Daron, J, Lorenz, S orcid.org/0000-0002-9124-9690, Taylor, A orcid.org/0000-0002-8949-1234 et al. (1 more author) (2021) Communicating future climate projections of precipitation change. Climatic Change, 166 (1-2). 23. ISSN 0165-0009
Abstract
Understanding how precipitation may change in the future is important for guiding climate change adaptation. Climate models are the primary tools for providing information on future precipitation change, though communicating and interpreting results of different model simulations is challenging. Using an online survey, completed by producers and users of climate model information, we compare and evaluate interpretations of different approaches used to summarise and visualise future climate projections. Results reveal large differences in interpretations of precipitation change arising from choices made in summarising and visualising the data. Respondents interpret significantly smaller ranges of future precipitation change when provided with the multi-model ensemble mean or percentile information, which are commonly used to summarise climate model projections, compared to information about the full ensemble. The ensemble mean is found to be particularly misleading, even when used with information to show model agreement in the sign of change. We conclude that these approaches can lead to distorted interpretations which may impact on adaptation policy and decision-making. To help improve the interpretation and use of climate projections in decision-making, regular testing of visualisations and sustained engagement with target audiences is required to determine the most effective and appropriate visualisation approaches.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021, The Author(s). This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Interpretation, Visualisation, Uncertainties, Ensembles |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Business (Leeds) > Management Division (LUBS) (Leeds) > Management Division Decision Research (LUBS) 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: | 19 May 2021 11:06 |
Last Modified: | 27 Feb 2023 16:03 |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1007/s10584-021-03118-9 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:174119 |