Many studies have sought to constrain climate projections based on recent observations. Until recently, these constraints had limited impact, and projected warming ranges were driven primarily by model outputs. Here, we use the newest climate model ensemble, improved observations, and a new statistical method to narrow uncertainty on estimates of past and future human-induced warming. Cross-validation suggests that our method produces robust results and is not overconfident. We derive consistent observationally constrained estimates of attributable warming to date and warming rate, the response to a range of future scenarios, and metrics of climate sensitivity. We find that historical observations narrow uncertainty on projected future warming by about 50%. Our results suggest that using an unconstrained multimodel ensemble is no longer the best choice for global mean temperature projections and that the lower end of previous estimates of 21st century warming can now be excluded.

A realistic simulation of the Atlantic Multidecadal Variability (AMV) and related teleconnections is essential to resolve and understand the potential predictability over Europe at decadal timescale. Based on a large ensemble of state-of-the-art climate models, we show that a considerable intermodel spread exists in the spatiotemporal properties of the simulated AMV and teleconnections with European summer temperature. The greater the persistence, variance, and basin-scale spatial coherence, the stronger the teleconnection. We demonstrate that only a few members of a few models produce a teleconnection that is consistent with observational estimates over the instrumental period. This highlights the possible extreme nature of the last century teleconnection and/or a detrimental underestimation of ocean-land teleconnectivity in many climate models. Yet we emphasize the considerable uncertainties due to methods used to disentangle internal and externally forced variations in observations, and to sampling, which must be correctly accounted when analyses are performed on short temporal records.

Political decisions, adaptation planning, and impact assessments need reliable estimates of future climate change and related uncertainties. In order to provide these estimates, different approaches to constrain, filter, or weight climate model projections into probabilistic distributions have been proposed. However, an assessment of multiple such methods to, for example, expose cases of agreement or disagreement, is often hindered by a lack of coordination, with methods focusing on a variety of variables, time periods, regions, or model pools. Here, a consistent framework is developed to allow a quantitative comparison of eight different methods; focus is given to summer temperature and precipitation change in three spatial regimes in Europe in 2041-2060 relative to 1995-2014. The analysis draws on projections from several large ensembles, the CMIP5 multi-model ensemble, and perturbed physics ensembles, all using the high-emission scenario RCP8.5. The methods’ key features are summarized, assumptions are discussed and resulting constrained distributions are presented. Method agreement is found to be dependent on the investigated region but is generally higher for median changes than for the uncertainty ranges. This study, therefore, highlights the importance of providing clear context about how different methods affect the assessed uncertainty, particularly the upper and lower percentiles that are of interest to risk-averse stakeholders. The comparison also exposes cases where diverse lines of evidence lead to diverging constraints; additional work is needed to understand how the underlying differences between methods lead to such disagreements and to provide clear guidance to users.

Atlantic multidecadal variability (AMV) has been linked to the observed slowdown of global warming over 1998–2012 through its impact on the tropical Pacific. Given the global importance of tropical Pacific variability, better understanding this Atlantic–Pacific teleconnection is key for improving climate predictions, but the robustness and strength of this link are uncertain. Analyzing a multi-model set of sensitivity experiments, we find that models differ by a factor of 10 in simulating the amplitude of the Equatorial Pacific cooling response to observed AMV warming. The inter-model spread is mainly driven by different amounts of moist static energy injection from the tropical Atlantic surface into the upper troposphere. We reduce this inter-model uncertainty by analytically correcting models for their mean precipitation biases and we quantify that, following an observed 0.26 °C AMV warming, the equatorial Pacific cools by 0.11 °C with an inter-model standard deviation of 0.03 °C.

The influence of the Atlantic Multidecadal Variability (AMV) on the North Atlantic storm track and eddy–driven jet in the winter season is assessed via a coordinated analysis of idealised simulations with state-of-the-art coupled models. Data used are obtained from a multi-model ensemble of AMV± experiments conducted in the framework of the Decadal Climate Prediction Project component C. These experiments are performed by nudging the surface of the Atlantic ocean to states defined by the superimposition of observed AMV± anomalies onto the model climatology. A robust extra-tropical response is found in the form of a wave-train extending from the Pacific to the Nordic seas. In the warm phase of the AMV compared to cold phase, the Atlantic storm track is typically contracted and less extended poleward and the low-level jet is shifted towards the equator in the Eastern Atlantic. Despite some robust features, the picture of an uncertain and model-dependent response of the Atlantic jet emerges and we demonstrate a link between model bias and the character of the jet response.

Planning for adaptation to climate change requires accurate climate projections. Recent studies have shown that the uncertainty in global mean surface temperature projections can be considerably reduced using historical observations. However, the transposition of these new results to the local scale is not yet available. Here, we adapt an innovative statistical method that combines the latest generation of climate model simulations, global observations, and local observations to reduce uncertainty in local temperature projections. By taking advantage of the tight links between local and global temperature, we can derive the local implications of global constraints. The model uncertainty is reduced by 30% up to 70% at any location worldwide, allowing to substantially improve the quantification of risks associated with future climate change. A rigorous evaluation of these results within a perfect model framework indicates a robust skill, leading to a high confidence in our constrained climate projections.

The influence of the Atlantic Multidecadal Variability (AMV) and its amplitude on the Euro-Mediterranean summer climate is studied in two climate models, namely CNRM-CM5 and EC-Earth3P. Large ensembles of idealized experiments have been conducted in which North Atlantic sea surface temperatures are relaxed towards different amplitudes of the observed AMV anomalies. In agreement with observations, during a positive phase of the AMV both models simulate an increase (decrease) in temperature of 0.2 °C to 0.8 °C and a decrease (increase) in precipitation over the Mediterranean basin of 0.1 mm.day-1 to 0.2 mm.day-1 (northern half of Europe) compared to a negative phase. Heatwave durations over the Mediterranean land regions are 40% (up to 85% over the eastern regions) longer for a moderate amplitude of the AMV. Lower and higher amplitudes lead to longer durations of ∼30% and ∼100%, respectively. A comparison with observed heatwaves indicates that the AMV can considerably modulate the current anthropogenically-forced response on heatwaves durations depending on the area and on the AMV amplitude. The related anticyclonic anomalies over the Mediterranean basin are associated with drier soils and a reduction of cloud cover, which concomitantly induce a decrease (increase) of the latent (sensible) heat flux, and an enhancement of the downward radiative fluxes over lands. It is found that both tropical and extra-tropical forcings from the AMV are needed to trigger mechanisms, which modulate the atmospheric circulation over the Euro-Atlantic region. The amplitude of the local climate response over the Mediterranean basin evolves linearly with the amplitude of the AMV. However, the strength of this relationship differs between the models, and depends on their intrinsic biases.

Abstract. Building on CMIP6 climate simulations, updated global and regional observations, and recently introduced statistical methods, we provide an updated assessment of past and future warming over France. Following the IPCC AR6 and recent global-scale studies, we combine model results with observations to constrain climate change at the regional scale. Over mainland France, the forced warming in 2020 with respect to 1900–1930 is assessed to be 1.66 [1.41 to 1.90] ∘C, i.e., in the upper range of the CMIP6 estimates, and is almost entirely human-induced. A refined view of the seasonality of this past warming is provided through updated daily climate normals. Projected warming in response to an intermediate emission scenario is assessed to be 3.8 ∘C (2.9 to 4.8 ∘C) in 2100 and rises up to 6.7 [5.2 to 8.2] ∘C in a very high emission scenario, i.e., substantially higher than in previous ensembles of global and regional simulations. Winter warming and summer warming are expected to be about 15 % lower than and 30 % higher than the annual mean warming, respectively, for all scenarios and time periods. This work highlights the importance of combining various lines of evidence, including model and observed data, to deliver the most reliable climate information. This refined regional assessment can feed adaptation planning for a range of activities and provides additional rationale for urgent climate action. Code is made available to facilitate replication over other areas or political entities.