Aerosol Cloud

Aerosol-cloud interactions (ACI) are a critical area of climate research, focusing on how atmospheric aerosols influence cloud properties and ultimately, Earth's radiative balance. Current research employs advanced machine learning techniques, including neural networks and variational autoencoders, to analyze high-dimensional datasets from satellite imagery and sophisticated cloud simulations, improving the accuracy of cloud microphysics modeling and ACI quantification. This work addresses significant uncertainties in climate models by providing more accurate representations of cloud formation and evolution, particularly concerning the effects of anthropogenic aerosols like those from ship emissions, and improving predictions of precipitation and renewable energy potential. Improved understanding of ACI is crucial for refining climate change projections and informing mitigation strategies.