Model-assisted retrievals of aerosol properties from Polarization-sensitive Automated Lidar-Ceilometers and test applications to Vaisala CL61 measurements during desert dust transport episodes

Aerosols play a key role in air quality, weather, and climate. Ground-based active remote sensing can contribute to the continuous monitoring of aerosol vertical profiles, especially when operating within regional, national and international networks. In fact, networked Automated-Lidar-Ceilometers (ALC) are now widely used to this purpose, monitoring the low and middle troposphere. However, conversion of their raw data into quantitative geophysical information is not straightforward.

In this work, we present a model-supported approach to retrieve vertically-resolved aerosol optical and physical properties (aerosol backscatter and extinction coefficients, surface area, volume and mass concentrations) from elastic lidar systems. It extends previous results and processing capabilities of lidar and/or ALC data developed and employed within the Italian ALC network ALICENET (Dionisi et al., 2018; Bellini et al., 2024). In particular, we present here an upgraded version of the model, which relies on a Monte Carlo framework generating a large ensemble of light-scattering computations at multiple, lidar-relevant wavelengths (355, 532, 910, and 1064 nm) and targeted to reproduce a continental aerosol type mixed to low-to-moderate contributions of desert dust. With respect to previous model configurations (e.g., Dionisi et al., 2018), the new version simulate the coarse, dust particles as spheroids, taking advantage of the open-access spheroid package GRASP (Dubovik et al., 2006). This also allows computation of the aerosol depolarization ratio in addition to the other aerosol optical and physical properties. The model simulations are then used to derive mean functional relationships linking aerosol backscatter and particle depolarization ratio to the other aerosol properties. This upgraded version of the model was indeed developed within ALICENET to assist inversion of new commercially available ALC systems with polarization capability (PLC, as the Vaisala CL61). In this work, we will present: a) the numerical model simulations results, b) their evaluation through independent aerosol data from AERONET sun-photometers and 3) their practical use within the operative ALICENET inversion of PLC data to derive aerosol optical and physical properties. In fact, application of the new functional relationships shows improved agreement of PLC-retrievals with columnar aerosol optical depth and in situ mass measured at ground level in dust-loaded conditions. These results suggest that the proposed methodology could be applied to operational ALC/PLC networks operating in low-to-moderate dust-affected conditions, thus supporting radiative transfer, atmospheric chemistry, and air quality studies.

References:

• Dionisi, et al., A multiwavelength numerical model in support of quantitative retrievals of aerosol properties from automated lidar ceilometers and test applications for AOT and PM10 estimation, Atmos. Meas. Tech., 11, 6013–6042, https://doi.org/10.5194/amt-11-6013-2018, 2018.
• Bellini, et al., ALICENET– an Italian network of automated lidar ceilometers for four-dimensional aerosol monitoring: infrastructure, data processing, and applications, Atmos. Meas. Tech., 17, 6119–6144, https://doi.org/10.5194/amt 17-6119-2024, 2024.
• Dubovik et al., Application of spheroid models to account for aerosol particle nonsphericity in remote sensing of desert dust, J. Geophys. Res., 111, D11208, https://doi.org/10.1029/2005JD006619, 2006.