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Visualizations of Projected Rainfall Change in the United Kingdom: An Interview Study about User Perceptions

Author

Listed:
  • Astrid Kause

    (Centre for Decision Research, Leeds University Business School, Maurice Keyworth Building, University of Leeds, Leeds LS2 9JT, UK
    Priestley International Centre for Climate, School of Earth and Environment, University of Leeds, Leeds LS2 9JT, UK
    Harding Center for Risk Literacy, Max Planck Institute for Human Development, Lentzeallee 94, 14195 Berlin, Germany)

  • Wändi Bruine de Bruin

    (Sol Price School for Public Policy, Dornsife Department of Psychology, Schaeffer Center for Health Policy and Economics, and Center for Economic and Social Research, VPD 512D, 625 Downey Way, Los Angeles, CA 90089, USA)

  • Fai Fung

    (UK Met Office, Fitzroy Road, Exeter, Devon EX1 3PB, UK)

  • Andrea Taylor

    (Centre for Decision Research, Leeds University Business School, Maurice Keyworth Building, University of Leeds, Leeds LS2 9JT, UK
    Priestley International Centre for Climate, School of Earth and Environment, University of Leeds, Leeds LS2 9JT, UK)

  • Jason Lowe

    (Priestley International Centre for Climate, School of Earth and Environment, University of Leeds, Leeds LS2 9JT, UK
    UK Met Office, Fitzroy Road, Exeter, Devon EX1 3PB, UK)

Abstract

Stakeholders from public, private, and third sectors need to adapt to a changing climate. Communications about climate may be challenging, especially for audiences with limited climate expertise. Here, we study how such audience members perceive visualizations about projected future rainfall. In semi-structured interviews, we presented 24 participants from climate-conscious organizations across the UK with three prototypical visualizations about projected future rainfall, adopted from the probabilistic United Kingdom Climate Projections: (1) Maps displaying a central estimate and confidence intervals, (2) a line graph and boxplots displaying change over time and associated confidence intervals, and (3) a probability density function for distributions of rainfall change. We analyzed participants’ responses using “Thematic Analysis”. In our analysis, we identified features that facilitated understanding—such as colors, simple captions, and comparisons between different emission scenarios—and barriers that hindered understanding, such as unfamiliar acronyms and terminology, confusing usage of probabilistic estimates, and expressions of relative change in percentages. We integrate these findings with the interdisciplinary risk communication literature and suggest content-related and editorial strategies for effectively designing visualizations about uncertain climate projections for audiences with limited climate expertise. These strategies will help organizations such as National Met Services to effectively communicate about a changing climate.

Suggested Citation

  • Astrid Kause & Wändi Bruine de Bruin & Fai Fung & Andrea Taylor & Jason Lowe, 2020. "Visualizations of Projected Rainfall Change in the United Kingdom: An Interview Study about User Perceptions," Sustainability, MDPI, vol. 12(7), pages 1-21, April.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:7:p:2955-:d:342652
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    References listed on IDEAS

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    Cited by:

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    2. Wändi Bruine de Bruin & Andrew Dugan, 2022. "On the differential correlates of climate change concerns and severe weather concerns: evidence from the World Risk Poll," Climatic Change, Springer, vol. 171(3), pages 1-24, April.

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