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Regularization methods for the inversion of infrared nadir sounding observations are currently investigated. An iterative Runge-Kutta type method for nonlinear ill-posed problems has been implemented and its performance has been studied using synthetic measurements. Comparisons with Tikhonov type inversion with a priori regularization parameter selection indicate that both methods are of similar accuracy; however, the Runge-Kutta method is less sensitive to regularization parameter variations. Furthermore, vertical column density retrieval from nadir infrared sounders such as AIRS will be used for validation of column densities retrieved from near infrared SCIAMACHY observations. Two closely related retrieval codes are used for L2 processing of SCIAMACHY near infrared and AIRS mid infrared spectra. First results of this intercomparison are shown.

EARLINET, the European Aerosol Research Lidar Network, is the first aerosol lidar network with the main goal to provide a comprehensive, quantitative, and statistically significant database for the aerosol distribution on a continental scale. Lidar measurements are systematically performed at each station and additional observations are performed to monitor special events. The data quality of the database is assured by intercomparisons at both instrument and algorithm levels. At present, the database is already useful to fill partially the gap in the aerosol vertical distribution knowledge, necessary for a better understanding of aerosol effects on climate and atmospheric processes. It will be useful to improve the quality of several satellite retrieval systems affected by the presence of aerosols, and in validation measurement campaign for future satellite missions like CALIPSO.