Wageningen University & Research held a three-day training (13-15 March 2017) in Wageningen on the application of climate model projections in different decision maker’s contexts. In total 22 participants worked during this training in real life decision making contexts and worked with hands-on exercises to find, access, process and analyze climate data relevant to the problem at hand. The decision making context was based on case studies provided by most of the attendees.
The objectives of the training was to get acquainted with several climate impact data portals, assess usability for their use case and provide feedback to developers on usability. This training was built on experiences gained in previous, similar courses and used data search and access services developed and provided by:
- Climate4Impact, Exploring climate model data
- CLIPC, climate information portal
- SWICCA, Service for Water Indicators in Climate Change Adaptation
- International Research Institute for Climate Society, Earth Institute, Columbia University
During the training the participants presented their case studies to identify the user needs on climate data. Other presentations were: Climate and impact indicators: selecting models, scenarios and socio economic data; short introduction to the Copernicus Climate Change Service project of SWICCA, its goal, the show cases and the functioning of the Demonstrator. The participants used the Demonstrator to learn, find, process and analyse the climate data for their own case. Delete: Also an exercise in which the seasonal climate forecasts from the IRI portal was given.
The training was shortly evaluated. All respondents rated the overall quality of the training and the way it was organised and accommodated as good to excellent. Other questions in the evaluation and answers were e.g.:
- What was the most interesting part you learned in this training?: The attendants found that the European / global datasets and tools shown were very instructive. Each session was followed by an interesting discussion.
- What were the least interesting topics?: Seasonability and meteorological data, live combination of maps, some of the discussions on uncertainty were too long.
- What would have made the training more effective?: The answers varied from none to a tutorial from start to finish.
- What should the next learning event for the “knowledge purveyors network” be about? And with whom?: Invite speakers not only from academia, but also outside the academia to make it even more useful.