Climate data, in all its dimensions, is too often reduced to static maps or single-layer charts: simplicity mistaken for clarity. In this talk, I share visual explorations that enrich datasets by combining atmospheric variables, satellite imagery, and geographical processes into short, unfolding narratives. Rather than simplifying, the aim is to embrace complexity. In doing so we can help bridge the gap between scientific insight and public understanding.
While animation introduces the dimension of time, guiding the viewer through change and scale, techniques like Gaussian splatting open up the dimension of space, allowing data to be explored from different angles and perspectives. Together, they can reveal relationships that remain hidden in static views, while keeping uncertainty and data limitations visible.
Rather than a strict scientific analysis, this talk is a collection of visual experiments and workflows—an iterative, hands-on approach to discovering new ways of exploring and communicating climate data.