Embracing Climate Change through Painting: A Scientific and Artistic Collaboration

In an era of pressing environmental challenges, the fusion of art and science offers a powerful medium for deepening individual and public understanding and emotional engagement with global issues. This presentation explores the intersection of climate science and art through the collaborative efforts of a climate scientist and a painter/teacher. Building on the scientific findings of the SEARCH project, which investigates rates of change in past warm climates, we are using the emotional and cognitive power of art to promote a deeper awareness of climate risks and the goals of the European Green Deal (GreenSCENT project), and to contribute to the education of the next generation of scientifically literate and emotionally engaged young people.

Our approach integrates the principles of Intuitive Vision Painting, an art form we have developed, inspired by the method founded by Michele Cassou, which emphasizes unrestricted choice and spontaneity in creative expression. By engaging participants through painting examples and video demonstrations of this form of spontaneous painting, we aim to make the scientific complexities of climate change more accessible and relatable. This method serves as a catalyst for participants to connect emotionally with the urgency of climate action, increasing their receptivity to the scientific narratives and policies surrounding climate adaptation.

Through this interdisciplinary collaboration, we demonstrate how combining scientific data with artistic practice can break down barriers to understanding and create a shared language that bridges the gap between abstract scientific concepts and personal, emotional experiences. Our presentation will include a brief overview of the results of the SEARCH project, examples of Intuitive Vision Painting, and hopefully an interactive discussion on how such artistic interventions can enhance public engagement and drive more effective communication strategies in the face of climate change.

References and Notes:

Advanced Climate Risk Education https://www.acre.blue

Mudelsee M (2014) Climate Time Series Analysis: Classical Statistical and Bootstrap Methods. Second Edition. Springer, Cham, xxxii + 454 pp.

Mudelsee M (2020) Statistical Analysis of Climate Extremes. Cambridge Univ. Press, Cambridge, xii + 200 pp.

Ólafsdóttir KB, Schulz M, Mudelsee M (2016) REDFIT-X: Cross-spectral analysis of unevenly spaced paleoclimate time series. Computers and Geosciences 91:11–18.

This work has been funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), project number 468589022 (SEARCH), within the SPP 2299, project number 441832482; and by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101036480 (GreenSCENT).