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The field of extreme event attribution (EEA) has rapidly developed over the last two decades. Various methods have been developed and implemented, physical modelling capabilities have generally improved, the field of impact attribution has emerged, and assessments serve as a popular communication tool for conveying how climate change is influencing weather and climate events in the lived experience. However, a number of non-trivial challenges still remain that must be addressed by the community to secure further advancement of the field whilst ensuring scientific rigour and the appropriate use of attribution findings by stakeholders and associated applications. As part of a concept series commissioned by the World Climate Research Programme, this article discusses contemporary developments and challenges over six key domains relevant to EEA, and provides recommendations of where focus in the EEA field should be concentrated over the coming decade. These six domains are: (1) observations in the context of EEA; (2) extreme event definitions; (3) statistical methods; (4) physical modelling methods; (5) impact attribution; and (6) communication. Broadly, recommendations call for increased EEA assessments and capacity building, particularly for more vulnerable regions; contemporary guidelines for assessing the suitability of physical climate models; establishing best-practice methodologies for EEA on compound and record-shattering extremes; co-ordinated interdisciplinary engagement to develop scaffolding for impact attribution assessments and their suitability for use in broader applications; and increased and ongoing investment in EEA communication. To address these recommendations requires significant developments in multiple fields that either underpin (e.g., observations and monitoring; climate modelling) or are closely related to (e.g., compound and record-shattering events; climate impacts) EEA, as well as working consistently with experts outside of attribution and climate science more generally. However, if approached with investment, dedication, and coordination, tackling these challenges over the next decade will ensure robust EEA analysis, with tangible benefits to the broader global community.

The reality of human-induced climate change is unequivocal and exerts an ever-increasing global impact. Access to the latest scientific information on current climate change and projection of future trends is important for planning adaptation measures and for informing international efforts to reduce emissions of greenhouse gases (GHGs). Identification of hazards and risks may be used to assess vulnerability, determine limits to adaptation, and enhance resilience to climate change. This article highlights how recent research programs are continuing to elucidate current processes and advance projections across major climate systems and identifies remaining knowledge gaps. Key findings include projected future increases in monsoon rainfall, resulting from a changing balance between the rainfall-reducing effect of aerosols and rainfall-increasing GHGs; a strengthening of the storm track in the North Atlantic; an increase in the fraction of precipitation that falls as rain at both poles; an increase in the frequency and severity of El Niño Southern Oscillation (ENSO) events, along with changes in ENSO teleconnections to North America and Europe; and an increase in the frequency of hazardous hot-humid extremes. These changes have the potential to increase risks to both human and natural systems. Nevertheless, these risks may be reduced via urgent, science-led adaptation and resilience measures and by reductions in GHGs.

Abstract Britain's power system has shifted towards a major contribution from wind energy. However, wind is highly variable, and exceptionally low wind events can simultaneously occur with cold conditions, which increase demand. These conditions can pose a threat for the security of energy supply. Here we use bias‐corrected wind supply data and the estimated temperature‐related part of demand to analyse events of potential weather‐related energy shortfall based on the historic meteorological record. We conduct sensitivity studies with varying scenarios of Britain's total wind energy capacity and the temperature sensitivity of national demand. These scenarios are estimates for present‐day conditions as well as potential future changes of the power system. We apply a new methodology to estimate the potential severity of an event for the power system, and analyse the atmospheric conditions associated with the most severe events. We find that events of potentially severe shortfall are relatively rare and short‐lived, and often occur with an atmospheric pattern broadly resembling a negative North Atlantic Oscillation. This broad tendency emerges from a wide range of individual daily weather patterns that cause cold and still conditions. With an increase in wind capacity, it is likely that severe events will become rarer, although the most severe days of the record are relatively insensitive to changes in wind supply and temperature sensitivity of demand under our assumptions.

Abstract Heatwaves are becoming more frequent under climate change and can lead to thousands of excess deaths. Adaptation to extreme weather events often occurs in response to an event, with communities learning fast following unexpectedly impactful events. Using extreme value statistics, here we show where regional temperature records are statistically likely to be exceeded, and therefore communities might be more at-risk. In 31% of regions examined, the observed daily maximum temperature record is exceptional. Climate models suggest that similar behaviour can occur in any region. In some regions, such as Afghanistan and parts of Central America, this is a particular problem - not only have they the potential for far more extreme heatwaves than experienced, but their population is growing and increasingly exposed because of limited healthcare and energy resources. We urge policy makers in vulnerable regions to consider if heat action plans are sufficient for what might come.

Abstract Variability in the North Atlantic Oscillation (NAO) has contributed to the recent multidecadal trends observed in European climate, especially to trends in winter precipitation over Northern Europe. However, the current generation of coupled climate models struggle to reproduce the NAO's contribution to multidecadal trends, which has important implications for deriving constraints based on the comparison of observed and modeled trends. An observational constraint based on attribution results, both with and without the contribution of variability associated with the NAO, is applied to projections of Northern European precipitation and temperature, and observed NAO variability is shown to lead to a constraint that overestimates future forced changes. Only after removing the NAO variability is the observed climate change consistent with model simulations, and a tighter, unbiased observational constraint based on the forced signal (without the NAO) can be applied to future projections.

Global warming has clearly affected the occurrence of extreme events in recent years. Here, we assess changes in the frequency of temperature extremes and their causes, using percentile-based indices. Cold extremes are defined as temperatures below the 10th percentile of daily minimum (TN10) and maximum (TX10) temperatures while hot extremes exceed the 90th percentile of daily minimum (TN90) and maximum (TX90) temperatures. We analyze Berkeley Earth Surface Temperature (BEST) for observed changes in the last four decades 1981-2020, for two extended seasons, boreal summer April–September (AMJJAS) and boreal winter October–March (ONDJFM), and evaluate results using several reanalysis data sets. For the attribution of causes we use CMIP6 climate model simulations, analyzing natural-only and anthropogenic-only forcings. We use an attribution method that accounts for climate modeling uncertainty in both amplitude and pattern of responses.The observations show detectable changes in both cold and hot extreme temperatures. Hot extremes have increased in all regions and in both seasons while cold extremes have decreased over the past decades. Our attribution analysis revealed anthropogenic forcings are robustly detectable and the main drivers of observed changes in all indices for all regions, consistently in all data sets. Contributions from natural forcings are found small and detectable only in a few regions mainly for daytime cold extremes in ONDJFM. Anthropogenic forcing contributed to an increase of 3.4 days per decade in TN90 and of 2.7 days per decade in TX90, on average, at the global scale. Regionally, the anthropogenic contribution caused a range of decrease of 2–4.7 days per decade in TN10, 1.5–3.6 days per decade in TX10 while it caused an increase of 2.2–4.8 days per decade for TN90 and 2–3.3 days per decade in TX90. Anthropogenic-only warming in ONDJFM is slightly less than in AMJJAS.

Climate change does not only increase mean temperatures, but also the magnitude of year-to-year temperature variability. Here, the authors use large model ensembles to show that these changes can be statistically distinguished from the baseline variability in most regions of the world during the 21st century.

Two founding fathers of climate science and climate modelling were honoured with the Nobel prize in physics this year. They led early climate research towards both fundamental and societally relevant research, which is now as vital as it was then.

In the 1930s, the US was hit by a severe drought and record-breaking heatwaves in a period known as the Dust Bowl. Here, the authors present model experiments that suggest that warm North Atlantic temperatures and human devegetation played key roles in making these heatwaves particularly strong.

Observations facilitate model evaluation and provide constraints that are relevant to future predictions and projections. Constraints for uninitialized projections are generally based on model performance in simulating climatology and climate change. For initialized predictions, skill scores over the hindcast period provide insight into the relative performance of models, and the value of initialization as compared to projections. Predictions and projections combined can, in principle, provide seamless decadal to multi-decadal climate information. For that, though, the role of observations in skill estimates and constraints needs to be understood in order to use both consistently across the prediction and projection time horizons. This paper discusses the challenges in doing so, illustrated by examples of state-of-the-art methods for predicting and projecting changes in European climate. It discusses constraints across prediction and projection methods, their interpretation, and the metrics that drive them such as process accuracy, accurate trends or high signal-to-noise ratio. We also discuss the potential to combine constraints to arrive at more reliable climate prediction systems from years to decades. To illustrate constraints on projections, we discuss their use in the UK's climate prediction system UKCP18, the case of model performance weights obtained from the Climate model Weighting by Independence and Performance (ClimWIP) method, and the estimated magnitude of the forced signal in observations from detection and attribution. For initialized predictions, skill scores are used to evaluate which models perform well, what might contribute to this performance, and how skill may vary over time. Skill estimates also vary with different phases of climate variability and climatic conditions, and are influenced by the presence of external forcing. This complicates the systematic use of observational constraints. Furthermore, we illustrate that sub-selecting simulations from large ensembles based on reproduction of the observed evolution of climate variations is a good testbed for combining projections and predictions. Finally, the methods described in this paper potentially add value to projections and predictions for users, but must be used with caution.

The intensity and frequency of extreme heat events is increasing due to climate change, resulting in a range of societal impacts. In this paper, we use temporal analogues to analyse how past UK heatwave events, such as during the summer of 1923, may change if they were to occur under different global warming scenarios. We find that the six most intense early heat events are caused by circulation patterns similar to that of 1923, which can cause intense heat over the UK and parts of NW Europe. Circulation analogues for the 1923 heatwave are also linked to intense heat events in the future, although not all analogues are anomalously hot. At 4 °C of global warming, mean summer temperatures in England over the duration of the 1923 heatwave are between 4.9 and 6.4 degrees warmer than pre-industrial levels across the three models used. At that global mean warming level, future heat events with similar circulation as 1923 over England are estimated to be on average 6.9 °C–10.7 °C hotter than those at pre-industrial levels. Exploring how the intensity of events similar to past events may change in the future could be an effective risk communication tool for adaptation decision making, particularly if past events are stored in society’s memory, for example, due to high impacts.

The North Atlantic Oscillation (NAO) plays a leading role in modulating wintertime climate over the North Atlantic and the surrounding continents of Europe and North America. Here we show that the observed evolution of the NAO displays larger multi-decadal variability than that simulated by nearly all CMIP6 models. To investigate the role of the NAO as a pacemaker of multi-decadal climate variability, we analyse simulations that are constrained to follow the observed NAO. We use a particle filter data-assimilation technique that sub-selects members that follow the observed NAO among an ensemble of simulations, as well as the El Niño Southern Oscillation and Southern Annular Mode in a global climate model, without the use of nudging terms. Since the climate model also contains external forcings, these simulations can be used to compare the simulated forced response to the effect of the three assimilated modes. Concentrating on the 28 year periods of strongest observed NAO trends, we show that NAO variability leads to large multi-decadal trends in temperature and precipitation over Northern Hemisphere land as well as in sea-ice concentration. The Atlantic subpolar gyre region is particularly strongly influenced by the NAO, with links found to both concurrent atmospheric variability and to the Atlantic Meridional Overturning Circulation (AMOC). Care thus needs to be taken to account for impacts of the NAO when using sea surface temperature in this region as a proxy for AMOC strength over decadal to multi-decadal time-scales. Our results have important implications for climate analyses of the North Atlantic region and highlight the need for further work to understand the causes of multi-decadal NAO variability.

The adverse impacts of marine heatwaves (MHWs) on marine ecosystems and human activities are well-documented, yet observational studies tend to largely rely on recent records. Long-term records of MHWs can put the recent increase in frequency and intensity of MHWs in the context of past variability. We used long-term monthly sea surface temperature (SST) data and night marine air temperatures to characterise past MHW activity. A persistent increase in the global extent of MHWs is demonstrated, beginning around 1970. The average annual MHW extent post-2010 is estimated to be increased at least four fold compared to that pre-1970. A strong correlation between spatial variance of recorded average monthly SSTs and the average inverse number of monthly observations implies both frequency and amplitude of MHWs is overestimated when the number of monthly observations is low. Nevertheless, many identified early MHWs appear genuine, such as a multi-month event in the North Atlantic in 1851–1852. MHWs are also affected by poorer sampling during the world wars. The most extensive MHW years globally coincide with El Niño years, and MHW extent in the North Atlantic is correlated with the Atlantic Multidecadal Oscillation.

Extreme heat, particularly if combined with humidity, poses a severe risk to human health. To estimate future global risk of extreme heat with humidity on health, we calculate indicators of heat stress that have been commonly used: the Heat Index, the Wet-Bulb Globe Temperature and the Wet-Bulb Temperature, from the latest Climate Model Intercomparison Project (CMIP6) projections. We analyse how and where different levels of heat stress hazards will change, from severe to deadly, and how results are sensitive to the choice of the index used. We evaluate this risk at country-level and use population and GDP $|$ PPP growth scenario to estimate the vulnerability of each nation. Consistent with previous studies, we find that South and East Asia, and the Middle-East, are highly exposed to heat stress hazards, and that this exposure increases by 20%–60% with global mean temperature change from 1.5 to 3 ^∘ C. However, we also find substantial increases in heat health risk for some vulnerable countries with less adaptive capacity, such as West Africa, and Central and South America. For these regions, about 20 to more than 50% of the population could be exposed to severe heat stress each year on average, independent of the index used. For global warming of 3 ^∘ , European countries and the USA will also be exposed several times per year to conditions with daily mean heat stress level equal to the maximum heat stress of the 2003 heat wave.

Climate models predict a strengthening contrast between wet and dry regions in the tropics and subtropics (30 °S–30 °N), and data from the latest model intercomparison project (CMIP6) support this expectation. Rainfall in ascending regions increases, and in descending regions decreases in climate models, reanalyses, and observational data. This strengthening contrast can be captured by tracking the rainfall change each month in the wettest and driest third of the tropics and subtropics combined. Since wet and dry regions are selected individually every month for each model ensemble member, and the observations, this analysis is largely unaffected by biases in location of precipitation features. Blended satellite and in situ data from 1988–2019 support the CMIP6-model-simulated tendency of sharpening contrasts between wet and dry regions, with rainfall in wet regions increasing substantially opposed by a slight decrease in dry regions. We detect the effect of external forcings on tropical and subtropical observed precipitation in wet and dry regions combined, and attribute this change for the first time to anthropogenic and natural forcings separately. Our results show that most of the observed change has been caused by increasing greenhouse gases. Natural forcings also contribute, following the drop in wet-region precipitation after the 1991 eruption of Mount Pinatubo, while anthropogenic aerosol effects show only weak trends in tropic-wide wet and dry regions consistent with flat global aerosol forcing over the analysis period. The observed response to external forcing is significantly larger ( p > 0.95) than the multi-model mean simulated response. As expected from climate models, the observed signal strengthens further when focusing on the wet tail of spatial distributions in both models and data.

We examine the precipitation response to volcanic eruptions in the Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations compared to three observational datasets, including one with ocean coverage. Global precipitation decreases significantly following eruptions in CMIP5 models, with the largest decrease in wet tropical regions. This also occurs in observational land data, and ocean data in the boreal cold season. Monsoon rainfall decreases following eruptions in both models and observations. In response to individual eruptions, the ITCZ shifts away from the hemisphere with the greater concentration of aerosols in CMIP5. Models undergo a longer-lasting ocean precipitation response than over land, but the response in the short satellite record is too noisy to confirm this. We detect the influence of volcanism on precipitation in all three datasets in the cold season, although the models underestimate the size of the response. In the warm season the volcanic influence is only marginally detectable.