Causal counterfactual theory provides clear semantics and sound logic for causal reasoning and may help foster research on, and clarify dissemination of, weather and climate-related event attribution. The current event attribution framework obeys the spirit of counterfactual logics. The author has proposed a methodology, which relies on in silico experimentation to derive both the factual and counterfactual probabilities. The attributable proportion are also used to name the same quantity. The FAR, as well as these similar terms, is used to communicate the idea, particularly relevant in epidemiology from which it originates, that the exposition to a given risk factor X translates into an increase of, say, the frequency of a given disease Y. In causal theory, the probability of necessary causation PN formally embeds the notion of causal attribution in its definition. Finally, at a more practical level, attribution studies applying causal theory require the availability of counterfactual model simulations.

We describe a new approach that allows for systematic causal attribution of weather and climate-related events, in near-real time. The method is designed so as to facilitate its implementation at meteorological centers by relying on data and methods that are routinely available when numerically forecasting the weather. We thus show that causal attribution can be obtained as a by-product of data assimilation procedures run on a daily basis to update numerical weather prediction (NWP) models with new atmospheric observations; hence, the proposed methodology can take advantage of the powerful computational and observational capacity of weather forecasting centers. We explain the theoretical rationale of this approach and sketch the most prominent features of a “data assimilation–based detection and attribution” (DADA) procedure. The proposal is illustrated in the context of the classical three-variable Lorenz model with additional forcing. The paper concludes by raising several theoretical and practical questions that need to be addressed to make the proposal operational within NWP centers.