Inverse Methods: a Powerful Tool for Evaluating Aerosol Data, Exemplified on Cases With Relevance for the Atmosphere and the Aerosol Climate Effect

Abstract

For a complete description of a given aerosol, more than one parameter is necessary, e.g. parameters concerning size distribution, chemical composition, and particle morphology. On the other hand, most instruments measuring aerosol properties are sensitive mostly to one parameter, but cross-sensitive to others. These cross-sensitivities are often eliminated by assumptions during data evaluation, inducing systematic uncertainties in the results. The use of assumptions can be reduced by combining the information of several instruments on the same aerosol and using inverse methods for interpretation of the data. The presentation focuses on two application examples of these methods. The first example concerns a size distribution inversion algorithm that combines data from several instruments into one size distribution. The second example deals with an algorithm that retrieves the aerosol asymmetry parameter (with respect to particle scattering) from measurements of the aerosol absorption and spectral scattering and hemispheric backscattering coefficients, thereby providing a set of parameters that completely describes an aerosol with respect to its direct climate effect.