Extreme weather events, such as droughts, floods and shifting monsoon patterns, are becoming more frequent globally. To assess future risks, scientists rely on climate models, whose accuracy is often constrained by complex processes within the climate system that are difficult to simulate. Clouds, which typically cover much of the sky and strongly influence global temperatures, are among the largest sources of uncertainty in these models.
Researchers aim to bridge this knowledge gap. One of them is Mayur Sapkal, a Pioneer Fellow at ETH Zurich, who is working on the RepliClouds project. He has developed an instrument that accurately replicates the conditions for cloud droplet formation, enabling scientists to study this process precisely in laboratory settings, during field measurements, or at atmospheric observatories.
The term “RepliClouds” embodies the goal of mimicking natural conditions in intricate detail to enhance our understanding of them. More precise data on how cloud droplets develop on tiny particles can greatly refine climate models. This leads to a more dependable foundation for long-term planning, especially for communities already hardest hit by the effects of climate change.