New operational perspective to identify aerosols and hydrometeors in real-time with a pioneering algorithm (CONIOPOL) based on single-wavelength polarization lidar (CL61)

Abstract

Air quality monitoring and climate studies require continuous, vertically resolved observations to characterize aerosols and their impact on radiation, cloud microphysics, and atmospheric composition. In this study, we present CONIOPOL (CONIOlogy + POLarization), an automated depolarization-based classification algorithm developed with the polarized Automatic Lidar Ceilometer (ALC), CL61 (Vaisala Oyj, Finland). The algorithm combines volume linear depolarization ratio (VDR), attenuated backscatter (ATB), and cloud-base height (CBH) retrievals to distinguish between aerosols, cloud phase, and precipitation, and to further classify aerosol subtypes. One full year (February 2024–January 2025) of observations collected at Uccle (Belgium) was analyzed to investigate the seasonal and vertical distributions of the identified atmospheric targets. Aerosol classifications were assessed through a conditional comparison, using Copernicus Atmosphere Monitoring Service (CAMS) Global Forecast products. CONIOPOL successfully identified dust, smoke/marine, continental, and mixed aerosol environments showing strong temporal and vertical correspondence with CAMS, in particular for transported mineral dust and smoke plumes. Despite its spectral limitations, the single-wavelength polarization-enabled ALC allows continuous, high-resolution aerosol classification over extended periods, providing a consistent observational dataset for investigating the seasonal evolution of aerosol types over mid-latitude Europe. These findings underscore the potential of polarization-enabled ALCs for long-term aerosol climatology and air quality monitoring, bridging temporal gaps between satellite, in situ, and multi-wavelength lidar observations.