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The emergence of clear semantics for causal claims and of a sound logic for causal reasoning is relatively recent, with the consolidation over the past decades of a coherent theoretical corpus of definitions, concepts and methods of general applicability (e.g. Pearl [2000]) which is anchored into counterfactuals. The latter corpus has proved to be of high practical interest in numerous applied fields (e.g. epidemiology, economics, social science). In spite of their rather consensual nature and proven efficacy, these definitions and methods are to a large extent not used in Detection and Attribution (D&A). This article gives a brief overview on the main concepts underpinning the causal theory and proposes some methodological extensions for the causal attribution of weather and climate-related events that are rooted into the latter. Implications for the formulation of causal claims and their uncertainty are finally discussed. CAPSULE SUMMARY Causal counterfactual theory provides clear semantics and sound logic for causal reasoning. It may help foster research on, and clarify dissemination of, weather and climate-related events attribution. 17