Studies of aerosol-cloud interactions and estimates of the effective aerosol radiative forcing (ERF) of climate depend crucially on the vertical distribution of aerosol microphysical and radiative properties, but few reliable observations of such properties exist on a global scale. The 2024 launch of the EarthCARE mission provides new observations of aerosol extinction from the ATMospheric LIDar (ATLID) system. These observations are proving to be superior to past satellite-based lidar observations of aerosol extinction in accuracy because of the use of the high-spectral resolution lidar (HSRL) technique. These high-accuracy lidar observations can be used as input to machine-learning (ML) models to estimate cloud condensation nuclei (CCN at 0.4% supersaturation) and aerosol absorption (ABS at 532nm).We present novel ML-based CCN and ABS retrievals using the first full year of ATLID observations (September 2024 to August 2025) of aerosol backscatter, extinction, and depolarization as predictors. These higher-level aerosol properties are compared to retrievals of the same quantities derived from airborne HSRL observations by the WALES system (derived from WAter vapor Lidar Experiment in Space) during the ORCESTRA (ORganized Convection and EarthCARE STudies over the Tropical Atlantic) PERCUSION (Persistent EarthCARE Underflight Studies of the ITCZ and Organized Convection) campaign in the summer of 2024. We provide validation results of the ML-based CCN and ABS retrievals against ground-based in situ observations, which indicate relative errors less than 30% for all but the cleanest aerosol loading conditions. Based on the first year of ATLID observations, we present global maps of ML-derived CCN and ABS and suggestions for improvements in the ATLID observations. Finally, we discuss opportunities to study aerosol-cloud-climate interactions facilitated by these new retrievals and climatologies.