Project Ukko: seasonal wind speed predictions at a glance

Introduction

Climate services provide made-to-measure climate information, tailored to the specific requirements of different users and industries. In the wind energy sector, understanding of wind conditions in the next few months has high economic value, for instance, for the energy traders. Current energy practices use retrospective climatology, but access to reliable seasonal predictions based in the recent advances in global climate models has potential to improve their resilience to climate variability and change.

Approach

Despite their potential benefits, a barrier to the development of commercially viable services is the complexity of the probabilistic forecast information, and the challenge of communicating complex and uncertain information to decision makers in industry.
Project Ukko is a prototype climate service to visually communicate probabilistic seasonal wind forecasts for the energy sector. In Project Ukko, an online interactive visualisation enhances the accessibility and readability to the latest advances in seasonal wind speed predictions developed as part of the RESILIENCE prototype of the EUPORIAS (EC FP7) project.

Main body of abstract

Project Ukko consists of an interactive climate service interface for wind energy users to explore probabilistic wind speed predictions for the coming season (www.project-ukko.net). This interface enables fast visual detection and exploration of interesting features and regions likely to experience unusual changes in wind speed in the coming months. The aim is not only to support users to better understand the future variability in wind power resources, but also to bridge the gap between practitioners’ traditional approach and the advanced prediction systems developed by the climate science community.

Conclusion

Project Ukko is presented as a case study of cross-disciplinary collaboration between climate science, design and energy users, for the development of climate services that are useful, usable and effective for wind industry.


Learning objectives
Energy decision-makers will gain insight into the advances in seasonal predictions of wind speed through a user friendly interface.