Abstract. The use of automated lidar ceilometer (ALC) systems for the
aerosol vertically resolved characterization has increased in recent
years thanks to their low construction and operation costs and their
capability of providing continuous unattended measurements. At the same time
there is a need to convert the ALC signals into usable geophysical
quantities. In fact, the quantitative assessment of the aerosol properties
from ALC measurements and the relevant assimilation in meteorological
forecast models is amongst the main objectives of the EU COST Action TOPROF
(“Towards operational ground-based profiling with ALCs, Doppler lidars and
microwave radiometers for improving weather forecasts”). Concurrently, the E-PROFILE program of the European
Meteorological Services Network (EUMETNET) focuses on the harmonization of
ALC measurements and data provision across Europe. Within these frameworks,
we implemented a model-assisted methodology to retrieve key aerosol
properties (extinction coefficient, surface area, and volume) from elastic
lidar and/or ALC measurements. The method is based on results from a large
set of aerosol scattering simulations (Mie theory) performed at UV, visible,
and near-IR wavelengths using a Monte Carlo approach to select the input
aerosol microphysical properties. An average “continental aerosol type”
(i.e., clean to moderately polluted continental aerosol conditions) is
addressed in this study. Based on the simulation results, we derive mean
functional relationships linking the aerosol backscatter coefficients to the
abovementioned variables. Applied in the data inversion of single-wavelength
lidars and/or ALCs, these relationships allow quantitative determination of
the vertically resolved aerosol backscatter, extinction, volume, and surface
area and, in turn, of the extinction-to-backscatter ratios (i.e., the
lidar ratios, LRs) and extinction-to-volume conversion factor
(cv) at 355, 532, and 1064 nm. These variables provide valuable
information for visibility, radiative transfer, and air quality applications.
This study also includes (1) validation of the model simulations with real
measurements and (2) test applications of the proposed model-based ALC
inversion methodology. In particular, our model simulations were compared to
backscatter and extinction coefficients independently retrieved by Raman
lidar systems operating at different continental sites within the European
Aerosol Research Lidar Network (EARLINET). This comparison shows good
model–measurement agreement, with LR discrepancies below 20 %. The
model-assisted quantitative retrieval of both aerosol extinction and volume
was then tested using raw data from three different ALCs systems
(CHM 15k Nimbus), operating within the Italian Automated LIdar-CEilometer
network (ALICEnet). For this purpose, a 1-year record of the ALC-derived
aerosol optical thickness (AOT) at each site was compared to direct AOT
measurements performed by colocated sun–sky photometers. This comparison
shows an overall AOT agreement within 30 % at all sites. At one site, the
model-assisted ALC estimation of the aerosol volume and mass (i.e.,
PM10) in the lowermost levels was compared to values measured at
the surface level by colocated in situ instrumentation. Within this
exercise, the ALC-derived daily-mean mass concentration was found to
reproduce the corresponding (EU regulated) PM10 values measured by
the local air quality agency well in terms of both temporal variability and
absolute values. Although limited in space and time, the good performances of
the proposed approach suggest it could possibly
represent a valid option to extend the capabilities of ALCs to provide
quantitative information for operational air quality and meteorological
monitoring.