Will reduce uncertainty in climate predictions

Researchers currently have relatively little knowledge about how the particles in the Earth’s atmosphere affect the climate. Wallenberg Academy Fellow Christina Williamson will develop techniques to investigate this. Her aim is to generate knowledge that can radically reduce uncertainty in current climate predictions. 

The atmosphere contains aerosols, such as desert dust or soot particles from combustion, which interact with both sunlight and clouds, thus affecting the Earth’s climate. However, researchers have relatively little knowledge about the role that the particles’ size, shape or location in the atmosphere, for example, play in atmospheric heating. This results in uncertainty in climate predictions. 

To make these predictions more certain, Dr Christina Williamson at the University of Colorado, Boulder, USA, will conduct a targeted investigation of the effects that different types of aerosol factors have on the climate. Using a technique, emulated perturbed parameter ensemble (EPPE), which is based on machine learning, she will first identify the aerosol factors that cause the greatest uncertainty in current predictions. Then she will use instruments, at ground stations and on research flights, that can measure how these aerosol factors affect the climate.

The knowledge she collects will contribute to radically improved predictions. In turn, this will provide a better foundation for all the decisions we must take mitigating and adapting to climate change

As a Wallenberg Academy Fellow, Christina Williamson will work at the University of Gothenburg. 

Photo: Josh Vertucci