Machine Learning Uncovers Aerosol Size Information From Chemistry and Meteorology to Quantify Potential Cloud-Forming Particles

Nair, A. A., F. Yu, P. Campuzano-Jost, P. J. DeMott, E. J. T. Levin, J. L. Jimenez, J. Peischl, I. B. Pollack, C. D. Fredrickson, A. J. Beyersdorf, B. A. Nault, M. Park, S. S. Yum, B. B. Palm, L. Xu, I. Bourgeois, B. E. Anderson, A. Nenes, L. D. Ziemba, R. H. Moore, T. Lee, T. Park, C. R. Thompson, F. Flocke, L. G. Huey, M. J. Kim, and Q. Peng, 2021: Machine Learning Uncovers Aerosol Size Information From Chemistry and Meteorology to Quantify Potential Cloud-Forming Particles. Geophysical Research Letters, 48, e2021GL094133, doi: 10.1029/2021GL094133.