An Adaptive Base Point Algorithm for the Retrieval of Aerosol Microphysical Properties

We propose a new iterative algorithm for the retrieval of the microphysical properties of stratospheric and tropospheric aerosols from multiwavelength lidar data. We consider the basic equation as an ill-posed problem and solve the system derived from spline collocation via a Padé iteration. The algorithm takes special care of the fact that the reconstruction of the distribution via spline collocation is very sensitive to the choice of base points of the chosen spline basis. The algorithm makes use of this fact by changing the base points used for the spline collocation at certain iteration steps. In addition, the effects of projection to ensure a nonnegative solution are examined. We tested how well this and other algorithms are suitable for retrieving the complex refractive index of the particles as well. We also examine whether the algorithm is capable of distinguishing between different, very small imaginary parts of the refractive index, which is often a main problem in practice. Finally, the algorithm is applied to real multiwavelength Raman lidar data and our results are partially validated by the thermodynamic chemical model Isorropia II.