Literature DB >> 33218461

Severe weather event attribution: Why values won't go away.

Eric Winsberg1, Naomi Oreskes2, Elisabeth Lloyd3.   

Abstract

We start by reviewing the complicated situation in methods of scientific attribution of climate change to extreme weather events. We emphasize the social values involved in using both so-called ″storyline″ and ordinary probabilistic or ″risk-based″ methods, noting that one important virtue claimed by the storyline approach is that it features a reduction in false negative results, which has much social and ethical merit, according to its advocates. This merit is critiqued by the probabilistic, risk-based, opponents, who claim the high ground; the usual probabilistic approach is claimed to be more objective and more ″scientific″, under the grounds that it reduces false positive error. We examine this mostly-implicit debate about error, which apparently mirrors the old Jeffrey-Rudner debate. We also argue that there is an overlooked component to the role of values in science: that of second-order inductive risk, and that it makes the relative role of values in the two methods different from what it first appears to be. In fact, neither method helps us to escape social values, and be more scientifically ″objective″ in the sense of being removed or detached from human values and interests. The probabilistic approach does not succeed in doing so, contrary to the claims of its proponents. This is important to understand, because neither method is, fundamentally, a successful strategy for climate scientists to avoid making value judgments.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Climate; Models; Risk; Severe weather; Values

Mesh:

Year:  2020        PMID: 33218461     DOI: 10.1016/j.shpsa.2020.09.003

Source DB:  PubMed          Journal:  Stud Hist Philos Sci        ISSN: 0039-3681            Impact factor:   1.429


  3 in total

1.  Forecast-based attribution of a winter heatwave within the limit of predictability.

Authors:  Nicholas J Leach; Antje Weisheimer; Myles R Allen; Tim Palmer
Journal:  Proc Natl Acad Sci U S A       Date:  2021-12-07       Impact factor: 12.779

2.  Health Economists on Involving Patients in Modeling: Potential Benefits, Harms, and Variables of Interest.

Authors:  Stephanie Harvard; Gregory R Werker
Journal:  Pharmacoeconomics       Date:  2021-05-07       Impact factor: 4.981

3.  Climate scientists set the bar of proof too high.

Authors:  Elisabeth A Lloyd; Naomi Oreskes; Sonia I Seneviratne; Edward J Larson
Journal:  Clim Change       Date:  2021-04-19       Impact factor: 4.743

  3 in total

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