On the Prediction of Aerosol‐Cloud Interactions Within a Data‐Driven Framework

Aerosol‐cloud interactions (ACI) pose the largest uncertainty for climate projection. Among many challenges of understanding ACI, the question of whether ACI can be deterministically predicted has not been explicitly answered. Here we attempt to answer this question by predicting cloud droplet numbe...

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Bibliographic Details
Published in:	Geophysical research letters Vol. 51; no. 24
Main Authors:	Li, Xiang‐Yu, Wang, Hailong, Chakraborty, TC, Sorooshian, Armin, Ziemba, Luke D., Voigt, Christiane, Thornhill, Kenneth Lee, Yuan, Emma
Format:	Journal Article
Language:	English
Published:	Washington John Wiley & Sons, Inc 28.12.2024 American Geophysical Union (AGU) Wiley
Subjects:	Aerosol clouds Aerosol concentrations Aerosol particles Aerosol properties Aerosols aerosol‐cloud interaction Climate Climate models Climate prediction Cloud droplet concentration Cloud droplets Clouds Crystals Data points Droplets ENVIRONMENTAL SCIENCES Ice Ice crystals Ice formation Learning algorithms Machine learning Meteorology Observational learning Predictions Questions Spatiotemporal data stochasticity Uncertainty Vertical velocities Water resources
ISSN:	0094-8276, 1944-8007
Online Access:	Get full text
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