Against “Possibilist” Interpretations of Climate Models

Dethier, Corey

doi:10.1017/psa.2023.6

Cited by 2 publications

(1 citation statement)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We would argue, nevertheless, that probabilistic projections remain both justifiable and useful. A probability distribution derived from climate models may be distorted, but this does not mean that we should abandon a probabilistic approachidealized models can still provide valuable information about the real world (Dethier, 2023).…”

Section: Introductionmentioning

confidence: 99%

Fusion of Probabilistic Projections of Sea-Level Rise

Grandey,

Dauwels,

Koh

et al. 2024

Preprint

View full text Add to dashboard Cite

Alternative projections of sea-level rise from ice sheet mass loss differ markedly. The differences drive ambiguity in probabilistic projections of sea level. Can the alternative projections be combined to produce a single probabilistic projection that quantifies a best estimate of the scientific uncertainty? To produce this best estimate, we propose a fusion of alternative projections. The fusion combines the complementary strengths of the ‘medium confidence’ and the ‘low confidence’ projections. Two assumptions undergird the fusion. First, we assume that the ‘medium confidence’ projections reliably sample the most-likely central possibilities. Second, we assume that the p-box outer bound – which includes the ‘low confidence’ projections – provides a more reliable estimate of unlikely tail possibilities driven by poorly-understood processes. Accordingly, the fusion is weighted towards the ‘medium confidence’ projections near the median and towards the p-box outer bound near the tails. We demonstrate our proposed fusion by combining alternative projections of sea-level change at the end of the 21st century. The fusion provides probabilistic answers: according to the fusion, the probability of global mean sea-level change exceeding 1.0 m by 2100 is 6% under a low-emissions scenario and 31% under a high-emissions scenario. The fusion also informs summary statements based on credible intervals: under a high-emissions scenario, for example, we are 90% certain that global mean sea level will rise by 0.5–2.2 m during the 21st century. By quantifying a best estimate of scientific uncertainty, the fusion caters to diverse users.

show abstract

Section: Introductionmentioning

confidence: 99%

Fusion of Probabilistic Projections of Sea-Level Rise

Grandey,

Dauwels,

Koh

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Contrast classes and agreement in climate modeling

Dethier

2024

Euro Jnl Phil Sci

Self Cite

View full text Add to dashboard Cite

It's widely argued that agreement-or "robustness"-across climate models isn't a useful marker of confirmation: that the models agree on a hypothesis does not indicate that that hypothesis should be accepted. The present paper argues against pinning the failure of agreement-based reasoning on the models. Instead, the problem is that agreement is a reliable marker of confirmation only when the hypotheses under consideration are mutually exclusive. Since most cutting-edge questions in climate modeling require making distinctions between mutually consistent hypotheses, agreement across models is unlikely to help answer these questions. Because the problem here is agreement (and not the models), we should expect that there are other ways of using the models that are more informative and reliable.

show abstract

Against “Possibilist” Interpretations of Climate Models

Cited by 2 publications

References 22 publications

Fusion of Probabilistic Projections of Sea-Level Rise

Fusion of Probabilistic Projections of Sea-Level Rise

Contrast classes and agreement in climate modeling

Contact Info

Product

Resources

About