Machine learning reveals climate forcing from aerosols is dominated by increased cloud cover

• Published in: Nature Geoscience
• Main Authors: Chen, Ying, Haywood, Jim, Wang, Yu, Malavelle, Florent, Jordan, George, Partridge, Daniel, Fieldsend, Jonathan, De Leeuw, Johannes, Schmidt, Anja, Cho, Nayeong, Oreopoulos, Lazaros, Platnick, Steven, Grosvenor, Daniel P., Field, Paul, Lohmann, Ulrike
• Format: Article in Journal/Newspaper
• Language: English
• Published: Nature Publishing Group 2022
• Subjects: Erdsystem-Modellierung; Holuhraun; Iceland
• Online Access: https://elib.dlr.de/198390/; https://elib.dlr.de/198390/2/198390_PA_infotext.pdf; https://doi.org/10.1038/s41561-022-00991-6

Aerosol–cloud interactions have a potentially large impact on climate but are poorly quantified and thus contribute a substantial and long-standing uncertainty in climate projections. The impacts derived from climate models are poorly constrained by observations because retrieving robust large-scale...