Science on the role of anthropogenic influence on extreme weather events, such as heatwaves or droughts, has evolved rapidly in the past years. The approach of “event attribution” compares the occurrence‐probability of an event in the present, factual climate with its probability in a hypothetical, counterfactual climate without human‐induced climate change. Several methods can be used for event attribution, based on climate model simulations and observations, and usually researchers only assess a subset of methods and data sources. Here, we explore the role of methodological choices for the attribution of the 2015 meteorological summer drought in Europe. We present contradicting conclusions on the relevance of human influence as a function of the chosen data source and event attribution methodology. Assessments using the maximum number of models and counterfactual climates with pre‐industrial greenhouse gas concentrations point to an enhanced drought risk in Europe. However, other evaluations show contradictory evidence. These results highlight the need for a multi‐model and multi‐method framework in event attribution research, especially for events with a low signal‐to‐noise ratio and high model dependency such as regional droughts.

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 Intergovernmental Panel on Climate Change starting in 1990. Extreme event attribution (EEA), also known as attribution science and developed in the The history of the scientific discovery of climate change began in the early 19th century when ice ages and other natural changes in paleoclimate were first suspected and the natural greenhouse effect was first identified. In the late 19th century, scientists first argued that human emissions of greenhouse gases could change Earth's energy balance and climate. The existence of the greenhouse effec Extreme event attribution (EEA), also known as attribution science, was developed in the early decades of the 21st century. EEA uses climate models to identify and quantify the role that human-caused climate change plays in the frequency, intensity, duration, and impacts of specific individual extreme weather events. Results of attribution studies allow scientists and journalists to make statements such as, "this weather event was made at least n times more likely by human-caused climate change" or "this heatwave was made m degrees hotter than it would have been in a world without global warming" or "this event was effectively impossible without climate change". A common EEA approach uses model simulations to compare events in two worlds—a first world with human-caused greenhouse gas emissions and a second world without such emissions—and attributing differences to human influence. Greater computing power of the 2000s allowed weather to be simulated over and over again, and conceptual breakthroughs in the early to mid 2010s enabled attribution science to detect the effects of climate change on some events with high confidence. Scientists use methods that have already been peer reviewed, allowing "rapid attribution" studies to be published within a "news cycle" time frame.

Attribution of extreme climate events to global climate change as a result of anthropogenic greenhouse gas emissions has become increasingly important. Extreme climate events arise at the intersection of natural climate variability and a forced response of the Earth system to anthropogenic greenhouse gas emissions, which may alter the frequency and severity of such events. Accounting for the effects of both natural climate variability and the forced response to anthropogenic climate change is thus central for the attribution. Here, we investigate the reproducibility of probabilistic extreme event attribution results under more explicit representations of natural climate variability. We employ well-established methodologies deployed in statistical Earth System Model emulators to represent natural climate variability as informed from its spatio-temporal covariance structures. Two approaches towards representing natural climate variability are investigated: (1) where natural climate variability is treated as a single component; and (2) where natural climate variability is disentangled into its annual and seasonal components. We showcase our approaches by attributing the 2022 Indo-Pakistani heatwave to human-induced climate change. We find that explicit representation of annual and seasonal natural climate variability increases the overall uncertainty in attribution results considerably compared to established approaches such as the World Weather Attribution Initiative. The incre

Over the last 30 years, scientific research has increasingly implicated human activities in contemporary regional- to global-scale climatic change. Over the last decade, this research has extended to the detection of the fingerprint of human activities on individual extreme weather events. Is it possible to say that this or that weather extreme was ‘caused by’ human activities? Pursuing answers to this question raises many difficult philosophical, epistemological and political issues. In this progress report, I survey the nascent science of extreme weather event attribution by examining the field in four stages: motivations for extreme weather attribution, methods of attribution, some example case studies and the politics of weather event attribution. There remain outstanding political dangers and obstacles for extreme weather attribution if it is to be used, as some claim it can and should be, for guiding climate adaptation investments, for servicing the putative loss and damage agenda of the UN Framework Convention on Climate Change or for underpinning legal claims for liability for damages caused by extreme weather.