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Abstract: Machine Learning derived CCN concentrations better constrain aerosol-cloud interactions than aerosol optical properties (AGU25)

Machine Learning derived CCN concentrations better constrain aerosol-cloud interactions than aerosol optical properties

Dr. Lan Gao1, Jens Redemann2, Emily Lenhardt3, Benting Chen4, Feng Xu5, Richard Anthony Ferrare6, Johnathan W Hair6, Amin R Nehrir7, Chris A Hostetler6, Taylor Shingler7, Marta A Fenn8, Brian Cairns9 and Armin Sorooshian10, (1)University of Oklahoma Norman Campus, Meteorology, Norman, United States, (2)University of Oklahoma, School of Meteorology, Norman, United States, (3)University of Oklahoma Norman Campus, Norman, United States, (4)University of Oklahoma, Norman, United States, (5)University of Oklahoma, School of Meteorology, Norman, OK, United States, (6)NASA Langley Research Center, Hampton, VA, United States, (7)NASA Langley Research Center, Hampton, United States, (8)Coherent Applications, Inc. -Psionic, LLC, Hampton, United States, (9)NASA Goddard Institute for Space Studies, New York, NY, United States, (10)University of Arizona, Department of Chemical and Environmental Engineering, Tucson, AZ, United States