Aerosol–cloud interactions (ACI) contribute most to the uncertainty in total anthropogenic forcing of the climate system. A reliable ACI estimate from observations is urgently needed to constrain climate models and enable better climate predictions. However, satellite-based estimates of ACI are subject to many uncertainties, such as the difficulty in identifying cloud-active aerosol and its anthropogenic perturbation, the cloud regime dependency of ACI, and satellite retrieval biases, which are rarely considered simultaneously in current estimates. Your project is to quantify and constrain all those uncertainties, with a focus on liquid clouds, by integrating diverse satellite and reanalysis datasets with targeted synthetic experiments using the ICON-A-HAM climate model. In combination with novel satellite retrievals from recently launched PACE and EarthCARE missions, your work will provide ‘optimal’ observational estimates of ACI and its forcing. These estimates will be used to evaluate and benchmark current climate models.

You will collaborate within a team of experts specializing in aerosol-cloud-climate modeling and observations, which offers a unique opportunity to gain hands-on experience in satellite data analysis and climate modeling. You will present your work at scientific conferences and publish your work in scientific peer reviewed journals.