Aerosol–cloud interactions are the largest uncertainty in radiative forcing. We combined machine learning and long-term satellite observations to quantify aerosol fingerprints on tropical marine clouds, using degassing volcanic events in Hawaii as natural experiences, and found that cloud cover increased relatively by 50% in humid and stable atmosphere, leading to strong cooling radiative forcing.
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References
Chen, Y. et al. Machine learning reveals climate forcing from aerosols is dominated by increased cloud cover. Nat. Geosci. 15, 609–614 (2022). A research article that pioneered the machine-learning approach for disentangling the fingerprints of aerosols on clouds.
Ghan, S. et al. Challenges in constraining anthropogenic aerosol effects on cloud radiative forcing using present-day spatiotemporal variability. Proc. Natl Acad. Sci. USA 113, 5804–5811 (2016). A research article that summarizes the challenges in constraining aerosol–cloud interactions in global climate models using traditional observational evidence.
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This is a summary of: Chen, Y. et al. Substantial cooling effect from aerosol-induced increase in tropical marine cloud cover. Nat. Geosci. https://doi.org/10.1038/s41561-024-01427-z (2024).
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Evidence of strong aerosol cooling implies great efficacy of marine cloud brightening. Nat. Geosci. (2024). https://doi.org/10.1038/s41561-024-01428-y
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DOI: https://doi.org/10.1038/s41561-024-01428-y
