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Session Proposal: Aerosol Impacts on Clouds: Assessment via AI and Statistical Methods (AGU25)

A018
Aerosol Impacts on Clouds: Assessment via AI and Statistical Methods

Session ID#: 247913

Session Description:
Aerosol–cloud interactions span a wide range of regimes and are influenced by complex adjustments and feedbacks across spatiotemporal scales. Recent advances in machine learning and data-driven techniques offer new pathways, in additon to traditional-statistics, to isolate causal aerosol effects, accelerate analysis of massive datasets, and advance process-level understanding of indirect effects and cloud adjustments. This session solicits contributions leveraging AI/ML and data-driven frameworks to dissect how aerosol perturbations modulate cloud microphysics, macrophysics, precipitation and radiative properties across diverse cloud regimes.We welcome studies employing, but not limited to: Causal inference and explainable AI to untangle aerosol effects in observational and model datasets; Deep learning for processing remote‑sensing, in‑situ or cloud‑resolving outputs; Emulators of aerosol and cloud processes trained from high‑fidelity simulations; Statistical analyses to quantify response patterns and uncertainties across regimes, etc.We encourage submissions of theoretical, observational, modeling and statistical methods to drive deeper understanding of aerosol‑cloud interactions.
Index Terms:

0305 Aerosols and particles [ATMOSPHERIC COMPOSITION AND STRUCTURE]
0320 Cloud physics and chemistry [ATMOSPHERIC COMPOSITION AND STRUCTURE]
1942 Machine learning [INFORMATICS]
3311 Clouds and aerosols [ATMOSPHERIC PROCESSES]
Primary Convener:  Xiaojian Zheng, Argonne National Laboratory, Argonne, IL, United States
Conveners:  Jianhao Zhang, National Oceanic and Atmospheric Administration (NOAA), Chemical Sciences Laboratory, Boulder, United States, Peng Wu, Pacific Northwest National Laboratory, Richland, WA, United States and Dié WANG, Brookhaven National Laboratory, Upton, NY, United States
Student/Early Career Convener:  Litai Kang, University of Washington, Department of Atmospheric and Climate Science, Seattle, United States
 
Factors Affecting Aerosol Activation to Cloud Droplets and Aerosol Growth by Cloud Processing during the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) (1901707)
Lynn M Russell1, Abigail Williams2, Veronica Z. Berta3, Christian Pelayo4, Jeramy Dedrick5, Sanghee Han6, Elavarasi Ravichandran7, Markus D Petters8, Lauren Robinson9, Rachel Ying-Wen Chang10, Israel Silber11, Dan Lubin1, Mark A Miller12, Jeremy J B Wentzell13, Michael J Wheeler13, John Liggio13 and EPCAPE Science Team, (1)University of California San Diego, Scripps Institution of Oceanography, La Jolla, CA, United States, (2)University of California Davis, Davis, United States, (3)University of California San Diego, La Jolla, United States, (4)Scripps Institution of Oceanography, La Jolla, United States, (5)Texas A&M University, College Station, United States, (6)University of California San Diego, Scripps Institution of Oceanography, La Jolla, United States, (7)University of California Riverside, Riverside, United States, (8)University of California Riverside, Center for Environmental Research and Technology, Riverside, United States, (9)Dalhousie University, Department of Physics and Atmospheric Science, Halifax, NS, Canada, (10)Harvard University, Cambridge, MA, United States, (11)Pacific Northwest National Laboratory, Richland, United States, (12)Rutgers University, New Brunswick, NJ, United States, (13)Environment and Climate Change Canada, Air Quality Research Division, Toronto, ON, Canada
 
Aerosols and Deep Convection in the Amazon Basin: A Spectrum of Possible Updraft Responses (1923493)
Christian P Lackner1, Dié WANG1 and Siddhant Gupta2, (1)Brookhaven National Laboratory, Upton, NY, United States, (2)University of Illinois at Urbana Champaign, Atmospheric Sciences, Urbana, United States
 
Physics-Informed Neural Networks for Aerosol Activation in High-Resolution WRF-Chem Simulations of Aerosol–Cloud Interactions over the Eastern North Atlantic (1973253)
Liran Peng, University of California Irvine, Earth System Science, Irvine, CA, United States, Yan Xia, University of California Irvine, Irvine, CA, United States, Peter N Blossey, University of Washington, Department of Atmospheric and Climate Science, Seattle, United States, Michael J Prather, Univ California Irvine, Irvine, CA, United States, Po-Lun Ma, Pacific Northwest National Laboratory, Richland, WA, United States, Hsiang-He Lee, University of California Davis, Davis, CA, United States, Xue Zheng, Lawrence Livermore National Laboratory, Livermore, CA, United States and Michael Pritchard, NVIDIA Corporation, Santa Clara, CA, United States
 
Aerosol Influences on Cloud Water: Insights From ARM EPCAPE Observations With Explainable Machine Learning (1999811)
Haipeng Zhang, University of Maryland Baltimore County, Baltimore, United States, Yunyan Zhang, Lawrence Livermore Nat Labs, Livermore, United States, Zhanqing Li, University of Maryland, Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary, College Park, United States and Youtong Zheng, University of Houston, Houston, United States
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