Establishing causation in climate litigation

• Verfasst von: Pfrommer, Tobias [VerfasserIn]
• Verfasst von: Goeschl, Timo [VerfasserIn]
• Titel: Establishing causation in climate litigation
• Titelzusatz: admissibility and reliability
• Verf.angabe: Tobias Pfrommer, Timo Goeschl, Alexander Proelss, Martin Carrier, Johannes Lenhard, Henrike Martin, Ulrike Niemeier, Hauke Schmidt
• E-Jahr: 2019
• Jahr: 4 January 2019
• Umfang: 18 S.
• Fussnoten: Gesehen am 17.05.2019
• Titel Quelle: Enthalten in: Climatic change
• Ort Quelle: Dordrecht [u.a.] : Springer Science + Business Media B.V, 1977
• Jahr Quelle: 2019
• Band/Heft Quelle: 152(2019), 1, Seite 67-84
• ISSN Quelle: 1573-1480
• DOI: doi:10.1007/s10584-018-2362-4
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1665811625

Abstract

Climate litigation has attracted renewed interest as a governance tool. A key challenge in climate litigation is to assess the factual basis of causation. Extreme weather attribution, specifically the Fraction of Attributable Risk (FAR), has been proposed as a way to tackle this challenge. What remains unclear is how attribution science interacts with the legal admissibility of evidence based on climate models. While evidence has to be legally admissible in order to be considered in a trial, it has to be reliable in order for the court to arrive at a legally correct conclusion. Since parties to the trial have incentives to produce evidence favorable to their case, admissibility requirements and the reliability of the evidence brought forward are linked. We provide a specific proposal for how to accommodate FAR estimates in admissibility standards by modifying an existing set of admissibility criteria, the Daubert criteria. We argue that two of the five Daubert criteria are unsuitable for dealing with such evidence and that replacing those criteria with ones directly addressing the reliability of FAR estimates is adequate. Lastly, we highlight the dependence of courts on both the existence and accessibility of a framework to determine the reliability of FAR estimates in executing such criteria.