Mapping the vertical structure of aerosols and clouds is vital for climate science. We developed an AI model that reconstructs full atmospheric profiles from standard lidar data, even above signal attenuation. It accurately classifies aerosol and cloud types, capturing key atmospheric features. This cost-effective approach extends beyond sparse Cloudnet sites, enhancing monitoring and supporting improved weather and climate models.