Details
Original language | English |
---|---|
Article number | 15 |
Journal | CLIMATIC CHANGE |
Volume | 169 |
Issue number | 1-2 |
Publication status | Published - 25 Nov 2021 |
Abstract
When do probability distribution functions (PDFs) about future climate misrepresent uncertainty? How can we recognise when such misrepresentation occurs and thus avoid it in reasoning about or communicating our uncertainty? And when we should not use a PDF, what should we do instead? In this paper, we address these three questions. We start by providing a classification of types of uncertainty and using this classification to illustrate when PDFs misrepresent our uncertainty in a way that may adversely affect decisions. We then discuss when it is reasonable and appropriate to use a PDF to reason about or communicate uncertainty about climate. We consider two perspectives on this issue. On one, which we argue is preferable, available theory and evidence in climate science basically exclude using PDFs to represent our uncertainty. On the other, PDFs can legitimately be provided when resting on appropriate expert judgement and recognition of associated risks. Once we have specified the border between appropriate and inappropriate uses of PDFs, we explore alternatives to their use. We briefly describe two formal alternatives, namely imprecise probabilities and possibilistic distribution functions, as well as informal possibilistic alternatives. We suggest that the possibilistic alternatives are preferable.
Keywords
- Climate projection, Deep uncertainty, Possibility theory, Probability, Uncertainty representations
ASJC Scopus subject areas
- Environmental Science(all)
- Global and Planetary Change
- Earth and Planetary Sciences(all)
- Atmospheric Science
Sustainable Development Goals
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In: CLIMATIC CHANGE, Vol. 169, No. 1-2, 15, 25.11.2021.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - On the appropriate and inappropriate uses of probability distributions in climate projections and some alternatives
AU - Katzav, Joel
AU - Thompson, Erica L.
AU - Risbey, James
AU - Stainforth, David A.
AU - Bradley, Seamus
AU - Frisch, Mathias
N1 - David A. Stainforth. The U.K. Economic and Social Research Council (ES/R009708/1) Centre for Climate Change. Economics and Policy (CCCEP); The Grantham Research Institute on Climate Change and the Environment. James Risbey. The Decadal Climate Forecast Project at CSIRO.
PY - 2021/11/25
Y1 - 2021/11/25
N2 - When do probability distribution functions (PDFs) about future climate misrepresent uncertainty? How can we recognise when such misrepresentation occurs and thus avoid it in reasoning about or communicating our uncertainty? And when we should not use a PDF, what should we do instead? In this paper, we address these three questions. We start by providing a classification of types of uncertainty and using this classification to illustrate when PDFs misrepresent our uncertainty in a way that may adversely affect decisions. We then discuss when it is reasonable and appropriate to use a PDF to reason about or communicate uncertainty about climate. We consider two perspectives on this issue. On one, which we argue is preferable, available theory and evidence in climate science basically exclude using PDFs to represent our uncertainty. On the other, PDFs can legitimately be provided when resting on appropriate expert judgement and recognition of associated risks. Once we have specified the border between appropriate and inappropriate uses of PDFs, we explore alternatives to their use. We briefly describe two formal alternatives, namely imprecise probabilities and possibilistic distribution functions, as well as informal possibilistic alternatives. We suggest that the possibilistic alternatives are preferable.
AB - When do probability distribution functions (PDFs) about future climate misrepresent uncertainty? How can we recognise when such misrepresentation occurs and thus avoid it in reasoning about or communicating our uncertainty? And when we should not use a PDF, what should we do instead? In this paper, we address these three questions. We start by providing a classification of types of uncertainty and using this classification to illustrate when PDFs misrepresent our uncertainty in a way that may adversely affect decisions. We then discuss when it is reasonable and appropriate to use a PDF to reason about or communicate uncertainty about climate. We consider two perspectives on this issue. On one, which we argue is preferable, available theory and evidence in climate science basically exclude using PDFs to represent our uncertainty. On the other, PDFs can legitimately be provided when resting on appropriate expert judgement and recognition of associated risks. Once we have specified the border between appropriate and inappropriate uses of PDFs, we explore alternatives to their use. We briefly describe two formal alternatives, namely imprecise probabilities and possibilistic distribution functions, as well as informal possibilistic alternatives. We suggest that the possibilistic alternatives are preferable.
KW - Climate projection
KW - Deep uncertainty
KW - Possibility theory
KW - Probability
KW - Uncertainty representations
UR - http://www.scopus.com/inward/record.url?scp=85120674204&partnerID=8YFLogxK
U2 - 10.1007/s10584-021-03267-x
DO - 10.1007/s10584-021-03267-x
M3 - Article
AN - SCOPUS:85120674204
VL - 169
JO - CLIMATIC CHANGE
JF - CLIMATIC CHANGE
SN - 0165-0009
IS - 1-2
M1 - 15
ER -