Journal
BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY
Volume 97, Issue 1, Pages 99-110Publisher
AMER METEOROLOGICAL SOC
DOI: 10.1175/BAMS-D-14-00034.1
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Funding
- French Agence Nationale de la Recherche Grant DADA
- French Agence Nationale de la Recherche Grant MCSim
- French Agence Nationale de la Recherche Grant MOPERA
- U.S. National Science Foundation [DMS-1049253, OCE-1243175]
- Direct For Computer & Info Scie & Enginr [1527490, 1302448] Funding Source: National Science Foundation
- Directorate For Geosciences
- Division Of Ocean Sciences [1243175] Funding Source: National Science Foundation
- Div Of Information & Intelligent Systems [1527490, 1302448] Funding Source: National Science Foundation
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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 that is anchored into counterfactuals. The latter corpus has proved to be of high practical interest in numerous applied fields (e.g., epidemiology, economics, and 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 of 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.
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