We develop data inversion algorithms that are used for inferring microphysical properties of aerosol pollution from remote sensing measurements and specialise in data from multiwavelength (3+2) Raman lidar and combinations of Raman lidar with Sun photometer.
We develop novel data inversion algorithms which are used to infer microphysical properties of particulate pollution. Microphysical properties are particle size distribution, mean particle size, as for example particle effective radius, complex refractive index and particle morphology. The latter parameter for example describes if particle are of spherical shape or if they exhibit more complex shape that is characteristic for mineral dust.
Our development work also includes making these algorithms available for use of data acquired with space-borne radiometers. A brief outline of the basic methodology is given for data inversion algorithms.
A historic overview on the development of the methodology for lidar applications can be found in Ansmann and Müller (2005).