When is an Ensemble like a Sample? ‘Model-Based’ Inferences in Climate Modeling

authored by

Corey Nathaniel Dethier

Abstract

Climate scientists often apply statistical tools to a set of different estimates generated by an “ensemble” of models. In this paper, I argue that the resulting inferences are justified in the same way as any other statistical inference: what must be demonstrated is that the statistical model that licenses the inferences accurately represents the probabilistic relationship between data and target. This view of statistical practice is appropriately termed “model-based,” and I examine the use of statistics in climate fingerprinting to show how the difficulties that climate scientists encounter in applying statistics to ensemble-generated data are the practical difficulties of normal statistical practice. The upshot is that whether the application of statistics to ensemble-generated data yields trustworthy results should be expected to vary from case to case.

Organisation(s)

Graduiertenkolleg 2073/1

Type

Article

Journal

Synthese

Volume

200

ISSN

0039-7857

Publication date

28.02.2022

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Social Sciences(all), Philosophy

Sustainable Development Goals

SDG 13 - Climate Action

Electronic version(s)

https://doi.org/10.1007/s11229-022-03477-5 (Access: Open)