HETEAC-Flex model: comparative evaluation of six forward model configurations for dust cases using ground-based Lidar observations in Limassol

The Cyprus Atmospheric Remote Sensing Observatory National Facility (CARO NF) of Eratosthenes Centre of Excellence plays a key role in atmospheric research and the characterization of atmospheric conditions in the Eastern Mediterranean. Equipped with cutting-edge remote sensing instruments including a Polly^ΧΤ Polarization Raman Lidar, a Cloud Radar and a Solar Infrastructure, CARO provides critical observations for studying aerosol properties, cloud dynamics, and radiative processes. Its advanced capabilities make it an essential ground-based station for satellite validation studies, particularly in the context of the EarthCARE mission (ESA/JAXA). To ensure compatibility between ground-based observations and satellite measurements, the HETEAC-Flex model, introduced by A. A. Floutsi et al., 2024 [1] have been applied for the aerosol layer classification. This model was created to validate the aerosol classification of ATLID (ATmospheric LIDar) measurements, onboard EarthCARE, by providing a robust comparison framework. Based on an Optimal Estimation Method (OEM) HETEAC-Flex provides six forward retrieval modes, each incorporating different sets of optical properties including Particle linear depolarization ratio at 355, 532 nm, Lidar ratio at 355, 532 nm, Extinction-related Ångström exponent at 355/532 nm and the Backscatter-related color ratio for 532/1064 nm. The typing scheme enables the identification of four aerosol components of aerosol mixtures, absorbing and less-absorbing fine-mode particles and spherical and non-spherical coarse-mode particles (FSA, FSNA CS, CNS, respectively). CARO’s Polly^ΧΤ lidar in Limassol can retrieve all the optical properties needed for the utilization of all the six retrieval modes. In this study, we apply the HETEAC-Flex model to several dust cases recorded in Limassol between the period 2021-2024, aiming to determine which retrieval mode is the optimal for the characterizing dust aerosol layers.