Baldissera Pacchetti, M orcid.org/0000-0002-5867-6893, Dessai, S orcid.org/0000-0002-7879-9364, Stainforth, DA et al. (1 more author) (2021) Assessing the quality of state-of-the-art regional climate information: the case of the UK Climate Projections 2018. Climatic Change, 168 (1-2). 1. ISSN 0165-0009
Abstract
In this paper, we assess the quality of state-of-the-art regional climate information intended to support climate adaptation decision-making. We use the UK Climate Projections 2018 as an example of such information. Their probabilistic, global, and regional land projections exemplify some of the key methodologies that are at the forefront of constructing regional climate information for decision support in adapting to a changing climate. We assess the quality of the evidence and the methodology used to support their statements about future regional climate along six quality dimensions: transparency; theory; independence, number, and comprehensiveness of evidence; and historical empirical adequacy. The assessment produced two major insights. First, a major issue that taints the quality of UKCP18 is the lack of transparency, which is particularly problematic since the information is directed towards non-expert users who would need to develop technical skills to evaluate the quality and epistemic reliability of this information. Second, the probabilistic projections are of lower quality than the global projections because the former lack both transparency and a theory underpinning the method used to produce quantified uncertainty estimates about future climate. The assessment also shows how different dimensions are satisfied depending on the evidence used, the methodology chosen to analyze the evidence, and the type of statements that are constructed in the different strands of UKCP18. This research highlights the importance of knowledge quality assessment of regional climate information that intends to support climate change adaptation decisions.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2021, corrected publication 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
Keywords: | Knowledge quality assessment; Regional climate information; Climate models; Uncertainty; Adaptation |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Sustainability Research Institute (SRI) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 27 Oct 2021 09:18 |
Last Modified: | 27 Oct 2021 09:18 |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1007/s10584-021-03187-w |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:179626 |
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