A good knowledge of the aerosols is necessary due to the important role that they play in the Earth radiative balance; they also interact by several processes with human life, frequently harming human health. These processes depend on optical and microphysical proprieties of the particles and on their spatial distribution.
At present, the space-time distributions of atmospheric particles optical properties can be investigated by LIDAR systems, but the ability to determine microphysical properties from optical properties is still a challenge which can only be addressed by inverse methods and providing additional information on specific characteristics of different aerosols.
In order to identify different typologies of particles and determine their microphysical characteristics and optical properties, we started with a statistical study on the particle size distributions and complex refractive index, using the dataset which is available from AERONET project; an international network of sun-photometers that allows the access to an huge database of main characteristic parameters of the atmospheric aerosols.
A non-secondary objective of this study is the capability to obtain a target system for the validation of the inversion methods in use and/or under development.
We have selected several AERONET stations located in different part of the Earth. A consistent number of stations have been chosen in a random way. On the contrary, another amount of data was chosen to underline three different kind of particles source (Desert Dust, Marine and Volcanic Ash). For each station, eight data set has been taken referred to two days for season.
In order to parametrize the particles size distributions from AERONET we chosea three-modal lognormal distribution and we find the lognormal standard parameters (Area, Mode and Geometrical Standard Deviation) for each mode of the distributions. As concern the complex refractive index, the real and the imaginary parts are retrieved for the wavelengths corresponding to the sky radiance measurements on the average daily value.
The statistical analysis of the AERONET data has brought to three different types of results: a first one is represented by the variability ranges of the three modes parameters and by the maximum and minimum average value and standard deviation of each parameter. Secondly the same analysis has been performed for the complex refractive index at three wavelengths (355nm, 532nm, and 1064nm) finding a strong correlations between imaginary and real part of the refractive index at different wavelengths.
A third important result is the ability to determine several relationships between the parameters of the modal distributions, the refractive index and the optical parameters of the atmospheric particulate matter. These relations can constitute valuable elements for the development of effective inversion methods of optical lidar data.