Uncertainty: Nothing is more certain

Cripps, S; Durrant-Whyte, H

Uncertainty: Nothing is more certain

Cripps, S

Durrant-Whyte, H

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Publisher:: WILEY
Publication Type:: Journal Article
Citation:: Environmetrics, 2023, 34, (1)
Issue Date:: 2023-02-01

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Field	Value	Language
dc.contributor.author	Cripps, S https://orcid.org/0000-0003-3207-172X
dc.contributor.author	Durrant-Whyte, H
dc.date.accessioned	2024-05-29T21:47:54Z
dc.date.available	2024-05-29T21:47:54Z
dc.date.issued	2023-02-01
dc.identifier.citation	Environmetrics, 2023, 34, (1)
dc.identifier.issn	1180-4009
dc.identifier.issn	1099-095X
dc.identifier.uri	http://hdl.handle.net/10453/179337
dc.description.abstract	This articles discusses the importance and types of uncertainty in environmental science. Uncertainty is categorized into four types, three of which are familiar to statisticians and one of which is introduced by the authors as knowledge uncertainty. The article claims that the Bayesian paradigm is a logically consistent mechanism, and a useful framework for decision makers in environmental science, to manage and quantify the first three types of uncertainty. However knowledge uncertainty, common in environmental sciences, requires more detailed thought and more nuanced management strategies for robust decision making in the environment. The article concludes with the observation that only if we acknowledge the uncertainty inherent in inferring complex quantities from data can we make robust and explainable policy decisions that build trust with the public.
dc.language	English
dc.publisher	WILEY
dc.relation.ispartof	Environmetrics
dc.relation.isbasedon	10.1002/env.2745
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	01 Mathematical Sciences, 05 Environmental Sciences
dc.subject.classification	Statistics & Probability
dc.subject.classification	41 Environmental sciences
dc.subject.classification	49 Mathematical sciences
dc.title	Uncertainty: Nothing is more certain
dc.type	Journal Article
utslib.citation.volume	34
utslib.for	01 Mathematical Sciences
utslib.for	05 Environmental Sciences
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Provost
utslib.copyright.status	open_access	*
dc.rights.license	This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0). To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.date.updated	2024-05-29T21:47:53Z
pubs.issue	1
pubs.publication-status	Published
pubs.volume	34
utslib.citation.issue	1

Abstract:

This articles discusses the importance and types of uncertainty in environmental science. Uncertainty is categorized into four types, three of which are familiar to statisticians and one of which is introduced by the authors as knowledge uncertainty. The article claims that the Bayesian paradigm is a logically consistent mechanism, and a useful framework for decision makers in environmental science, to manage and quantify the first three types of uncertainty. However knowledge uncertainty, common in environmental sciences, requires more detailed thought and more nuanced management strategies for robust decision making in the environment. The article concludes with the observation that only if we acknowledge the uncertainty inherent in inferring complex quantities from data can we make robust and explainable policy decisions that build trust with the public.

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http://hdl.handle.net/10453/179337