Primary Convener:
Peng Wu, Pacific Northwest National Laboratory

Convener:
Chuanfeng Zhao, Peking University
Jonathan Jiang, NASA Jet Propulsion Laboratory
Kuan-Man Xu, NASA Langley Research Center
Jingjing Tian, Pacific Northwest National Laboratory

Early Career Convener:
Litai Kang, University of Washington

Chair:
Peng Wu, Pacific Northwest National Laboratory
Chuanfeng Zhao, Beijing Normal University
Xiaojian Zheng, Argonne National Laboratory
Jianhao Zhang, University of Miami
Dié WANG, Brookhaven National Laboratory
Litai Kang, University of Washington

Clouds play essential roles in the Earth system, yet their representations remain among the largest sources of uncertainty in models. Accurate, long-term observations and improved understanding of cloud processes are crucial for reducing these uncertainties. Recent advances in observational techniques, model simulations, and artificial intelligence and machine learning (AI/ML) methods have significantly enhanced our capability to analyze and interpret cloud-related data, providing deeper insights into cloud processes and their parameterizations.This session invites contributions focused on observations, analyses, and modeling of cloud properties and processes. Topics include, but are not limited to: 1) cloud observations and retrieval techniques; 2) analysis of cloud microphysical, macrophysical, and radiative properties; 3) quantification of cloud-related uncertainties; 4) parameterizations of cloud and precipitation processes in numerical models; and 5) applications of AI/ML techniques to advance cloud and precipitation research.

Index Terms
0320 Cloud physics and chemistry
0321 Cloud|radiation interaction
3311 Clouds and aerosols
1640 Remote sensing

Neighborhoods:
3. Earth Covering