Communicating Climate Change Data: What Is the Right Format to Change People’s Behaviour?

  • Andrew ThatcherEmail author
  • Keren-Amy Laughton
  • Kaylin Adamson
  • Coleen Vogel
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 825)


This study looks at a comparison of three data formats for the communication of climate change information; a dynamic visual representation, tables and charts, and pictures. Using design principles which are largely drawn from the field of cognitive ergonomics, good examples of each data format that represented a local climate change issue were identified. A sample of 453 students was randomly assigned to one of the three data format conditions and compared on their understanding and comprehension of the data format information and their motivation to act to mitigate the effects of climate change. Results suggest that there was no clear “best” data format, although tables and charts were likely to have the most consistently positive impact. These results are discussed in the context of climate change communication.


Green ergonomics Climate change Communication formats 


  1. Bord RJ, O’Connor RE, Fisher A (2000) In what sense does the public need to understand global climate change? Pub Underst Sci 9:205–218CrossRefGoogle Scholar
  2. Campbell D (2007) Geopolitics and visuality: sighting the darfur conflict. Polit Geogr 26:357–382CrossRefGoogle Scholar
  3. Chapman DA, Corner A, Webster R, Markowitz EM (2016) Climate visuals: a mixed methods investigation of public perceptions of climate images in three countries. Glob Environ Change 41:172–182CrossRefGoogle Scholar
  4. Daron JD, Lorenz S, Wolski P, Blamey RC, Jack C (2015) Interpreting climate data visualisations to inform adaptation decisions. Clim Risk Manag 10:17–26CrossRefGoogle Scholar
  5. Gamson WA, Modigliani A (1989) Media discourse and public opinion on nuclear power: a constructionist approach. Am J Soc 95:1–37CrossRefGoogle Scholar
  6. Gasper D, Portocarrero AV, St. Clair AL (2013) The framing of CC and development: a comparative analysis of the human development report 2007/8 and the world development report 2010. Glob Environ Change 23:28–39CrossRefGoogle Scholar
  7. Graber DA (1990) Seeing is remembering: how visuals contribute to learning from television news. J Commun 40:134–156CrossRefGoogle Scholar
  8. Harold J, Lorenzoni I, Shipley T, Coventry K (2016) Cognitive and psychological science insights to improve climate change data visualisation. Nat Clim Change 6:1080–1089CrossRefGoogle Scholar
  9. Hegarty M (2011) The cognitive science of visual-spatial displays: implications for design. Top Cogn Sci 3:446–474CrossRefGoogle Scholar
  10. Hope KR (2009) Climate change and urban development in Africa. Int J Environ Stud 66:643–658CrossRefGoogle Scholar
  11. Joffe H (2008) The power of visual material: persuasion, emotion and identification. Diogenes 55:84–93CrossRefGoogle Scholar
  12. Ladstädter F, Steiner AK, Lackner BC, Pirscher B, Kirchengast G, Kehrer J, Doleisch H (2010) Exploration of climate data using interactive visualization. J Atmos Oceanic Technol 27:667–679CrossRefGoogle Scholar
  13. Leiserowitz A (2006) Climate change risk perception and policy preferences: the role of affect, imagery, and values. Clim Change 77:45–72CrossRefGoogle Scholar
  14. Liberman N, Trope Y, Stephan E (2007) Psychological distance. In: Kruglanski AW, Higgins ET (eds) Social psychology: handbook of basic principles. The Guildford Press, New York, pp 353–383Google Scholar
  15. Lorenz S, Dessai S, Forster PM, Paavola J (2015) Tailoring the visual communication of climate projections for local adaptation practitioners in Germany and the UK. Philosphical Trans Roy Soc A 373(2055):20140457CrossRefGoogle Scholar
  16. Lorenzoni I, Nicholson-Cole S, Whitmarsh L (2007) Barriers perceived to engaging with climate change among the UK public and their policy implications. Glob Environ Change 17:445–459CrossRefGoogle Scholar
  17. Maloney MP, Ward MP, Braucht GN (1975) A revised scale for the measurement of ecological attitudes and knowledge. Am Psychol 30:787–790CrossRefGoogle Scholar
  18. Moser SC (2010) Communicating climate change: history, challenges, process and future directions. Wiley Interdisc Rev Clim Change 1:31–53CrossRefGoogle Scholar
  19. Nocke T, Flechsig M, Bohm U (2007) Visual exploration and evaluation of climate-related simulation data. In: Simulation conference, 2007 Winter. IEEE, Washington, pp 703–711, December 2007Google Scholar
  20. O’Neill SJ (2013) Image matters: climate change imagery in US, UK and Australian newspapers. Geoforum 49:10–19CrossRefGoogle Scholar
  21. O’Neill S, Nicholson-Cole S (2009) “Fear won’t do it”. Promoting positive engagement with climate change through visual and iconic representations. Sci Commun 30:355–379CrossRefGoogle Scholar
  22. Retchless DP, Brewer CA (2016) Guidance for representing uncertainty on global temperature change maps. Int J Climatol 36:1143–1159CrossRefGoogle Scholar
  23. Retief JV, Diamantidis D, Barnardo-Viljoen C, van der Klashorst E (2014) Extreme actions and climate change: experience gained in South Africa and Germany. Civil Eng Environ Syst 31:179–188CrossRefGoogle Scholar
  24. Scannell L, Gifford R (2013) Personally relevant climate change: the role of place attachment and local versus global message framing in engagement. Environ Behav 45:60–85CrossRefGoogle Scholar
  25. Schneider B (2011) Image politics: picturing uncertainty. The role of images in climatology and climate policy. In: Climate change and policy. Springer, Berlin, pp 191–209Google Scholar
  26. Slocum TA, Blok C, Jiang B, Koussoulakou A, Montello DR, Fuhrmann S, Hedley NR (2001) Cognitive and usability issues in geovisualization. Cartography Geograph Inf Sci 28:61–75CrossRefGoogle Scholar
  27. Stoll-Kleemann S, O’Riordan T, Jaeger CC (2001) The psychology of denial concerning climate mitigation measures: evidence from Swiss focus groups. Glob Environ Change 11:107–117CrossRefGoogle Scholar
  28. Taylor AL, Dessai S, de Bruin WB (2015) Communicating uncertainty in seasonal and interannual climate forecasts in Europe. Philosphical Trans Roy Soc A 373(2055):20140454CrossRefGoogle Scholar
  29. Thatcher A (2013) Green ergonomics: definition and scope. Ergonomics 56:389–398CrossRefGoogle Scholar
  30. Tominski C, Donges JF, Nocke T (2011) Information visualization in climate research. In: Information visualisation (IV), 15th international conference on information visualisation. IEEE Computer Society, Washington, pp 298–305, July 2011Google Scholar
  31. Whitmarsh L, O’Neill S (2010) Green identity, green living? The role of pro-environmental self-identity in determining consistency across diverse pro-environmental behaviours. J Environ Psychol 30:305–314CrossRefGoogle Scholar
  32. Wright CY, Garland RM, Norval M, Vogel C (2014) Human health impacts in a changing South African climate. S Afr Med J 104:568–573CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Andrew Thatcher
    • 1
    Email author
  • Keren-Amy Laughton
    • 1
  • Kaylin Adamson
    • 1
  • Coleen Vogel
    • 2
  1. 1.Psychology DepartmentUniversity of the Witwatersrand, WITSJohannesburgSouth Africa
  2. 2.Global Change InstituteUniversity of the Witwatersrand, WITSJohannesburgSouth Africa

Personalised recommendations