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Synergy of CALIOP and ground-based solar radiometer data to study statistical characteristics of aerosols in regions with a low aerosol load
* 1 , 2 , 3 , 4 , 5 , 5 , 6 , 6 , 7 , 8 , 2 , 2 , 6 , 9
1  Head of Centre "Optical Remote Sensing", Institute of Physics, National Academy of Sciences of Belarus, Belarus
2  Leading Researcher, Institute of Physics, National Academy of Sciences of Belarus, Belarus
3  Teacher-Researcher, LOA, Universite de Lille, Lille, France
4  Distinguished professor, Deputy Director State Environment Protection Key Laboratory of Satellite Remote Sensing, of Aerospace Information Research Institute of CAS, Beijing, China
5  Researcher, Institute of Physics, National Academy of Sciences of Belarus, Belarus
6  Engineer, LOA, Universite de Lille, Lille, France
7  Senior Researcher, Institute of Physics, National Academy of Sciences of Belarus, Belarus
8  Assistant engineer, LOA, Universite de Lille, Lille, France
9  Doctor of Philosophy, State Environment Protection Key Laboratory of Satellite Remote Sensing, of Aerospace Information Research Institute of CAS, Beijing, China
Academic Editor: Alexander Kokhanovsky

Abstract:

Implementation of combined lidar and radiometer sounding of atmospheric aerosol with application of CALIOP lidar data, measured in the area of radiometric station (LRS-C technique) has increased the number of potential LRS-S measuring sites up to 500 all over the planet, except for polar regions with a latitude greater than 80°. However, scattered solar radiation background significantly reduces the signal-to-noise ratio of the recorded lidar signals, especially the depolarized component of the backscattered signal at 532 nm. It results in problems with application of LRS-C technique in regions with a low aerosol load. An aerosol load is considered low if aerosol optical depth (AOD) at the wavelength of 500 nm is below 0.1.

We propose a statistical approach to the formation of input data set and retrieving aerosol parameters from LRS-C data. A lot of lidar signals measured in the vicinity of a radiometric station during a certain time period constitute the “lidar” part of the statistical ensemble of input data. The radiometric information is represented by the columnar optical characteristics of the aerosol layer, retrieved from the radiometric observations coordinated with the satellite overpass.

The basic system of equations determines the relationship between the statistical characteristics of input data set and parameters of the aerosol model.

At the stage of solving the inverse problem, lidar information is represented by the average values and variance of lidar signals calculated from a large number input data that provide resulting high signal-to-noise ratio of averaged lidar signals.

In the frame of this work the LIRIC-2 code was developed for processing LRS-C data. LIRIC-2 contains program modules for creating the ensemble of input data and options for calculating the statistical characteristics of vertical distributions of aerosol concentration and optical parameters.

The statistical version of the LRS-C technique and the LIRIC-2 code were used to study the aerosol annual and seasonal changes in the Europe regions, in Antarctica and in mountainous areas.

Keywords: aerosol; ground-based and satellite remote sensing; CALIOP; AERONET; SONET
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