Dr Yu Wang, from the School of GeoSciences at the University of Edinburgh, has led a new international study published in Nature Communications examining how well global climate models capture the way clouds respond to aerosols, which play a crucial role in regulating Earth’s climate. How do aerosols create clouds? Aerosols – tiny particles suspended in the air - which can come from both natural sources such as sea spray, dust and volcanic ash and human activities such as pollution, help form clouds by acting as ‘seeds’ - known as Cloud Condensation Nuclei (CCN) – giving water vapour something to cling to as it cools and turns into cloud droplets. The number of these particles affects how bright, long-lasting and reflective clouds are. By influencing cloud brightness, coverage and how long-lasting they are, aerosols affect how much sunlight clouds are able to reflect back into space and how much heat is trapped in the atmosphere. These aerosol–cloud interactions are therefore central to understanding climate sensitivity and predicting future warming. Uncertainty in cloud response to aerosols Despite their importance, cloud responses to aerosols remain one of the largest sources of uncertainty in climate models. To address this, the team took six state-of-the-art global climate models and benchmarked them against a large-scale, observation-based constraint. This constraint was developed in a previous study (Chen et al., 2022)1, using machine-learning techniques and satellite observations of cloud changes following the 2014 Holuhraun volcanic eruption in Iceland, which released large amounts of aerosols into the atmosphere.The team found that while models reasonably capture changes in cloud optical depth (a proxy of cloud albedo), all models systematically underestimate cloud cover responses to aerosol changes. This suggests that the models misrepresent cloud changes, therefore causing uncertainty when looking at how precipitation and radiation balance has responded in the past, or will respond in future predictions. This underestimation has important implications for predicting future warming and climate sensitivity. Improving climate prediction models The results highlight a key research gap in understanding aerosol–cloud interactions and provide insights for improving cloud schemes in climate models. Better representation of clouds is essential for reducing uncertainty in projections of future climate change, and for strengthening the scientific basis of climate mitigation and adaptation policies. Accurately capturing aerosol–cloud interactions are essential for reliable climate projections. Our study shows that underestimating cloud cover responses to aerosols could have important consequences for understanding past and future climate change. Dr Yu Wang Lecturer in Environmental Science, School of GeoSciences Related links Read the full paper: https://www.nature.com/articles/s41467-025-67359-3 References Chen, Y., Haywood, J., Wang, Y., Malavelle, F., Jordan, G., Partridge, D., Fieldsend, J., De Leeuw, J., Schmidt, A., Cho, N., Oreopoulos, L., Platnick, S., Grosvenor, D., Field, P., and Lohmann, U.: Machine learning reveals climate forcing from aerosols is dominated by increased cloud cover, Nature Geoscience, 15, 609-614, 10.1038/s41561-022-00991-6, 2022. Publication date 11 Feb, 2026
