1. Using Sound to Represent Uncertainty in UK Climate Predictions 2009 Data: Communication of Uncertainty Nick Bearman Phil Jones Andrew Lovett

2. Uncertainty All data have some uncertainty but it is often not represented or used in a particularly helpful way People* generally are not comfortable with the concept of uncertainty Mobile phones & cancer / carcinogenicity Nuclear power stations & earthquakes 29 June 2011

3. It is something people deal with in their everyday lives: Travelling (car / train / air) Smoking Betting Pensions / investments whether they are aware of it or not So everyone can understand it….. in some situations Uncertainty 29 June 2011

4. Uncertainty & UK Climate Predictions There is uncertainty in future climate predictions CCIRG91, CCIRG96, UKCIP98, UKCIP02, UKCP09 The first four only provided a single prediction value (for specific time, place, emissions scenario) UKCP09 provides a range of values 29 June 2011 Temperature Increase Probability Temperature Increase

5. UKCP09 - Uncertainty Uncertainty is useful But users have to change their workflow to make use of it The users need to be able to understand the data UKCIP have done a lot of training on this for users of UKCP09 They use the analogy of ‘horse race betting’ to explain how the probabilities work Which people are familiar with 29 June 2011 2.5 Existing Workflow 1.8, 2.0, 2.1, 2.1, 2.5, 2.6, 2.8

6. UKCP09 - Projections UKCP09 data consists of projections of future climate List of probabilities and values Need to view the value (e.g. temperature) and the probability distribution to fully understand how accurate the temperature prediction is Large amount of information to show So calculate a range instead (90 th – 10 th percentile) Can do this visually but limits on what can be shown 29 June 2011 Temperature Increase Probability

7. Representing Uncertainty Why sound? Easy – most computers have sound cards Cheap – only need headphones / speakers Played relevant sound as mouse moved over map Asked users to highlight areas above specific threshold Summer mean daily temperature for each cell 50 th percentile (≈ mean) Range (≈ uncertainty) Used Google Maps interface for the evaluation 29 June 2011

13. Results – How does sound help represent uncertainty? Participants (n = 71) from UEA, OS & UKCIP Usefulness of sound varied widely Some found it very helpful, some couldn’t stand it Knowledge of data set important (p < 0.001) Using sound to reinforce vision increases scores (p = 0.005) for most Choosing the correct sonification method is crucial for understanding the data Only general findings, but there is potential to extend this sonification to show more data (e.g. the distribution of the probabilities) or for public engagement 29 June 2011

14. Thanks to participants

15. Visual Saturation 29 June 2011 http://kbark.wordpress.com/2006/12/17/where-am-i/http://kbark.wordpress.com/2006/12/17/where-am-i/ (18/03/2009) Finnish Town

16. Results Compared users results to the correct results Great variation within results Cluster C had a very visual learning style Awareness of data set is important (p < 0.001) Using sound to reinforce vision increases scores (p = 0.005) for most Using sound for different variable helps some but not others Learning Style – Visual learners more effective Not significant trends: Subject knowledge Repeated use