability determines a large uncertainty that prevents to identify long-term links between precipitation in the Mediterranean region and global temperature. However, in the twenty-first century, as mean global temperature increases, in the Mediterranean region, precipitation will decrease at a rate around − 20 mm/K or − 4%/K and temperature will warm 20% more than the global average. Warming will be particularly large in summer (approximately 50% larger than global warming) and for the land areas located north of the basin (locally up to 100% larger than global warming). Reduction of precipitation will affect all seasons in the central and southern Mediterranean areas, with maximum reduction for winter precipitation (− 7 mm/K or − 7%/K for the southern Mediterranean region). For areas along the northern border of the Mediterranean region, reduction will be largest in summer (− 7 mm/K or − 9%/K for the whole northern Mediterranean region), while they will not experience a significant reduction of precipitation in winter.

To understand how global warming can be kept well below 2 degrees Celsius and even 1.5 degrees Celsius, climate policy uses scenarios that describe how society could reduce its greenhouse gas emissions. However, current scenarios have a key weakness: they typically focus on reaching specific climate goals in 2100. This choice may encourage risky pathways that delay action, reach higher-than-acceptable mid-century warming, and rely on net removal of carbon dioxide thereafter to undo their initial shortfall in reductions of emissions. Here we draw on insights from physical science to propose a scenario framework that focuses on capping global warming at a specific maximum level with either temperature stabilization or reversal thereafter. The ambition of climate action until carbon neutrality determines peak warming, and can be followed by a variety of long-term states with different sustainability implications. The approach proposed here closely mirrors the intentions of the United Nations Paris Agreement, and makes questions of intergenerational equity into explicit design choices. Fundamental value judgments about acceptable maximum levels of climate change and future reliance on controversial technologies can be made explicitly in climate scenarios, thereby addressing the intergenerational bias present in the scenario literature.