1. Visualisation and communication of uncertainty and risk
Marta Terrado, Isadora Christel (BSC), Ghislain Dubois, Sébastien Bruyère (TEC Conseil), Jaroslav Mysiak (CMCC/U. Ca’Foscari), Josep Maria Solé (Meteosim SL), Stefano Bagli (Gecosistema)

2. EUPORIAS: Lessons learnt
Seasonal forecasts can be useful but are not easy to access or understand ▼
Skill (forecast quality/uncertainty) is not communicated effectively ▼
Users prefer visualisations that are familiar to them
EUPORIAS Project was the first clear attempt to develop visualisations to better describe the uncertainty and risk of using climate knowledge. The project developed different case studies, and some of them resulted in prototypes, such as LMTool, a climate service addressed to farmers or project Ukko, addressed to wind energy users. Some lessons learnt from the EUPORIAS project were: (list them)
Users need tailored forecasts
Need of communication formats suitable for both expert and non-expert users

3. Lessons learnt in EUPORIAS integrated in other projects
The lessons learnt in EUPORIAS have been integrated in the development of tools in subsequent projects

4. Decision Support Tools
Renewable energy
Tourism
Agriculture
Sector
Agriculture/Water/Energy
High
> Power producers
> Energy traders
> TSOs
> Snowmakers
> Consultants
Low
> Farmers
> Agronomists
Technical level
> Irrigation Authorities
> Water Managers
User
participation
High
> Interviews/focus group (feedback on previous work)
> Eye tracking test prototype
> Test of interactive prototype
> Local working group sessions in the ski resorts
> Feedback on the tool
> Multi-User Forums
> Co-design and co-development
In the case of some of the tools, they are addressed to users that have high technical level, meaning that they have some background in using probabilistic data, but in some cases, such as VISCA, it is addressed to users that are not necessarily familiar with probabilistic data.
User participation is quite unanimous. All the DSTs have counted with high user involvement, either through interviews and focus groups, testing the prototypes, or providing feedback on the tool.
Although desired, the participation of experts in visualisation is high in some projects and low in others. Even though visualisation is regarded as a very important asset, the interaction between climate scientists and visualisation experts is always challenging. On one hand, visualisation experts are not climate experts and they need to learn how to interpret climate data, and on the other hand climate scientists are not aware that visualisation is a field of expertise that considers many aspects that are not always obvious for them
High involvement
> Data visualisation
> Designers
Medium/High involvement
> Visualisation
Visualisation experts
> Web-GUI co-designed

5. Showing probability and skill
The lessons learnt in EUPORIAS have been integrated in the development of tools in subsequent projects

6. Showing probability and skill - DST energy▼
Terciles – Define probability threshold. Only locations with a higher probability in the most likely tercile are shown ▼
RPSS skill score. View all values or hide forecasts below a selected value ▼
Extremes probability

7. ▼ Progressive disclosure of information ▼
Advanced panel. Additional information on the forecast trend (all time windows) and information on past forecasts and observations.
Basic panel. Opens when selecting forecast for a particular location and variable ▼
Because not all users – even within the same sector – have different background, the type of information that will be useful to them differs. While some users may prefer to see a summary of the main information regarding the prediction, others may prefer to see more detailed data. Here is when the use of a progressive disclosure of information is useful.

8. Showing probability and skill - DST tourism
Colors showing the level of certainty of the prediction. Green: >80% probability, Orange: between 50%-80% probability, Red: <50% probability ▼
Quantile curve - Snow depth threshold. Customised to each ski resort (level under which the service should send a warning) ▼ ▼
No skill shown. Technicians said they don’t want to deal with skill values – only taking certain predictions into account

9. ▼ Progressive disclosure of information ▼
Advanced panel. Additional information for a particular slope in terms regarding different variables and risk of lack of information depending on the probability
Basic panel. View with aggregated figures and mean values ▼

10. Showing probability and skill - DSS agriculture
RPSS skill score value. Value of skill appears when hovering the mouse over the histograms ▼ ▼
Use of terciles. Showing percentage probability of below normal, normal and above normal when RPSS>0; otherwise, the climatology is shown.

11. All information shown in the main interface
Complete panel. Users expressed their desire of reducing the number of clicks. ▼

12. Showing probability and skill - DSS water
IRRICLIME ▼
Use of statistical boxplot. Show seasonal forecast of soil water budget

13. Decision Support Tools
Yes
> Basic view
> Advanced view (temporal evolution, historical analysis)
> Basic view (aggregated information)
> Advanced view No
Progressive disclosure of information
Probabilities
Terciles
Extreme values
Quantile curves
customised thresholds
Boxplots
4 H2020 projects
Skill
Yes No

14. Conclusion
Trying to be generic doesn’t provide a useful service to anyone. Each user is different and it is important to tailor the service to user needs.
A salient service might need to leave out of the visualisation some scientific knowledge. Good to have a progressive disclosure of information.
Working with users is necessary to develop a useful climate service. Data visualisation experts and designers can help develop a clearer and more appealing interface for users.

15. Thank you
The projects participating in this presentation have received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreements n° (S2S4E), nº (PROSNOW), nº (VISCA) and (CLARA).
The content of this presentation reflects only the author’s view. The European Commission is not responsible for any use that may be made of the information it contains.