Description:

The characterization of aerosols, clouds, and precipitation in datasets from remote sensing instruments is key to understanding many weather and climate processes. In many ways artificial intelligence (AI) and machine learning (ML) based approaches have improved upon physically-based algorithms or offered alternative perspectives on the estimation of these properties. This session aims to encourage submissions focused on AI and ML applications to estimating these properties from both ground-based and space-based remote sensing instruments. This can include (but is not necessarily limited to) validation studies, algorithm intercomparisons, dataset curation and efforts toward model interpretability.